[Editor's Note: Chris Jaffe, writer for The Hardball Times, has written a new book, “Evaluating Baseball’s Managers.” The commentary below is the introductory essay to EBM’s Chapter 5, which is titled “Rise of the Fundamentalists, 1893-1919.”]

The importance of managers peaked at the turn of the century. They inhabited a specific period in the evolution of baseball between two crucial metamorphoses of the game. First, in the late nineteenth century, field generals like Gus Schmelz and Ned Hanlon caused the rise of the modern manager and the extinction of the old business manager. By placing a premium of the preparation of players before contests and handling strategy during them, the position of manager came into its own. A generation later, the rise of the front office diminished the manager’s position by serving as a rival power source within the franchise. Between these transformations, managerial power in the sport crested. Managers ascended into the ranks of ownership with greater frequency than at any other time in baseball history, as there were fewer steps between themselves and owners. Even those who did not own a share of the club frequently had considerable autonomy. When John McGraw became Giants manager, he told the owners which players to keep or remove from the roster, indicating who called the shots for that franchise. Not all managers wielded such authority in this era, and many held considerable power in the future, but they had their strongest opportunity to control the entire franchise at the turn of the century.

Managerial power also reached its zenith because coaching was more important in this period than any other. Old time baseball is often remembered as a glory era, when players dedicated themselves to the craft of the game in a way that modern players with their supposedly softer attitudes never could. Though this attitude is very frequent in the modern day, ideas that the old-timers were better, wiser, and more dedicated are as old as the game itself.

People look at John McGraw and his devotion to those precious fundamentals. He ordered his players come to the park to practice and work out for several hours every day, making the athletes perform precisely in accordance with his formidable will. Other managers, like Frank Chance, made a similar fervent push for sound ball. Chance’s Cubs had a well-earned reputation as the sharpest players in the league.

However, not only was the deadball era far from being the golden era of fundamentals, but the evidence used to make it seem like a Mecca of proper execution are the very facts that indicate otherwise. John McGraw did not want his players practicing constantly because they were so committed, but because those who earned a spot in major league baseball commonly displayed poor fundamentals. The book Crazy ‘08 by Cait Murphy provides an interesting window into baseball during the 1908 NL pennant race. Despite focusing on teams that diligently practiced their basics – McGraw’s Giants and Chance’s Cubs – examples of shoddy play litter the book. It was not a matter of errors; the gloves and conditions of the day made muffed grounders understandable. The problems went deeper. Virtually every game contained at least one boneheaded play that could not be blamed on the conditions. Flies landed between fielders. A base runner would be doubled off on a pop up. An outfielder would misplay a grounder for an inside-the-park home run. These plays still happen, but not nearly as often. If the Cubs and Giants played like that, imagine how the doormats played. There were also some extremely smart plays, but the floor for proper conduct was much lower in 1908.

It seems strange that teams that practiced so religiously played so poorly, but think for a second. Much of what is now received wisdom was still being worked out. In the last quarter of the nineteenth century, players slowly began figuring out how to work together, or back each other up. For example, what should a catcher do when a base runner is caught in a run-down between first and second? Where should the shortstop go when the runner on first heads for third on a single to right? People are not born knowing the answers.

Look at it from the point of view of someone born in 1879 earning a roster slot in 1900. He grew up in a world where even the best players at the highest levels were still learning the core basics. It did not trickle down to Iowa’s cornfields or Pennsylvania’s coal mines overnight. Neither TV nor radio existed to teach him how the pros acted. Odds were very good he had never seen a big league game, and may not know anyone who has. Sandlot baseball has always been self-regulating, but there is usually at least some fundamental knowledge for kids to rely on. When he starts playing semipro ball, his manager was likely another player, probably under 30 years old himself. That man hopefully has some exposure to the basics being threshed out, but that was not guaranteed. Even if the skipper had basic knowledge of fundamentals, perhaps he cannot coach well. Depending on the club’s finances, he might be a business manager. If a kid could hit or possessed a strong arm, he would receive playing time, no matter how ignorant he was of fundamentals.

Thus you end up with the following story told by baseball historian Fred Stein. In 1897, a rawboned young buck called Honus Wagner began playing for the Louisville Colonels. His manager, a not yet 25-years-old Fred Clarke, told the kid to “lay one down” in his next at bat. Instead, Wagner hit a home run. Appreciative of the result but curious as to why the rookie ignored his instructions to bunt, Clarke asked Wagner what happened. Shamefacedly, the future Hall of Famer shortstop admitted he had never heard the phrase “lay one down” before. He had no idea what his manager was talking about. This was the situation Clarke, McGraw, and Chance contended with.

Fundamentals first have to be developed. Then they diffuse. Next, their instruction becomes institutionalized. Once the lessons become second nature to one generation, the next wave can be fully and immediately immersed in them. Nowadays, high schoolers are better versed in solid fundamentals than many big leaguers a century ago. After enough years and decades go by, fundamentals are so ingrained even Little Leaguers learn them, and you assume that everyone getting paid to play the game knows them by heart. Even a poor kid from the Dominican Republic has access to more knowledgeable adults and coaches than was the case for an 1890s Wisconsin farm boy.

This might oversell the point. At SABR’s annual convention in 2007, I heard Cait Murphy talk about what she learned from researching her book, and she was surprised at how advanced the level of play sometimes was. Examples of intelligent play existed – for instance the Cubs had worked out an impressive system of defensive signals amongst each other. However, such plays coincided with embarrassing miscues, as the floor for acceptable play was quite low. A wide discrepancy existed in the quality of fundamental ball played in these years. The more advanced examples of shrewd gamesmanship were often the result of major league managers instilling those values into their charges.

This explains why coaching fundamentals mattered so much for this generation of managers. The basic ideas of how to play had been worked out, now it was a time to diligently instruct them to the players. McGraw, Chance, and their ilk focused on the fundamentals because their players so sorely lacked knowledge that these pointers could significantly improve squads.

A century later, in his bestseller Moneyball, Michael Lewis introduced the phrase “market inefficiency” to baseball fans. He argued the 2002 A’s won 103 games despite a low payroll because they realized the baseball world undervalued the importance of on-base percentage. By exploiting this gap between reality and perception, A’s GM Billy Beane made his team a winner. A century earlier, the market inefficiency was fundamentals. The best managers, such as McGraw and Chance, were those who could transform raw clumps of talent into majestic creations. One should not underestimate how important sound play was back then. In the early twentieth century some teams made 100 fewer errors a year than their rivals. Combined with improved base running, solid mental play, and all those other little things, proper fundamentals were worth many wins.

Chris Jaffe is an instructor of history and a columnist for the The Hardball Times. He lives in Schaumburg, Illinois. For more information about Chris Jaffe and Evaluating Baseball’s Managers, visit the author’s website.

Permalink | Comments (1)

Author's Note: Ernie Harwell's birthday is January 25th. When I sat down to start writing this article last month, I had that birthday in mind as a deadline. I thank Rich for allowing me to print it here in time for time for Ernie's birthday. Happy Birthday Ernie. Listening to you broadcast a game was always a pleasure.

In 1953, a baseball fan in New York City turning the radio dial had several delightful choices. The trio of Red Barber, Connie Desmond and Vin Scully were the voices for the Dodgers; Russ Hodges and Ernie Harwell called Giant games; Mel Allen, Joe E. Brown and Jim Woods were the broadcasters for the Yankees. Never before and not since have so many excellent broadcasters congregated in one city in one season to broadcast big league baseball.

Before 1939, the three New York teams, fearful that radio play by play would curtail attendance, kept radio broadcasts out of their ballparks. There were some exceptions to the radio ban. A few opening day and other scattered games were aired. All-Star games and the World Series were broadcast on New York radio stations. However, New Yorkers were unable to hear major league baseball on a regular basis until Larry MacPhail, brought to New York from the Cincinnati Reds to take over operation of a moribund Brooklyn Dodger franchise, broke the radio blackout in 1939.

Red Barber was the first of the seven legendary broadcasters of 1953 to take the air for a New York team for a full season of games. Red's first broadcasting job, taken while he was a student at the University of Florida, was at radio station WRUF in Gainesville, Florida. During his time at WRUF, Barber was able to hear the powerful signal of Cincinnati's WLW at his home in Gainesville. Red followed that radio signal to its source to audition for a job at the radio station that has long been dubbed as "The Nation's Station" because of the wide sweep of its AM transmitter.

In 1934, Red realized his goal of a job at WLW. Powel Crosley, the owner of stations WSAI and WLW in Cincinnati, took over control of the Cincinnati Reds during the Great Depression. With a team and two radio stations, Crosley naturally looked for a broadcaster to air the games of the team he owned. There were plenty of capable broadcasters in the Cincinnati area, but the job went to the young man in Florida who had never broadcast or even seen a big league baseball game.

Red's radio work involved more than sports and baseball broadcasts. Only about twenty Reds games were broadcast on the radio in 1934, so Red worked more as a staff announcer than as a baseball broadcaster in his first year in Cincinnati. The next year Red's baseball broadcasting career blossomed. Larry MacPhail brought lights to the Reds home park in 1935, and the Reds played the Philadelphia Phillies in the first night game in major league history on May 24th. Red Barber broadcast that game over the new Mutual Broadcasting network. Red's call of the major's first night game was the first sporting event ever carried by Mutual. After the end of the regular season Red was back in the national spotlight as a broadcaster for Mutual's coverage of the 1935 World Series between the Cubs and Tigers.

Red stayed in Cincinnati until the end of the 1938 season. Powel Crosley did not want to see his talented broadcaster leave. Red was offered more money to stay in Cincinnati than he would make in Brooklyn, but the lure of greater career possibilities in New York caused Red take the Dodger job.

Mel Allen will always be remembered as the voice of the Yankees. However during his early years as a baseball broadcaster Mel was actually the voice for two major league teams, the Giants and the Yankees. After Brooklyn broke the New York radio blackout, the Yankees and the Giants in 1939 joined forces to broadcast their home games over WABC. Brooklyn broadcast its entire schedule, home and away, although road games were recreated.

The principal broadcaster for the Yankee and Giant games in 1939 was Arch McDonald, a veteran broadcaster who had done Senator games in Washington, DC. McDonald's assistant was Garnet Marks. Marks was fired early in the season, and in June of 1939, Mel Allen was hired to take his place. After the 1939 season, McDonald returned to Washington and Allen became the primary broadcaster for Yankee and Giant home games in 1940.

Like Red Barber, Mel Allen was raised in the South. At the age of fifteen Mel enrolled at the University of Alabama. After completing his undergraduate degree, he began law school, also at the University of Alabama. While in law school, Mel became the public address announcer for University of Alabama football games. Shortly before the 1935 season the radio broadcaster for University of Alabama football games quit. The P.A. announcer was transferred to the radio booth to call Alabama football and a brilliant broadcast career was born.

In 1936, Mel traveled to New York for a winter vacation. While in New York he decided to audition for a job, and he landed a staff position at CBS radio in early 1937. Allen appeared in a variety of capacities for CBS including game shows, soap operas and big band broadcasts. In 1938 Mel appeared along with France Laux and Bill Dyer for CBS radio coverage of the World Series between the Cubs and Yankees. It was the first of many World Series broadcasts for perhaps the most recognizable voice in baseball broadcasting history.

Connie Desmond was the third of the seven legendary broadcasters to arrive in New York. In 1942 Desmond was hired to work at radio station WOR. Connie began his broadcasting career in 1932 in his hometown, Toledo, Ohio. During the 1942 baseball season, Connie teamed up with Mel Allen to broadcast Giant and Yankee home games over WOR. Connie also worked at WOR in a variety of capacities, including music shows that featured his own singing.

Red Barber's assistant broadcaster, Al Helfer, went into the military after the 1942 season. Desmond met with Barber and asked for Helfer's job. Connie was hired as Barber's assistant. In 1943 the Giants and Yankees did not broadcast any of their games, so Connie and Red were the only big league broadcasters on the air in New York during the 1943 season.

After World War II, a pivotal figure in New York baseball broadcasting returned from military duty. Larry MacPhail returned to New York, but not with the Dodgers. MacPhail became a co-owner of the Yankees and once again he brought change to baseball broadcasting in New York. MacPhail was not satisfied with the broadcasting partnership between the Giants and Yankees. In 1946, the Yankees began broadcasting all their games, home and away, on WINS. Mel Allen, also out of the military, returned as the principal Yankee broadcaster. The Giants hired Jack Brickhouse as their primary broadcaster in 1946. For the first time, all three New York teams were on the radio for a complete season of home and away games.

Russ Hodges was the fourth of the legendary broadcasters to reach New York. In 1946, Russ was hired to assist Mel Allen on Yankee broadcasts. Before taking the Yankee job, Hodges broadcast for the Cubs and White Sox in Chicago, and for the Senators in Washington, DC. Like Allen, Russ Hodges was a law school graduate. Hodges stayed with the Yankees until the Giants hired him to be their primary broadcaster for the 1949 season.

Ernie Harwell arrived in New York during the 1948 season to broadcast for the Brooklyn Dodgers. Ernie began his baseball career at an early age. When he was five years old he was a bat boy for visiting teams of the minor league Atlanta Crackers. At the age of sixteen, Ernie became the Atlanta correspondent for the "Baseball Bible," the Sporting News. Harwell began his broadcasting career at WSB in Atlanta in 1940 after graduating from Emory University. Ernie broadcast Atlanta Cracker games before the war, and after being discharged from the Marines, he resumed his baseball broadcasting career with the Crackers in 1946.

Ernie was brought to New York to fill in for an ailing Red Barber during the 1948 season. That year, the Dodgers began live broadcasts of their road games. Red Barber became severely ill with a bleeding ulcer during a Dodger road trip. Connie Desmond took over as the sole broadcaster for the Dodgers while Dodger management sought a replacement for Red. The Dodgers looked to Atlanta and the talented Harwell to fill in during Red's illness. However, Ernie was under contract to the Crackers, so Ernie's boss in Atlanta, Earl Mann, needed to be compensated for losing his play by play broadcaster. For the only time in major league history, a team traded a player for a baseball broadcaster when the Dodgers shipped minor league catcher Cliff Dapper to Atlanta for the services of play-by-play broadcaster Ernie Harwell.

Ernie remained with Red Barber and Connie Desmond through the end of the 1949 season. Ernie left the Dodgers to join Russ Hodges in broadcasting New York Giant games in 1950. To the delight everyone who has had a chance to listen to him during the past sixty years, Red Barber chose Vin Scully to replace Ernie in the Dodger broadcast booth.

Vin Scully graduated from Fordham in 1949. While he was in college he worked at the campus FM station and also played the outfield on the varsity baseball team. Vin sent letters to radio stations up and down the Eastern seaboard in search of a broadcasting job after graduation. He landed a temporary job as a summer replacement announcer in Washington, DC for the CBS affiliate, WTOP. Management at WTOP appreciated his talent, but at the end of the summer, they had no permanent job for him. Vin left Washington with a promise of a future job at WTOP, but no immediate employment.

Vin returned to his home in New York and contacted CBS radio in search of a job. Vin was able to meet with Ted Church, who was director of CBS radio news. Church had no job for him, but he did introduce Vin to Red Barber, who in addition to being the Dodger play-by-play broadcaster, was the director of sports for CBS radio. Red had no job to offer, though he was favorably impressed after talking with the youngster.

One of Red's primary duties as director of sports for CBS radio was selecting broadcasters to go to various college games throughout the country for the CBS college football roundup show. Luckily for Vin, in 1949 Red was unable to find a broadcaster for the Boston University-University of Maryland football game played at Boston's Fenway Park. Red remembered the young man he had met at CBS headquarters in New York and arranged for Vin to fill in at the last minute in Boston. Vin's performance impressed Red enough to give the youngster another assignment on the football roundup and a chance to be a major league broadcaster for the Dodgers.

Vin joined the Dodger broadcast booth after an eventful meeting with Red Barber and Branch Rickey that took place after Red returned to New York from a 1949 college football broadcast on the West coast. In an interview with author Ted Patterson for the splendid book, The Golden Voices of Baseball, Vin recalled the terms of his employment: "The agreement reached was that I would go to spring training on a one-month option. Either I make it, or they could lose me in the Everglades."

Jim Woods was the last of the seven legendary broadcasters to reach New York. In 1953, Jim teamed with Mel Allen to broadcast Yankee games. Joe E. Brown joined Woods and Allen for some Yankee broadcasts, but Brown primarily worked on the Yankee pre- and post-game shows. Woods had an eventful career before he arrived in New York. Jim replaced Ronald Reagan as the football radio voice of the Iowa Hawkeyes in 1939. After spending four years in the military during World War ll, Woods eventually landed in Atlanta where he replaced Ernie Harwell after Ernie left the Crackers to broadcast for the Brooklyn Dodgers. Woods followed Ernie's path to New York as a major league broadcaster in 1953.

The seven splendid broadcasters were together in New York for just one season. Ernie Harwell left the Giants to become the principal broadcaster for the Baltimore Orioles in 1954. Harwell's departure was not the only shift in the New York baseball broadcasting landscape. After the 1953 season, Red Barber left the Dodgers to join Mel Allen and Jim Woods in the Yankee broadcast booth.

Vin Scully and Connie Desmond continued as Dodger broadcasters in 1954. However, Connie missed some games because of alcoholism. In 1955, the only year Brooklyn won the World Series, Connie was gone from Dodger broadcasts. Dodger owner Walter O'Malley gave Connie a last chance to continue his career in 1956, but when Connie began drinking again, he was replaced for good by Jerry Doggett before the end of the season.

The Yankee broadcast team of Mel Allen, Jim Woods and Red Barber stayed together until the end of the 1956 season. Phil Rizzuto, whose Yankee playing career ended in 1956, was hired to replace Woods as a Yankee broadcaster. Woods was able to stay in New York by shifting to the Giants broadcast booth in 1957.

The departure of the Brooklyn Dodgers and New York Giants for Los Angeles and San Francisco after the 1957 season forever changed the face of baseball and baseball broadcasting in New York. Vin Scully and Russ Hodges relocated with their teams to the West coast. Remarkably, in 2010, Vin will begin his 61st consecutive season as a Dodger broadcaster. After the 1957 season, Jim Woods departed New York for Pittsburgh, where he teamed with Bob Prince to form one of the best play-by-play tandems in the history of baseball broadcasting.

In 1964, Mel Allen was fired by the Yankees. Mel broadcast for the Atlanta Braves and Cleveland Indians after leaving New York. Mel returned to the Yankees as a cable-TV announcer for SportsChannel in 1978. His primary fame though after 1964 was as the voice for the popular TV show, This Week in Baseball. TWIB with Mel Allen was on the air for seventeen terrific years.

Red Barber, the man who in 1939 was the first broadcaster for a New York team, was the last of the seven legendary broadcasters of 1953 to broadcast for a team in New York. After the 1966 season Red was fired by the Yankees. In the last years before his death, Red returned to radio as a regular guest of Bob Edwards on NPR's Morning Edition.

Sources:

Sports on New York Radio: A Play by Play History by David J. Halberstam is an absolute gem for anyone interested in the history of sports broadcasting. Ted Patterson's Golden Voices of Baseball is rich in pictures and commentary about the history of baseball broadcasting. The book includes two CD's containing excerpts of the author's interviews with various broadcasters. Both books are well worth their purchase price.

Also useful in this article were interviews of Vin Scully and Red Barber broadcast on Larry King's radio show for Mutual in 1982. A partial transcript of the King-Barber interview is available at Dodger Thoughts. I also used material from a radio program produced by a Cincinnati NPR station that was narrated by Marty Brennaman. The CD is available for purchase through the Cincinnati radio station's internet site.

Ross Porter's essay about Ernie Harwell, gives some details about Ernie's life that I included in my article. Also, Ernie has an audio scrapbook that is rich in information and is a delight to hear. It is available for purchase on the internet.

Some of the material about Mel Allen was taken from Mel's obituary in the New York Times. The obit from the New York Times is online. There are a few errors in the obituary though. Also helpful was a taped interview of Mel done by baseball broadcast historian Curt Smith.

Stan Opdyke grew up on the East Coast listening to baseball on the radio. He still prefers baseball on the radio (if the broadcasters are good) to baseball on TV.

Permalink | Comments (13)

The game of baseball as played today at the amateur level is very different from the game I played growing up in Rumford, Maine in the early 1960s. In my youth, wood bats ruled. Nowadays, almost no one outside the professional level uses wood bats, which have largely been replaced by hollow metal (usually aluminum) or composite bats. The original reason for switching to aluminum bats was purely economic, since aluminum bats don’t break. However, in the nearly 40 years since they were first introduced, they have evolved into superb hitting instruments that, left unregulated, can significantly outperform wood bats. Indeed, they have the potential of upsetting the delicate balance between pitcher and batter that is at the heart of the game itself. This state of affairs has led various governing agencies (NCAA, Amateur Softball Association, etc.) to impose regulations that limit the performance of nonwood bats. The primary focus of this article is on the techniques used to measure and compare the performance of bats.

Any discussion of bat performance needs to begin with a working definition of the word “performance.” Or, said a bit differently, what is meant by the statement, “bat A outperforms bat B”? Among people who have thought about this question, a consensus has emerged that a good working definition of performance is batted ball speed (or simply BBS). Generally speaking, if you want to improve your chances of getting a hit, then you want to maximize BBS, regardless of whether you are swinging for the fences or just trying to hit a well-placed line drive through a hole in the infield. The faster the ball comes off the bat, the better are your chances of reaching base safely. So, we will say that bat A outperforms bat B if the batter can achieve higher BBS with bat A than with bat B.

Which then brings up the next question: What does BBS depend on? I answer that by writing down the only formula you will find in this article:

This “master formula” is remarkably simple in that it relates the BBS to the pitch speed, the bat speed, and a quantity q that I will discuss shortly. It agrees with some of our intuitions about batting. For example, we know that BBS will depend on the pitch speed, remembering the old adage that `'the faster it comes in, the faster it goes out.'' We also know that a harder swing—i.e., a larger bat speed--will result in a larger BBS. All the other possible things besides pitch and bat speed that BBS might depend on are lumped together in q, which I will call the “collision efficiency.” As the name suggests, q is a measure of how efficient the bat is at taking the incoming pitch, turning it around, and sending it along its merry way. It is an important property of a bat. All other things equal, when q is large, BBS will be large. And vice versa. For a typical 34-inch, 31-oz wood bat impacted at the “sweet spot” (about 6 inches from the tip), q is approximately 0.2, so that the master formula can be written BBS = 0.2*(pitch speed) + 1.2*(bat speed). This simple but elegant result tells us something that anyone who has played the game knows very well, at least qualitatively. Namely, bat speed is much more important than pitch speed in determining BBS. Indeed, the formula tells us that bat speed is six times more important than pitch speed, a fact that agrees with our observations from the game. For example, we know that a batter can hit a fungo a long way (with the pitch speed essentially zero) but cannot bunt the ball very far (with the bat speed zero). Plugging in some numbers, for a pitch speed of 85 mph (typical of a good MLB fastball as it crosses home plate) and a bat speed of 70 mph, we get BBS=101 mph, which is enough to carry the ball close to 400 ft if hit at the optimum launch angle. Each 1 mph additional pitch speed will lead to about another 1 ft, whereas an extra 1 mph of bat speed will result in another 6 ft. On the other hand, if the bat were a “hotter bat” with q=0.22, that would add 3 mph to BBS, adding a whopping 18 ft to a long fly ball.

The master formula tells us that the quantities that determine bat performance are the collision efficiency and the bat speed, leading us to ask our next question. What specific properties of a bat determine its bat speed and collision efficiency? There are two such properties: the ball-bat coefficient of restitution (BBCOR) and the moment of inertia (MOI). In the following paragraphs, I’ll explain what these properties are and how they contribute to bat performance. The interplay among the various quantities is shown schematically in the picture below.

Let’s start with the BBCOR, which is a measure of the “bounciness” of the ball-bat collision. First a brief digression. During a high-speed ball-bat collision, the ball compresses by about 1/2 of its natural diameter and sort of wraps itself around the bat, as shown in the accompanying photo. It then expands back out again, pushing against the bat. During this process, much of the initial energy of the ball is converted to heat due to the friction from the rubbing of threads of yarn against each other. Try dropping a baseball onto a hard rigid surface, such as a solid wood floor. The ball bounces to only a small fraction of its initial height, reflecting the loss of energy in the collision with the floor. A wood bat with its solid barrel behaves more or less like a rigid surface. But a hollow aluminum bat is different since it has a thin flexible wall that can “give” when the ball hits it. Some of the ball’s initial energy that would otherwise have gone into compressing the ball instead goes into compressing the wall of the bat. The more flexible the wall, the less the ball compresses and therefore the less energy lost in the collision. This process is commonly called the “trampoline effect,” and the BBCOR is simply a quantitative measure of that effect. A wood bat has essentially no trampoline effect and has a BBCOR ≈ 0.50. Hollow bats can have a substantially larger BBCOR, leading to a larger q and a correspondingly larger BBS. For example, a bat with BBCOR = 0.55 will have about a 5 mph larger BBS. Indeed, the technology of making a modern high-performing bat is aimed primarily at improving the trampoline effect—i.e., increasing the BBCOR and consequently the BBS. For aluminum this is achieved by developing new high-strength alloys that can be made thinner (to increase the trampoline effect) without denting. The past decade has seen the development of new composite materials that increase the barrel flexibility beyond that achievable with aluminum, giving rise to a new generation of high-performing bats.

We now turn to the MOI, which depends on both the weight of the bat and the distribution of the weight along its length. For a given weight, the MOI is largest when a larger fraction of the weight is concentrated in the business end of the bat (i.e., the barrel). The MOI affects bat performance in two ways in that both q and the bat speed depend on it. A larger MOI means a larger q (and vice versa), in complete agreement with our intuition. A heavier bat will be more efficient than a light bat in transferring energy to the ball. But, contrary to popular belief, it is not the total weight of the bat that matters but rather the weight in the barrel, where the collision with the ball occurs. That’s why it is the MOI that matters and not just the weight. But a larger MOI also means that the bat won’t be swung as fast, which again agrees with our intuition. Once again, research has shown that it is the MOI of the bat and not just the weight that affects swing speed.

The fact that the MOI affects bat performance in two opposite ways raises an interesting question. If I have two bats with the same BBCOR but with different MOI, which one will have the larger BBS? For example, if I “cork” a wood bat, which reduces its MOI, will the resulting increase in swing speed compensate for the reduction in collision efficiency? Current research suggests that the answer is “no” and that corking a bat does not lead to a larger BBS. For a detailed account, see this article. By the way, corking a wood bat does have some important advantages, even though higher BBS is not one of them. By reducing the MOI, the batter will have a “quicker” and more easily maneuverable bat, allowing him to wait a bit longer on the pitch and to make adjustments once the swing has begun. So, although corking a bat may not lead to higher BBS, it certainly may lead to better contact more often.

For bats of a given length and weight, the MOI will generally be smaller for an aluminum bat than for a wood bat. After all, a wood bat is a solid object, so a larger fraction of its weight is concentrated in the barrel than for a hollow nonwood bat. Here is another simple experiment you can do. Take two bats of the same length and weight (e.g., 34”, 31 oz), one wood and one aluminum, and find the point on the bat where you can balance it on the tip of your finger. You will find that the balance point is farther from the handle for the wood bat than for the aluminum bat, showing that a larger concentration of the weight is in the barrel for the wood bat. However, keeping in mind the corked bat discussion, the lower MOI for an aluminum bat results in no net advantage or disadvantage for BBS. The real advantage in BBS of aluminum over wood is in the BBCOR (i.e., the trampoline effect).

Let’s talk briefly about how bat performance is measured in the laboratory. Details can be found at this web site. Briefly, the basic idea is to fire a baseball from a high-speed air cannon at speeds up to about 140 mph onto the barrel of a stationary bat that is held horizontally and supported at the handle. Both the incoming and rebounding ball pass through a series of light screens, which are used to measure accurately its speed. The collision efficiency q is the ratio of rebounding to incoming speed. The MOI is measured by suspending the bat vertically and allowing it to swing freely like a pendulum while supported at the handle. The MOI is related to the period of the pendulum. Once q and the MOI are known, these can be plugged into a well-established formula to determine the BBCOR. To calculate BBS, the master formula is used along with a prescription for specifying the pitch and bat speeds, the latter of which will depend inversely on the MOI.

Various organizations use this information in different ways to regulate the performance of bats. The Amateur Softball Association regulates BBS, using laboratory measurements of q and MOI along with the prescriptions noted above to calculate BBS using the master formula. For the past decade, the NCAA has regulated baseball bats by requiring that q is below some maximum value and the MOI is above some minimum value, the latter limiting the swing speed. Together the upper limit on q and lower limit on the MOI effectively limit the maximum BBS. The maximum q is set to be the same for nonwood as for wood. The lower limit on MOI is such that the best-performing nonwood bat outperforms wood by about 5 mph. You may have seen the words “BESR Certified” stamped on NCAA bats. The BESR is shorthand for the Ball Exit Speed Ratio; numerically, BESR = q + 1/2. Starting in 2011, the NCAA will instead regulate the BBCOR, taking advantage of the fact that for bats of a given BBCOR, the BBS does not depend strongly on MOI. Moreover, the NCAA has set the maximum BBCOR to be right at the wood level, so it is expected that nonwood bats used in NCAA will perform nearly identically to wood starting next year.

Alan Nathan has been a Professor of Physics at the University of Illinois since 1977. His research specialty is experimental nuclear/particle physics, with over 80 publications in scientific journals to his credit. He is a Fellow of the American Physical Society. For the last decade he has added the physics of baseball to his research portfolio and has written numerous papers on the subject for scientific journals, primarily on the physics of the ball-bat collision and the aerodynamics of baseball in flight. In addition, he has given many talks on the subject to both scientific and popular audiences and maintains a "physics of baseball" web site that is visited frequently. He is Chair of SABR's Baseball & Science Committee and a member of the scientific panel that advises the NCAA on issues related to bat performance.

Permalink | Comments (8)

Edgar Martinez is listed for the first time on this year’s Hall of Fame ballot. While Martinez is a very long shot for actually earning 75% of the writers’ votes in his first year of eligibility, I believe that Martinez meets the historical standards for Hall of Fame entry and should earn one’s vote.

Evaluating Edgar Martinez’ career presents some fairly unique challenges.

• Martinez played the majority of his career at DH, eventually finishing third behind Harold Baines and Hal McRae in career games played at DH. How do we evaluate a player who made no defensive contributions for most of his career?

• If one votes for Edgar Martinez, does that open the door for too many other candidates, such as Fred McGriff who also makes his debut on this year’s Hall of Fame ballot?

• Martinez had a somewhat short overall career compared to other Hall of Fame caliber players. How does he compare to position players with roughly comparable career length?

• Even measuring Martinez’ offensive contributions can be a bit tricky because he excelled at getting on-base and hitting doubles during an era better known for home run hitting.

Let’s start with that last challenge, and then we’ll work our way backwards through the remaining challenges.

First a Detour: wOPS+

I love using the OPS+ statistic (called adjusted on-base + slugging percentages) compiled at www.baseball-reference.com. It does most of the heavy lifting for us since it is adjusted for ballpark effects and the offensive context of the league and year. It’s readily accessible, because one can easily sort and filter based on it. The scale is also easy to grasp: 100 is average, and OPS+ scores above 100 are better than average.

The problem with OPS+ is that using on-base percentage plus slugging percentage just isn’t very accurate to start with. On-base percentage is considerably more important for creating runs. How much more important? Well, there’s no need to reinvent the wheel here. Tom Tango wrote recently that one can greatly improve OPS+ by weighting the on-base percentage by 1.2 and the slugging percentage by 0.8. We’ll call it weighted OPS+ or wOPS+. To be precise, we’ll define it as:

This will give us a statistic adjusted for offensive levels and home ballpark, is an accurate reflection of offensive contributions toward creating runs, and is still fairly easy to compute. We use just four pieces of input data, all of which are readily available in the Special Batting section of player batting data on baseball-reference.com.

We’ve got our shiny new hammer. Now let’s go find some nails.

Edgar’s Moderately Short Career

One objection to Edgar Martinez’ possible Hall of Fame credentials is that his career was a bit short by Hall of Fame standards. Martinez totaled 8,672 plate appearances, which isn’t too short. Let’s look at those with 7,500 – 9,500 plate appearances who played since 1901 and see where Martinez’ career batting quality ranks among those with similar career lengths.

These are the best batters in baseball history with career lengths roughly similar to Edgar Martinez’ career length. Obviously, it includes active players, with statistics through 2009, many of whom will retire with longer careers but with somewhat lower wOPS+ as they complete their decline phases.

Where’s the cutoff between the Hall of Famers and the non-Hall of Famers? If we ignore steroid problems, everyone above Brian Giles appears to be a Hall of Famer, although others may read the data differently. Jason Giambi’s Hall of Fame credentials are questionable, but he had a very high peak, with three consecutive top 5 MVP ballot finishes.

Below Brian Giles on that last table, one can still be a clear Hall of Famer by batting well and playing a premium defensive position, such as Piazza and Vaughn did, but we start to enter a gray area. There are many, many Hall of Famers below the top twenty that I listed, but it’s a dicey proposition the further down one goes. Incidentally, new Hall of Famer Jim Rice has a career wOPS+ of 124 on this list, not that he represents the dividing line between whether a guy comfortably fits into the Hall of Fame.

Edgar ranks sixth, surrounded by Hall of Fame caliber players. Here’s our starting point, that Edgar Martinez had a Hall of Fame caliber career based on the quality of his batting.

Edgar versus Crime Dog

Another worthy objection to letting Edgar Martinez into the Hall of Fame is that we end up with far too many modern batters in the Hall. Edgar wasn’t really that special, right? For example, looking just at the newcomers for next year’s 2010 ballot, if one votes for Edgar, doesn’t one first have to vote for Fred McGriff?

Not necessarily.

Comparing career wOPS+ totals shows a clear advantage to Martinez. However, now that we are comparing McGriff, a guy with a much longer career, that may not be a fair comparison. Edgar had an unusual career progression, with his early years spent clobbering minor league pitching and a short decline phase at the end of his career. Let’s instead look at individual years to see, in their best seasons, which player was a better batter. Here are all of their seasons where they had enough plate appearances to qualify for the batting title (502 in most years, but less for 1994-95 due to shortened seasons):

I don’t know whether Fred McGriff will eventually be in the Hall of Fame or not, but this table rather clearly shows that Edgar was the better hitter, with 8 of the 10 best seasons between the two of them. Martinez shouldn’t have to wait in line behind McGriff on anyone’s Hall of Fame ballot.

Stop Ignoring the 600-Pound Gorilla in the Room!

Probably the biggest objection to voting Edgar Martinez into the Hall of Fame is one that I’ve ignored so far: he spent the bulk of his career as a designated hitter.

How much is a player with no defensive value worth? According to Tom Tango’s positional adjustments, which are used for the Win Value metrics on Fangraphs.com, a DH is 22.5 runs per season worse than the average non-DH position player. However, Tango added back in another 5 runs for the difficulty of batting as a DH, resulting in a -17.5 runs per season positional adjustment.

What is so difficult about being a DH? It’s a little bit like having to be a permanent pinch hitter, and we all recognize that it is more difficult to perform well as a pinch hitter coming in cold off the bench. As summarized on p. 113 of The Book by Tango, Lichtman and Dolphin:

Players also lose effectiveness when being used as a designated hitter; the DH penalty is about half that of the PH penalty. This does vary significantly from player to player – some players hit as well as a DH as they do otherwise, while others perform as badly as pinch hitters.

So there can be a unique skill at batting well as a DH.

The result is that an average DH is worth about five runs per season less than an average fielding first baseman. Yes, that’s a disadvantage, but it isn’t huge. A DH can be more valuable than a below average first baseman with comparable batting statistics because the difficulty of batting as a DH partially offsets the defensive value of a below average fielding first baseman.

Being a DH is a negative marker for a Hall of Fame candidate, but, viewed rationally, it shouldn’t be an impossible hurdle.

Comparing Edgar to Other DHs

Perhaps the easiest way to evaluate Edgar is to just compare him to other DHs. We have to have some designated hitters in the Hall of Fame, right? Paul Molitor is already there and a plurality of his games played, including most of his best seasons, were when Molitor played primarily as a DH. Frank Thomas played over half of his career as a DH and he’ll be in the Hall eventually. It’s not unreasonable to think that we ought to have a couple of Hall of Fame DHs considering that the American League has had designated hitters since 1973, a span of over 35 years.

So here’s a list of the top 20 seasons for designated hitters, again using our wOPS+ rate statistic:

These are very fine seasons. You may remember that Milton Bradley led the American League in raw OPS in 2008, yet his season ranks only seventh on this list.

I don’t have any trouble eyeballing this list and concluding that Edgar Martinez has had the best career as a DH of any player in history so far. The best DH in history is not Hall of Famer Paul Molitor, nor future Hall of Famer Frank Thomas. It’s not Harold Baines, the longevity leader, or David Ortiz, the popular current star at DH. It’s Edgar Martinez.

That’s a Hall of Famer.

Other Considerations

According to the Hall of Fame:

Voting shall be based upon the player's record, playing ability, integrity, sportsmanship, character, and contributions to the team(s) on which the player played.

As far as integrity, sportsmanship and character go, let’s point out that Edgar Martinez was once honored with the Roberto Clemente Award for charitable contributions to his community. I also am unaware of any claims that Martinez used performance-enhancing drugs, for those inclined to go there. I don’t see much room for debate: character issues will not hurt Martinez’ candidacy.

While I would be surprised if the BBWAA membership agrees with me, in my opinion, Edgar Martinez is a Hall of Fame caliber player and should be voted in.

Michael Weddell is one of the Research & Analysis columnists for the fantasy baseball website www.BaseballHQ.com and a contributor to Ron Shandler’s Baseball Forecaster: 2010 Edition. Michael roots for the Tigers with his wife and adult children in metropolitan Detroit.

Permalink | Comments (7)

[Editor's note: In conjunction with Stan Opdyke's guest column on Connie Mack and Vin Scully, author Jon Weisman has granted us permission to publish "Vin," the number two item in 100 Things Dodgers Fans Should Know & Do Before They Die. As a lifelong Dodgers fan, Jon has listened to Scully broadcast games for four decades. In his wonderful book, he covers (among other topics) Vin, Jackie, 32, Fernandomania, Ebbets Field, The Move, Coliseum Carnival, Chavez Ravine, 'The Worst Club Ever to Win a World Series,' Walter Alston, Campy, Piazza, Dodger Dogs, Roseboro & Marichal, Arrive Late/Leave Early, Branch Rickey, Dodgertown, Nightline, The First High Five, and a section on Maury Wills that Weisman aptly named 'Go. Go. Go. Go. Go' after the chant that I can remember echoing throughout Dodger Stadium in 1962 when I was seven years old. This book is not only a must own for Dodgers fans but an entertaining and enjoyable read for baseball fans in general.]

He’s an artist. Of course he’s an artist. You don’t need a book to tell you that, to tell you that the man could broadcast paint drying and turn it into something worthy of Michelangelo, to tell you that his voice is a cozy quilt on a cold morning, a cool breeze on a blistering day; that he’s more than someone you listen to, that he’s someone you feel.

But saying he’s an artist is not meant as a cliché or as a convenient way to sum him up. It’s meant to stress that spoken words at a baseball game are themselves an art form, and, sure, sometimes they’re the equivalent of dogs playing poker, but when Vin Scully strings words together (and he’s done so at Dodger games — extemporaneously, mind you — for 25,000 hours or more), they’ll carry you away on wings.

If it weren’t so satisfying, it could make you weep.

But it’s not as if Scully – and at this point, it’s hard to resist referring to him by his first name, so vital and personal is the Dodger fan’s relationship with him – sets out to construct pieces for the Smithsonian. His principal goal has always only to simply tell you what’s going on. He’ll never miss a pitch. He will make a mistake here and there, and in that respect he’s like everyone else on the planet. But he never, ever loses sight of his task.

He is prepared with background on the players and the teams he covers. He has a knack for sifting out what’s interesting about the men on the field, and an infectious childlike enthusiasm for what he discovers. Reflecting his desire not to leave any listeners or viewers in the dark, he’ll repeat stories on different nights of the same series, but as long as you know that’s part of the deal, there’s no issue.

“One of the biggest reasons that I prepare is because I don’t want to seem like a horse’s fanny, as if I’m talking about something I don’t know,” Scully said in an interview. “So in a sense you could say I prepare out of fear. That’s really what you do. I think I’ve always done that since grammar school.”

That may be equal parts humility and truth. Scully’s utter genius, however, is the way he reacts when the moment takes him beyond preparation, the way he offers the lyrical when other broadcasters remain stuck in the trite. He offers bon mots covering pedestrian occurrences: Who else could deliver baseball play-by-play’s timeless philosophical comment: “Andre Dawson has a bruised knee and is listed as day-to-day. … Aren’t we all?” His work during Sandy Koufax’s perfect game, Hank Aaron’s 715th home run, Bill Buckner’s error and everything in between are all unforced majesty.

As far as rising to the occasion, Scully’s landmark call of Kirk Gibson’s showstopping, history-making homer in Game 1 of the 1988 World Series was practically its equivalent from a broadcasting perspective, minus the gimpiness. “In a year that has been so improbable, the impossible has happened” ranks with Al Michaels’ “Do you believe in miracles? Yes!” among the most memorable lines in sportscasting history for spontaneously summing up a moment. And yet, could anyone have been less surprised that Scully came up with such a wonderful remark? His broadcasts have been dotted with them ever since he joined the Brooklyn Dodger broadcast team in 1950 as a recent Fordham college graduate who had been singularly dreaming of such a job since boyhood.

“When I was 8 years old, I wrote a composition for the nuns saying I wanted to be a sports announcer,” Scully said. “That would mean nothing today – everybody watches TV and radio – but in those days, back in New York the only thing we really had was college football on Saturday afternoons on the radio. Where the boys in grammar school wanted to be policemen and firemen and the girls wanted to be ballet dancers and nurses, here’s this kid saying, ‘I want to be a sports announcer.’ I mean it was really out of the blue.

“The big reason was that I was intoxicated by the roar of the crowd coming out of the radio. And after that one thing led to another, and I eventually got the job as third announcer in Brooklyn. And I never thought about anything except the first year or two not making some terrible mistake is all. I worked alongside two wonderful men in Red Barber and Connie Desmond, but I never thought about becoming great. … All I wanted to do was do the game as best I could. And to this day that’s all I think about.”

Lots of people try to do their best, and for that they all deserve praise. But the best of some is better than the best of others, and even though he can’t bring himself to say it, we know into which of those categories Scully fits. Regardless of how intense or carefree one’s love for the game might be, Scully measures up to it and redoubles it. The Dodgers’ play-by-play man is an American Master.

Jon Weisman is the founder and writer of the Los Angeles Times blog Dodger Thoughts, the leading website providing commentary on the Los Angeles Dodgers. For more than 20 years, he has written for the Los Angeles Times, Los Angeles Daily News, SportsIllustrated.com, The Hardball Times, and other publications about baseball and virtually every other high school, college and professional sport. He has also written live-action and animation television scripts for shows including So Weird, W.I.T.C.H., Starship Troopers, Men in Black, and Disney's Hercules, and is currently Associate Editor, Features for Variety. A holder of degrees from Stanford and Georgetown, Weisman lives in Los Angeles with his wife and three children.

Permalink | Comments (1)

At an inconsequential Spring Training game in Florida in 1950 the torch was passed. In the broadcast booth for the Brooklyn Dodgers was a nervous youngster who at the ripe old age of 22 was about to begin his big league broadcasting career. On the field below him was a very old man who was about to begin his final year in major league baseball. The old man stepped down as manager of the Philadelphia A's after that season. Sixty years later, the young man in the broadcast booth is still the broadcaster for the Dodgers.

The major league careers of Connie Mack and Vin Scully intersected at the midpoint of the 20th century. Connie Mack was born Cornelius Alexander McGillicuddy in 1862, before the Emancipation Proclamation was issued, at a time when Abraham Lincoln was President and America was engaged in the Civil War. Today, Vin Scully is broadcasting for the Los Angeles Dodgers at a time when a black man is President.

Connie Mack began his major league career in 1886 as a catcher for the Washington Senators of the National League. He played with the Senators for four seasons. In 1890, Connie, along with many of his fellow players, bolted the National League to form the Players League. Unfortunately for Connie and his fellow players, the Players League folded after just one season.

In 1891, after the demise of the Players League, National League owners assigned Connie's contract to Pittsburgh. During the 1894 season Connie took over as playing manager for the Pirates. After a poor finish in 1896, Connie was fired by the Pittsburgh owner.

Connie's dismissal proved to be a blessing. In 1897, Connie left the National League to join Ban Johnson's Western League as a manager, part-time player, and part owner of the Milwaukee franchise. When Johnson transformed his Western League into the American League at the turn of the century, Connie Mack was poised to resume his major league career, this time as a manager and an owner.

In 1901, Ban Johnson sent Connie to Philadelphia to establish an American League franchise in that city. Connie built a strong team and in 1905 his Philadelphia Athletics played and lost in the World Series to John McGraw's New York Giants. Connie's teams remained powerful through the 1914 season. When the A's lost the 1914 World Series to Boston's "Miracle Braves," Connie jettisoned the team he had developed, much like the Florida Marlins would do after the 1997 World Series. Like the Marlins, the Philadelphia A's sank to the bottom of the standings.

In the mid-1920s, Connie began building a team to rival the accomplishments of his earlier championship A's teams. In the latter part of the roaring 20s and the early years of the Great Depression, Connie's A's defeated powerful New York Yankee teams that featured Babe Ruth and Lou Gehrig. The Great Depression led Connie to dismantle his team. Once more, the Philadelphia A's went to the bottom of the American League standings.

Connie was unable to build another championship team; the A's did not win another World Series title until the franchise shifted to Oakland. Connie Mack remained as manager of the Philadelphia A's throughout all the last place finishes the franchise endured. No doubt Connie's ownership of the team saved him from the fate that inevitably befalls managers of losing franchises.

Age and infirmity caused Connie to step down as manager after the 1950 season. Shortly thereafter, amid rising debt, the Mack family lost control of the franchise. The team relocated to Kansas City after the 1954 season.

As Connie Mack's career was coming to a close, Vin Scully began an amazing broadcasting career that is still in progress today. Vin attended college at Fordham and worked on the campus FM radio station. After graduation, in search of a broadcasting job, Vin sent his resume to radio stations both near and far from his New York home. Vin's letter writing bore fruit; he was hired as a temporary summer replacement announcer at WTOP in Washington, DC, the same city where Connie Mack made his big league debut in 1886.

Vin has said that going from a college FM station to an on-air job with the CBS affiliate in the Nation's Capitol was like going from the campus to the big leagues. Vin's stay in the big league atmosphere of WTOP was short lived; the management at WTOP told him that though they liked his work, they had no permanent job for him. Vin left Washington with vague promises of possible future employment at WTOP, but when he returned to his New York home he had no broadcasting job.

Vin's career took off after a meeting with Red Barber, who would become his mentor. Red hired Vin for a radio broadcast of a college football game in Boston for the CBS football roundup show. In a 1982 radio interview, Barber told Larry King about the circumstances that led to Vin being hired by the Dodgers (thanks to Jon Weisman for permission to quote from his transcription):

I was out at the end of the football season, doing a California-Stanford football game. And at halftime, the engineer handed me a note and said, "Ernie Harwell has joined Russ Hodges at the Polo Grounds. So flying back to New York, I kept thinking, "Who are we gonna get? Who are we gonna get for the third man?" Then I said, "That red-headed fellow that went up to Boston did a good job." So I sent for him, and talked to him for a bit. And then I said, "Would you be interested?"

Well, his eyes got as big as teacups. So I said, "You'll have to talk to Mr. Rickey." Well, in about an hour Mr. Rickey called back, and he said, "Walter"—he always called me Walter—"Walter, you've found the right man."

I cannot imagine any baseball fan who would dispute Mr. Rickey's assessment. Red Barber and Branch Rickey provided Vin with his initial opportunity, but the youngster had to make the most of it. Vin reported to Spring Training in 1950 with as much pressure to make good as any big league player looking to earn a job.

A few years ago in a 2006 interview on a Seattle Mariners pregame radio show, Vin was asked by Mariner broadcaster Rick Rizzs to recall his first broadcast for the Brooklyn Dodgers. Vin responded:

Well, I think the very first one was an exhibition game and we were playing the Philadelphia Athletics and the manager that year was Connie Mack. Now the next year Jimmy Dykes became the official manager but my first broadcast was with the A's in Vero Beach with Mr. Mack right there in the black suit, and the celluloid collar, and the straw hat. So, I remember in that game I think Ferris Fain was the first baseman and it seems to me there was a triple play which Red Barber called and I remember sitting there thinking, "He made it sound so easy," and I was scared to death.

Vin's career after that Spring Training game has made him an eye witness to some of the most memorable moments in baseball history. Vin was in the same radio booth as Red Barber when Red had the unfortunate duty to describe Bobby Thompson's home run in the third game of the 1951 National League playoffs. Vin was on the air for a much more joyous occasion, the final out of the 1955 World Series that brought Brooklyn its only world championship. A year later, Vin, along with Mel Allen, broadcast Don Larsen's World Series perfect game. On September 29, 1957, Vin was at Philadelphia's Connie Mack Stadium to broadcast the last game in the franchise history of the Brooklyn Dodgers. In 1958, he broadcast the first game played by the Los Angeles Dodgers. Vin also brilliantly called the last inning of Sandy Koufax' perfect game in 1965, a call that can be heard here thanks to Rob McMillin. He was in Atlanta in 1974 for the radio call of Hank Aaron's historic 715th career home run. In 1986, he was on national television at the World Series to call a little ground ball that went through Bill Buckner's legs. In 1988, he was at Dodger Stadium to make a memorable call ("In a year that has been so improbable, the impossible has happened") of Kirk Gibson's dramatic pinch hit World Series home run.

On the radio show where he reminisced about his first big league broadcast, Vin was asked, "Vinnie, how long do you want to do this?" Vin's answer was, "I don't know, but I can tell you a favorite expression of mine: If you want to see God smile, tell Him your plans."

After 60 years in the broadcast booth, Vin is nearing the end of his extraordinary broadcasting career. When Vin is in his final year, whenever that may be, I hope that some youngster will be in the first year of a six-decade long baseball career. If that happens, and if that person is a worthy successor to Connie Mack and Vin Scully, more than 60 years from now a postscript to this story can be written.

Stan Opdyke was a Dodgers fan as a kid during the Sandy Koufax, Don Drysdale, and Maury Wills era. His biggest baseball thrill was watching Koufax pitch the Dodgers to the National League pennant on the last day of the season at Connie Mack Stadium in 1966. He also got Vin Scully's autograph at Connie Mack Stadium in the mid-1960s. Vin was standing in the dugout before the game, and he called out his name and asked him to sign his autograph book. Scully graciously did. Meanwhile, the other kids looked at him like he was nuts. Why would he want an autograph of someone who looked and dressed like their father?

Permalink | Comments (7)

A Review of Basics

There are two sets of equations that together constitute the backbone of the art of modern statistical analysis: those that project team games won from runs scored and runs yielded, and those that project team runs scored (or yielded) from some combination of reasonably available team statistics. Since that second type is so important, it is worth taking a look at the many specimens out there—their logical bases and their actual performance.

Here we will look at what the more common formulations are and how they stack up against one another. The survey will cover the period of 1955 through 2009. The reason it starts in 1955 and no earlier is simply that several of these methods use stats that simply weren't available before 1955 (such as IBB or SF).

As an aside, let me say that in the course of preparing this overview I was struck by two things: how few people seem to understand how to write out equations, in particular how to use nested parentheses, and how many seem willing to specify some non-standard statistic without then defining it exactly. As to writing out equations, first consider this piece of simple arithmetic:

X = 3 x 5 + 7

Is the wanted answer 22 or 36? That depends on whether the writer intended--

X = (3 x 5) + 7

or

X = 3 x (5 + 7)

That is not an artificial example: one of the formulae evaluated below is given (in several places around the web) in exactly this form:

R = A*B/(B+C) + D

Jolly good luck deciphering that without extrinsic information. On further examination of the associated text, it turned out that what was meant was—

R = (A x [B / { B + C } ]) + D

— which brings up the other point about writing out equations: there are other enclosure marks than the parenthesis, to wit the bracket and the brace, both of which are illustrated in the preceding example. Using them makes untangling nested expressions very much easier.

(In principle, there is an implied order of precedence for arithmetic operations such that parentheses are often not needed, but not only do few people know it—I'd have to look it up—but there is never any guarantee that the writer of a given equation knows it either, or even knows that it exists.)

My other peeve is illustrated by these sorts of formulae:

R = ( [1B x 3] + [2B x 5] + [3B x 7] + [HR x 9] + [BB x 2] + [SB x 1] - [Outs x 0.61] ) x 0.16

R = (0.47 x 1B) + (0.78 x 2B) + (1.09 x 3B) + (1.40 x HR) + (0.33 x (BB+HB) + (0.30 x SB) - (0.60 x CS) - (?? x [AB-H]) - (0.50 x OOB)   —  (ignore the ?? as it is not germane to the point here)

In the first, whatever is "Outs"? In the second, whatever is "OOB" (even when expanded to "Outs on Base")? Is "Outs" all outs made by the team? Outs made only by batters? A particular estimate of all outs (such as [AB - H] + SH + SF + CS + GDP)? And what about OOB? Is it all team outs minus batters' outs? Some particular combination of standard stats (such as GDP + CS)? Or what? Which bodily part experiences the pain if the actual, exact meaning is explicitly stated? (Mind, not every formula presenter is guilty of all, or even any, of those sins; but altogether too many are.)

An interesting side question is just what stats is it "fair" to use? For example, one writer states that he means a particular term in a particular formula to signify an out made by a player trying to stretch a single into a double or a double into a triple (or the rare case of a triple into an inside-the-park home run). That's clear, and no doubt meaningful in the context, but whence such data? OK, yes, Retrosheet.org has it all there for those with the diligence and patience to mine it, and Baseball-Reference.com has done an awful lot of that mining. But whether a particular stat is "readily" available can be a tough call.

I suppose at bottom much depends on ultimate purposes: if the idea is to write up a technical paper examining the mechanisms of run-scoring, then anything that can be extracted from the record is fair dinkum; but if the idea is to make a tool suited for frequent and straightforward work, then using stats not readily available would seem to render the equation containing them unsuited for its purpose.

There are, though, a couple of stats that are sort of on the margin. Those are CI, catcher's interference, a typically very small but nonetheless official and significant stat, significant in that it is a component of PA, plate appearances—but is almost universally left out of published PA tallies and almost never published in itself (and suppose there's a Dale Berra or Roberto Kelly on the subject team?). And there's Eb (opponents' errors allowing an otherwise-out batter to reach base, which Baseball-Reference lists as ROE for "Reached On Error"). Omitting CI will—for most teams in most years—have very little, if any, effect, but I am surprised that Eb is so generally unused. (In the one case it is used, estimating it instead of using the exact number decreases average accuracy by about 0.08 of a run, which is about 0.1%; that may not seem like a lot, but wait and you'll see.)

Before we get to specifics, we ought also to consider what we are looking for and how to determine if we are getting it. What we want, of course, is accuracy: we want to feed in the stats for a team and, ideally, always get back the exact number of runs actually scored by the team that posted those stats. Obviously, we will not in general be able to get perfect results, so the way we evaluate various equations is by how closely they approximate perfection.

Formula makers have devised various ingenious ways to measure how well such things do; here, I will use some simple metrics that seem to my possibly naive mind to well express what we are seeking. The first, and foremost, is simply average percentage error. If formula X estimates R_est runs for a given team in a given year, and that team actually scored R_act runs—so that the absolute error is R_est - R_act runs—the percentage error will be:

E_pct = 100 x ( [R_est - R_act] / R_act)

Expressing error as a percentage is important, because absolute error sizes—actual numbers of runs off— are misleading: an absolute error of 10 runs signifies one level of accuracy for a team that scored 400 runs and quite another for one that scored 800 runs.

If we then take the unsigned value of the percentage error (that is, ignore whether it is positive or negative), we have a measure of the relative size of the error. We can then just average all the percentage error sizes over whatever time span we are examining to get an overall average percentage error size. That tells us how closely, on average, the subject formula's estimate of runs came out relative to the actual value.

But average size of error is not the only metric of importance. If a runs predictor is truly modelling run scoring fairly well, then its errors ought to be symmetrical: that is, they should scatter evenly around perfect accuracy. A formula that comes in with a given average size of error but has, say, twice as many over-estimates as under-estimates is clearly not working as well as one of roughly equal size accuracy that comes in with its errors about evenly divided between over and under.

Finally, we would expect that the better a runs-predictor is working, the more nearly its cumulative total error with + and - considered will trend to zero. That is, the cumulative sum of all its errors over the subject time span (with over- and under-estimates cancelling) should be nearly zero. This is related to but slightly different from the criterion above.

And for completeness, we should still also tabulate the absolute sizes of errors, both as an average error in runs and as—to keep the control freaks happy—as a standard deviation in runs.

With all that understood, we can turn to particular run-scoring formulae. All such run-scoring equations fall into two broad classes, which we can call "linear" and "multiplicative"; each has its devotees, and we will take an overview of each class separately.

The Formulae

The Multiplicative Approach

The Theory

The basic idea behind multiplicative approaches is quite simple: run-scoring consists in getting runners on, then driving them in. Equations based on that principle are "multiplicative" because they are probabilistic--that is, they seek to estimate the probability of runs scoring based on the occurence of certain game events. It is a base fact of probability analysis that the probability of two independent events both occuring is the multiplicative product of the independent probabilities of each one occurring: if the chance of a randomly selected person being male is 50%, and the chance of a randomly selected person being blue eyed is 16%, then the probability that a randomly selected person is a blue-eyed male is 8% (0.5 x 0.16). In multiplicative run-scoring equations, the factors being multiplied represent the probability of a batter getting on base and the probability of another batter advancing any runners already on base.

For the first term, the chances of a batter getting on base, it might seem that all that is needed is the now-familiar on-base percentage; but the OBP does not take into account the reality that a man who has successfully reached base may then be thrown out on the bases. A man thrown out on the bases may as well have never reached base (as far as the chances of his becoming a run scored), so multiplicative formulae need to in some way estimate net runners on base. That is not as easy as it might sound, because some data are not so easy to obtain. For example, by definition, total plate appearances equals runs plus left on base plus total outs:

PA = R + LOB + Outs

so that

R + LOB = PA - Outs

(And, of course, R + LOB is the number of men who reached base and were not later thrown out.) But total team Outs made is not so easy a datum to come by, unless one can find lines of "opponents' pitching"; otherwise, one has to assemble it from numerous pitching splits. If one has that capability, then one can use the exact datum; if not, one has to estimate it.

(Sidebar: for reasons best known to themselves, few if any stat services any longer tabulate LOB, once one of the fundamental stats ("No runs, two hits, one man left on base, and at the end of five . . . ." It can be adduced, using the simple equation above, if one can first assemble a total team Outs datum.)

If one has to estimate, some stats for runners thrown out on base are commonly available: caught stealing (CS) and grounded into a double play (GDP, or GIDP). But there are far more ways than those to be put out on the bases: pickoffs, throwouts trying to extend a hit, and so on. The general approach of multiplicative formulations is to either take the gross OB and multiply by an empirical estimation constant, or to take the gross OB, subtract what is known about outs on base, then apply an empirical estimation constant.

The base-advance component is the trickier of the two, and it is in constructing that component that multiplicative equations most differ from one another. The simplest and most obvious runner-advance stat is hits; moreoever, since the more extra bases a hit goes for the more it will advance any runners on, hits in any run-advance component are invariably weighted. The simplest weighting, one commonly used, is the Total Base (TB) value, which assigns each hit a weight equal to the number of bases (that is, for example, 3 for a triple). More advanced approaches use different weightings that presumably better represent the effective runner-advance value of a given hit. (To clarify: if one examines the eight possible base-occupancy situations, it is clear that overall a triple will not have 1.5 times the advance value of a double—what the exact relative values may be is something each formulator works out on his own, by such means as seem good to him.)

But, while hits must clearly dominate base-advancing, there are many other stats that reflect actions that can advance runners on base. Those include walks, hit batsmen, and catcher's interference, which will move along any runners on first or in sequence thereafter; stolen bases, which are pure (no batter action) base advances; sac bunts and sac flies; wild pitches and balks; and certain errors. Determining values for these lesser but not negligible actions is another thing each analyst working on the question has to do for himself.

(Note, though—and this applies to the linear methods, too—that while certain of the "lesser" stats may triflingly increase accuracy for a formula that works with actual, historical data, they will be deceptive if used when such formulae are to tried prospectively (that is, for predicting the future based on the past), because those actions are not under the control or influence of the offense. Such things as balks, wild pitches, and opponents' errors are essentially random happenings, and so a general empirical constant is best used to stand in for those things as a whole.)

The Formulations

I will here just list each and show the equation as I gleaned it from one or more sources on the web. If any of those equations seem to anyone reading this as incorrect expressions of the maker's intent, please email me. The accuracy surveys will come after we have introduced all the equations of both classes.

At least as early as 1964, a run-scoring equation of passable accuracy existed: Earnshaw Cook's "DX", which has an average accuracy of around 3½ percent, and which had a "simplified" form essentially identical to the original famous "Runs Created" formulation Bill James put forth 15 or 20 years later. For this evaluation, I tried to use all the current methods I could find documented around the web. I probably missed some, and would be pleased to hear from anyone who has one or more others to suggest (just email me with the formula—written out nicely, please, as spoken of earlier—and some info on who made it when), and if enough roll in I will try to assemble a follow-up survey. But for now, these are they:

Basic Runs Created:

        (H + BB) x TB

  RC =  -------------

           AB + BB

This (hereafter RCbasic) was Bill James' first opus. Its chief virtue is its extreme simplicity of both form and calculation: one can easily understand it, and one can easily reckon it.

Stolen-Bases Runs Created:

        (H + BB - CS) x (TB + [0.55 x SB])

  RC =  ----------------------------------

                    AB + BB

This (hereafter RCsb) is a modification of the "Basic" version to account for the value of, yes, stolen bases (and the corresponding caught-stealings).

"Technical" Runs Created:

  RC = (H + BB + HB - GDP - CS) x (TB + [0.26 x {BB - IBB + HB}] + [0.52 x {SH + SF + SB}]) / PA

  

     PA = AB + BB + HB + SH + SF

This (hereafter RCtech) is a substantially greater modification of the "Basic" version, to account for all sorts of other lesser data.

"Technical" Runs Created, 2nd Version:

  RC = (H + BB + HB - GDP - CS) x 

     (TB + (0.26 x (BB - IBB + HB)) + (0.62 x SB) + (0.5 x (SH + SF) - (0.03 x SO) / PA

     

    PA = AB + BB + HB + SH + SF

This (hereafter RCtech2) is a minor variation of the form above.

"Technical" Runs Created, 2nd Version, alternate:

  RC = (H + BB + HB - GDP - CS) x 

     (TB + [0.24 x {BB - IBB + HB}] + [0.62 x SB] + [0.5 x {SH + SF}] - [0.03 x SO]) / PA

     

    PA = AB + BB + HB + SH + SF

This (hereafter RCtech2a) is another very small variation of the RCtech2 form (0.26 becomes 0.24).

"Technical" Runs Created, 3rd Version:

  RC = (H + BB + HB - GDP - CS) x 

     (BaseWeights + [0.29 * {BB - IBB + HB}] + [0.492 * {SB + SH + SF}] - [0.04 * SO]) / PA

     

    BaseWeights = [1.125 * 1B] + [1.69 * 2B] + [3.02 * 3B] + [3.73 * HR]

    PA = AB + BB + HB + SH + SF

This (hereafter RCtech3) is the most complex yet of the variations on the RC formula; it is the only one to assign non-TB weights to base hits.

Base Runs:

  BaseRuns = (A x [B / {B + C}]) + D 

    

   where:


    A - H + BB + HB - HR - (0.5 x IBB)

    B - (BaseWeights + [0.1 x {BB - IBB + HBP}] + [0.9 x {SB - CS - GDP}]) x 1.1

    C - (AB - H) + CS + GDP

    D - HR

    

    BaseWeights = [1.4 x TB] - [0.6 x H] - [3.0 x HR]

This (hereafter BR) is David Smyth's offering in this category. Wikipedia cites Tom Tango as stating that BaseRuns models the reality of the run-scoring process significantly better than any other run estimator. (We shall see.)

Total Offensive Productivity:

  AdvR = (BaseWeights + [0.301 x {BB + HB}] + [0.526 x SH] + [0.912 x SB]) / PA

  Adv = (AdvR x 0.867) + 0.0412

  OBnet = PA - Outs

 

  TOP = OBnet x Adv

  

     BaseWeights = 1B + [1.551 x 2B] + [3.455 x 3B] + [4.421 x HR]

     PA = AB + BB + HB + CI + SH + SF

     Outs = all team outs

This (hereafter TOP) is mine own. It is sufficiently complex that the making of it (above) is split into multiple pieces for comprehensibility, since it uses the y = mx + b method for best-fitting the relation between runners scored and base-advance events.

Total Offensive Productivity, Dumbed-Down:

This (hereafter TOPdd) is as above, but with all coefficients rounded to only two decimal places of accuracy. No recalculating was done (though the coefficients do interact). The point was to see if using three decimal places, which many but not all formulae do, made any material difference.

Total Offensive Productivity, No Error Data:

  PA = AB + BB + HB + CI + SH + SF

  AdvR = (1B + [1.551 x 2B] + [3.455 x 3B] + [4.421 x HR] + [0.301 x {BB + HB}] + [0.526 x SH] + [0.912 x SB]) / PA

  Adv = (AdvR x 0.867) + 0.0412

  OBnet = (0.907527925021 x [H + BB + HB + CI + Eb - HR - CS]) + HR

    Eb = 0.017734746015 x ([AB - H)] + SH + SF)

 

  TOP = OBnet x Adv

This (hereafter TOPnoEs) is the full formulation except with opponents' errors (Eb)—and thus net runners on base—estimated by a couple of empirical coefficients. I inserted it here to show how much estimating net on-base does or does not cost accuracy as compared to using exact values (because they are not always simple to obtain). Because this is estimating a datum that should be known exactly, it uses full-accuracy constants (no point in double-crippling it)

The Linear Approach

The Theory

In a sense, there is no theory to linear methods (usually referred to as "linear weights", though that really signifies only one such method). Linear methods are based on what we might call the "ant on a globe" principle: place an ant on the surface of a sufficiently large globe and the surface, though actually curved, will seem flat. Indeed, we humans experience that every day on planet Earth, which is why so many people believed it flat for so long. Linear methods are not concerned with the full shape (and hence describing equation) of the relations between common baseball stats and runs scored: they assume that over the relatively short stretches of such curves that we are in practice concerned with, the relations can be considered to be straight lines (hence "linear"). From that assumption, it follows that one can construct runs by simply adding up the effects of each stat that might have some influence on run scoring, with that stat appropriately "weighted" by an empirical constant derived from experience.

The chiefest objection to linear methods is that they do not actually model run-scoring, which is a non-linear process. Countering that indubitable assertion is the sheer fact that they can and do produce good results. Further, they have this virtue: you can construct team values from individual-player values by simple addition.

(You cannot do that for multiplicative methods because in general the product of the averages is not equal to the average of the products. What that mouthful means can be shown quite easily:
X x Y = Z
2 x 4 = 8
4 x 8 = 32
-------------
3 x 6 = 18 but ([8+32]/2) = 20

That is, averaging the X's and the Y's and multiplying those averages gives a different result than averaging the individual Z's.)

The Formulations

Estimated Runs:

    ER = ( [1B x  3] + [2B x 5] + [3B x 7] + [HR x 9] + [BB x 2] + [SB x 1] - [Outs x 0.61] ) x 0.16

          Outs = (AB - H) + CS + GDP

This (hereafter ER) was created by Paul Johnson and got a nice write-up from Bill James; James seems to despise linear methods, and it is widely reported around the web that he apparently did not recognize Johnson's formulation as a linear method. There are other variants of this method, as described farther below; which version came first I cannot readily ascertain.

Estimated Runs a:

    ER = ( [1B x  3] + [2B x 5] + [3B x 7] + [HR x 9] + [{BB + HB + CI} x 2] + [SB x 1] - [Outs x 0.61] ) x 0.16

          Outs = (AB - H) + CS + GDP

This (hereafter ERa) is the above, but with HB and CI included; I just tried those on an off chance, and it much the results, so I include it.

Estimated Runs 2:

    ERP = ([2 x {TB + BB + HB}] + H + SB - [0.605 x {AB - H + CS + GDP}]) x 0.16 

This (hereafter ER2) is a variation on the method above; as I said, I don't know which came first.

Estimated Runs 3:

  ER3 = (TB * 0.318) + ([BB - IBB + HB - CS - GDP] * 0.333) + (H * 0.25) + (SB * 0.2) - (AB * 0.085)

This (hereafter ER3) is a yet another variation on the ER method. (The numbering, again, does not here imply a sequence.)

Extrapolated Runs:

  R = (0.50 x 1B) + 

      (0.72 x 2B) + 

      (1.04 x 3B) + 

      (1.44 x HR) + 

      (0.34 x [HB + BB - IBB]) + 

      (0.25 x IBB) + 

      (0.18 x SB) - 

      (0.32 x CS) - 

      (0.09 x [AB - H - SO]) - 

      (0.098 x SO) - 

      (0.37 x GDP) + (0.37 x SF) + 

      (0.04 x SH)

This (hereafter XR) is one of Jim Furtado's efforts at a linear formula; there is another one, listed below. I am unsure of their order of creation.

Extrapolated Runs 2:

  xRun = (1B x .51) + 

         (2B x .8) + 

         (3B x 1.14) + 

         (HR x 1.46) + 

         ([{BB - IBB} + HBP] x .33) + 

         ([IBB + SB] x .18) + 

         ([SH + SF] x .21) + 

         ([CS + GDP] x -.17) - 

         (0.10 x Outs)

     Outs = (AB - H + SF + SH + CS + GDP)

This (hereafter XR2) is a modified version of the above. I am unsure, actually, which version preceded which.

The Shoot-Out

The Results

Just for fun, I also included, as a sort of baseline, what one might call an "worst-possible-way" method. All it does is assign every team in every season the league-average runs for that league and season—that is, it doesn't "predict" at all, but assumes every team is "average". Any way of "projecting" runs that does worse than this is actually "anti-predicting".

The column headings are mostly self-explanatory, but here are notes on a couple. "Cumulative Error" is all actual errors added up, with sign (that is, plus and minus); the lower, the better. "Per Team-Year Error" is just the Cumulative Error divided by the number of team-seasons it was gathered over; it is not terribly important, but helps put the cumulative number in some sort of perspective.

As noted, the data are from the years 1955 through 2009, inclusive. The formulations are listed in order of average percentage accuracy, lowest to highest. The envelope, please . . . .

(The darker lines are multiplicative measures, while the lighter are linear.)

Some Reflections

First off, it is manifest that the best of the multiplicative and the best of the linear methods produce results that are quite close enough for folk music. Second, it is clear that the differences in performance of all these methods are far less consequential than the general accuracy of all. For perspective, let's keep in mind that a difference in accuracy of 0.14% is only about one run per team per season. Look at it: best to worst is only an average difference of less than 4 runs per team per season.

One thing, though, that is clear is that none of the linear methods is really close to a symmetrical distribution of its errors. That is scarcely a fatal flaw, but it does suggest that they are, as is known, not modelling process but empirically matching data. Now there are a lot of empirical constants in the multiplicative methods, too, but the thing is that the linear systems are their constants, and nothing else.

I thought it might be useful to take a look at graphical representations of a couple of these methods. For economy, I chose the best linear and the best multiplicative methods. Here they are:

There are differences, but you've got to look awfully hard to find them. And you will also notice—again, if you look carefully—what a tabled presentation would show better (but is too long for here), which is that these two rather different methods get mostly the same results for the same teams (look at the odd little dots that are fairly isolated), which demonstrates what we already knew: that variations from projection are essentially chance.

My own summing-up is that if you need convenient ease of use, as when doing calculations by hand, the XR method is easiest. If you want the sense that you're really modelling what happens, want best available accuracy, and have the use of a computer to do the heavy lifting of calculation, use the TOP formula. (The needed stats can be downloaded from various standard sources.)

The question of how these various methods can be used to analyze individual players is a fascinating one, but, owing to length, one for another time.

Eric Walker has been a professional baseball analyst for over a quarter-century. His paper "Winning Baseball", commissioned by the Oakland A's for the purpose, first instructed Billy Beane in the concepts later called "Moneyball"; Walker has also authored a book of essays, The Sinister First Baseman and Other Observations. Walker is now retired, but maintains the HBH Baseball-Analysis Web Site.

Permalink | Comments (6)

Baseball and statistics go together like peanut butter and jelly. The fact is, just about every position on the field can be successfully evaluated with numbers. But, in my opinion, the catching position is one spot that requires closer inspection. Rating receivers is hard to quantify because this position relies so heavily on intangibles.

Allow me to explain and show you how I see it from a catcher’s perspective. For every pitch, you’ve got about eight million variables coming at you. Who is the hitter and how have I attacked him in the past? What is the game situation? What are your pitcher’s strengths and weaknesses? What is the game plan/scouting report? Who is the umpire and what is his strike zone today? What does your manager want? The list goes on and on. And you need to process all this information and put down the correct number...right now.

Because for me, calling a game and having a good relationship with your pitchers and the umpire may have more of an effect on your team than anything else you might do. These intangibles aren’t flashy and won’t put butts in the seats like a home run hitting catcher can, but it might translate to more wins for your team.

I also believe good receivers must be good psychologists. You’ve got to know every individual on the staff and know whether they need to be kicked in the ass or patted on the back. The same applies for the umpire behind you. You’ve got to figure out what makes these guys tick and how to get results. Whether it’s playing the tough guy, the smart guy, or just offering words of encouragement, a good catcher knows how to get the most out the people he works with.

In this essay, I’d like to briefly cover some of these intangibles—communicating with pitchers, pitch selection and pitch counts, and controlling the pace of game. Before I get into that though, I hope you’ll indulge me as I go off on a little jag about coaches calling pitches. One last note, forgive me if I come off like I’m teaching. I’m a coach’s son and have a lot of that blood in me!

Coaches, Please Don’t Call the Game

Hear me out as I get something off of my chest. It concerns the epidemic I see of coaches calling pitches from the dugout. This bothers me on so many different levels I don’t even know where to start. Honestly, I think it should be outlawed and banished from the game. To begin with, how about the time it takes for the catcher to look over every single time to get a pitch selection? It drives me nuts to watch games that drag on forever as the coach satisfies his ego. I mean, what is the upside? Shouldn’t the kid be learning his craft? What good are you doing as a coach if you are turning out pitchers and catchers who cannot think and make quality decisions for themselves? It’s like graduating from school and not knowing how to read. Trust me—coaches don’t call pitches in pro ball. And the way things are going, amateur baseball is unleashing heaps of brain-dead players into the professional ranks. Yes, kids are going to make mistakes; yes, they are going to make stupid decisions. But that is how they learn. As pitching great Christy Mathewson wisely stated, “you can learn little from victory. you can learn everything from defeat.” Calling a game is a huge part of a catcher’s and pitcher’s development. Having a coach call the games stunts growth.

The bottom line, anyway, is: the best pitch a kid can throw is the one he can un-leash with conviction, even if it’s not the perfect choice. There is no way he can do that if the pitch is coming from the dugout. Talk about handcuffs. How about the little subtleties and changes only the catcher can notice in a hitter’s stance? The coach can’t possibly see that from his perch. How can a receiver anticipate and plan ahead when he is just robotically putting down signals? None of it makes any sense, and it drives me crazy. You may see pro catchers glancing into the dugout to get signs and think that if it’s good for them, it’s good for you. Let me tell you that except for rare instances, these glances have nothing to do with pitch selection. they almost always deal with controlling the running game—when to pitch out, throw over, slide step, and so forth. If you pay close attention, you will notice that pro catchers rarely look over when no one is on base. To be honest, if I were the manager, I would let the battery control the running game, too. But that is a whole different subject. Don’t get me started!

I was very fortunate to play for coaches and managers who never put the hand-cuffs on me. They would make corrections when I was wrong and suggestions when appropriate; however, they never stunted my growth by taking away the reins. As a result, the ability to call a good game and the subsequent trust that developed with my staff turned out to be my strong points. They kept me in baseball a long time and made the house payments. I am very grateful to my coaches for trusting me and seeing me through the learning curve.

I’ll finish this little rant with a plea to amateur coaches everywhere. Please take your hands off the steering wheel and let go of some of the control. Teach your players well, and then unleash them on the game to do what they will. A smarter, better developed athlete will emerge, the pace of the game will improve, and, trust me, the decisions won’t be half bad—maybe even better than yours.

Communicating with Pitchers

Now let’s switch gears and focus on the importance of the pitcher and catcher being on the same page. A good receiver takes the time to know his pitcher’s likes and dislikes and finds out where he (the pitcher) feels his limits are. He’s a good communicator and asks questions. Questions like: Do you like to throw the fastball up when ahead in the count? Do you like to bounce your breaking ball in the dirt? If we are in a strikeout situation, what is your best “out” pitch? Ask him to list his pitches in order of his confidence level. As a catcher, you want to get to the point where you and the pitcher are of the same mind. Your pitch choices are the same as his. As he stands on the rubber and decides on the next pitch, you want your signal to more or less take the words right out of his mouth. Nothing is better than when a pitcher and catcher are on the same wavelength and together slice through the opposing lineup.

Taking the time to communicate and learning how to call a good game helps a catcher earn the trust of his staff. Most great receivers aren’t remembered as box of rocks. Having the ability to put down the right signs takes a huge load off the pitcher’s shoulders by letting him focus on execution rather than choices. Yogi Berra summed it up nicely when he wisely stated, “Think! How the hell are you gonna think and hit [or pitch] at the same time?” Helping shoulder the mental load of pitch calling can help your staff concentrate on what’s important: throwing strikes.

Pitch Selection and Pitch Counts

I don’t have an enormous amount of information regarding proper pitch selection because what might be right for one situation won’t fit another situation. A huge list of variables must be filtered through the mind of the catcher, and they are constantly in flux. Some of the components affecting the decision-making process are the strengths of the particular pitcher, the weaknesses of the hitter, the game situation, and the umpire, to name just a few. Like I said, the list goes on and on and is rarely the same twice. Even though there is nothing written in stone, here are a few of the guidelines I followed.

The catcher’s primary focus should be to help the pitcher get outs as quickly and efficiently as possible. Keep your pitcher focused, and don’t let him get caught up in the thrill of making hitters look bad or the trap of trying to make a perfect pitch. Realize that the idea is not so much to “trick” hitters but rather to pound the strike zone in good locations, resulting in quick outs. Keep the pitch count down. Make the opposition swing the bat often and early by keeping your pitcher around the strike zone. I’ll take a first pitch ground out over a strikeout any day of the week. Both scenarios result in an out; however, the ground out requires only one pitch whereas the strikeout takes at least three. Over the course of a game, those numbers can really add up. Keep the pitcher focused on being efficient rather than wasting energy on something else.

Along those same lines, it’s important for the catcher, coach, and pitcher to realize that there’s rarely a pitch you just can’t throw to someone. Usually, even a “bad” pitch selection thrown in the right spot will work. From years of experience seeing thousands of outs, I can tell you that more often than not success or failure depends on the location of the pitch. I will say that again: location, location, location. It’s like real estate. that being said, don’t fall into the trap of setting up on the corners too much or letting the pitcher get too “fine.” If he is obsessed with throwing the ball in the perfect location (i.e., down and right on the corner), then unless his name is Greg Maddux, he is not going to be throwing a lot of strikes. You don’t want to put the hitter in the driver’s seat by getting yourself in counts where you have to pipe a fastball. Again, make hitters swing the bat and get quick outs by pounding the strike zone early with quality pitches.

The last thing to mention on the subject of what pitch to call is always to go with your pitcher’s strength. For example, if confusion arises because a certain hitter is known as a great change-up hitter but that is also your pitcher’s best pitch, go with the change-up. Again, if that is the pitcher’s best chance of throwing a strike in a good location and he can do it with conviction, then that is the best choice no matter what the scouting report says. Always call the game according to your pitcher’s strength instead of the hitter’s weakness.

Pace of Game

As a catcher, you also control the pace of the game. You’re kind of like a point guard in basketball. You can push the ball up the court and play the fast break game or you can slow it down and stall. The speed pedal is under your foot, and by toying with it you can control momentum shifts. I’m not going to lie—as a general rule, I have a heavy bias for pushing the action. I love quick play and recommend it for a number of reasons. That being said, when the offense was rolling and crushing my pitcher, I definitely tried to break the opposing team’s momentum by slowing down the action. Outside of that situation, though, I tried to put the signs down quickly and confidently and felt that doing so positively impacted my team. How so? Well, for one thing, I liked to get my pitcher in the groove of getting the ball, getting on the rubber, and letting it go. Like I’ve said before, the less time a pitcher has to think, the better. Pushing the action also keeps your defense on its toes. I know from playing middle infield that there is nothing worse than a pitcher who takes a minute in between every pitch. How about this reason—fans love quick games. But probably the biggest and best reason for speeding up play is that you take the opposition out of its comfort zone. In general, ballplayers know how to play the game at one speed—slow. Most have no idea how to compete at a quick pace. Pushing the issue by getting the ball back to the pitcher right away and quickly putting down the signal makes good sense if for no other reason than it makes the opposition uncomfortable.

Brent Mayne was a major league catcher from 1989 to 2004. He played most of his career with the Kansas City Royals but also spent time with the Mets, A's, Giants, Rockies, Diamondbacks, and Dodgers. He ranks 75th in the history of baseball with 1,143 pro games caught, and his .993 career fielding percentage is 4th all-time. Brent also has the distinction of being the only catcher in the twentieth century to have won a game as a pitcher. He caught Bret Saberhagenʼs no-hitter in 1991. An All-American in college, Brent was drafted in the first round (13th pick overall) and inducted into the Orange Coast College Hall of Fame in 2006. Mayne was a decent hitter with occasional power and compiled a career high .301 batting average in consecutive seasons (1999-2000).

In retirement, Mayne has gone on to serve on the board of directors of the Braille Institute and the Center for Hope and Healing. He is also the author of a book titled "The Art of Catching" and creator of a website, blog and podcast series at www.brentmayne.com.

Permalink | Comments (7)

A few weeks back, Jeremy Greenhouse presented a new method for evaluating who throws best pitches in baseball. Building on work by Dave Allen and John Walsh, the principle is to evaluate pitches based on their outcomes. Jeremy's innovation was to use regression to predict the likelihood of each outcome, given the velocity and movement of each pitch. Previous methods (such as those at FanGraphs, have the problem of giving too much credit to lucky pitchers. If two pitchers throw exactly the same pitch, Bronson Arroyo may get an out, and Chris Carpenter gives up a hit. The outcome-based method would give exactly the same credit to both pitchers.

While Jeremy was working on his analysis, I was working in parallel on a similar method. I've used a kernel density estimator and expectation-maximization algorithm to classify each of the 480,000 pitches throw by right-handed pitchers to right-handed batters between 2007 and 2009, and then estimate the likelihood of relevant outcomes. Some differences, instead of movement and velocity, this analysis includes five parameters: horizontal location, vertical location, velocity, vertical movement, and horizontal movement. Further, we can look at each pitch along each dimension in isolation to give a rough estimate of the importance of each dimension.

Note that although this method is not biased to favor lucky pitchers, it may be biased to punish pitchers with "intangibles." We can build any physically measurable factor into our model, but that won't help us quantify the value of "deception." I fully believe that some pitchers have strange deliveries that throw a batter's timing off, and some are better at sequencing their pitches. This method will undervalue them, because it is essentially evaluating each pitch in isolation. This method will fail to account for pitch selection or sequencing, or any contextual variables. Having a variety of pitches allows a pitcher to set up better pitch sequences, which will make the same fastball more successful. This method can't account for that.

Relative Importance of Components
Once each pitch was evaluated along each of the 5 dimensions, we could look to see how well these values correlated with the overall value of the pitch. This is sort of daft--we have a high powered mathematical algorithm that takes into account high-order statistical dependencies, and then we use a linear regression to evaluate the components. In using the regression for this step, we will lose the ability to look at nonlinearities and interactions, but its a first step. Depending on which pitches we look at (just 4-seamers, or all fastballs), this linear model explains 50 to 90% of the variance.

Regardless of how which pitches we include, the most valuable component is Velocity (with a beta of .592), followed by vertical location and movement (.494, .338 respectively). horizontal location limps in next at .163, and horizontal movement had might as well stayed home, at .070. These numbers change slightly depending on the parameters of the model, and the filters and such, but the general picture remains the same.

Top 20 Fastballs

Here is a list of the top 20 fastballs thrown between 2007 and August 2009, inclusive. Pitches are averaged by pitch type (4-seam fastball, FB; 2-seam fastball, FT; cut fastball, FC), for each pitcher and then ranked by average value. The marginal value of the pitch dimensions are summarized in Control, Velocity and Movement, evaluated by calculating how much value would drop by removing these dimensions. These values are represented as weighted Z scores.

Pitcher Plots
Below, I've plotted the pitch values on a pitch-by-pitch basis for a few pitchers I selected arbitrarily. The first plot shows the movement and the velocity of each pitch, to give a sense of how successful the pitch classification system was. The second and third plots show the expected value of each pitch plotted against its X location and velocity.

#1 Zack Greinke, 2-Seam Fastball

Greinke's two-seam fastball was given the highest rating in both control and movement and velocity. These values reflect how much the value of the pitch decreases when you remove that dimension from the equation. So it is a little misleading, since a better pitch has more to lose if you remove an important dimension. There are many guys who throw harder than Greinke, but there are no pitchers who would suffer more if they suddenly had league-average velocity.

#2 Roy Halladay, 2-Seam Fastball
#7 Roy Halladay, Cutter

My classification system says that Halladay has 3 pitches: the 2-seam fastball, the cutter, the curveball. He probably has a change-up that is being misclassified as well. But however you split it, they are a very good pair of pitches. The value-by-location plot shows pretty good control; he hits the outside half of the plate frequently.

#3 Ronald Belisario 4-Seam Fastball

If you don't know who Ronald Belisario is, you're not alone. His fastball averages 95 mph, and crosses the plate in the zone 56% of the time. He has a 1.92 ERA in 65 innings, though with a somewhat low BABIP. We only have 319 pitches to analyze, so he's likely getting somewhat lucky,

#5 Jonathan Broxton, 4-Seam Fastball

Broxton has a crazy good, totally boring fastball. Its all about velocity. He averages nearly 97 mph, and you can see from the value by velocity graph that he can touch 100, where his value spikes. His vertical movement is good, averaging 10 inches. He also has good command, hitting the strike zone 57% of the time. No bells or whistles here, just heat.

#9 Mariano Rivera, Cutter

If Rivera wasn't included as one of the top fastballs, we'd know something is wrong. Want to see something really beautiful? Check out the histogram at the bottom of the value-by-location plot. That's control.

#11 Daniel Bard, 4-Seam Fastball
Our scouts tell us Bard relies a 96 mph fastball that can reach 101 mph and a 82 mph slider wih bite. He also supposedly has a high 80s cutter, a low 90s sinker, and a change-up. We don't have enough data from Bard to see his full range--he only barely makes the 100 pitch minimum--but we can still get an initial look.

Pitch F/X agrees with the scouts: he has a very consistent 97 mph fastball with 11 inches of vertical movement. He relies heavily on the fastball and slider, but he has also thrown a handful of change-ups. He has not yet thrown a low 90s sinker or high 80s cutter in the majors. The lateral location of his pitches looks bimodal, almost like he's either trying to throw inside, or hit the outside edge. Those inside pitches account for many of his worst pitches. His best pitches were high and outside.

#27 Jonathan Papelbon, 4-Seam Fastball

When he's not dancing, he throws this...

Other Rankings of Note
#22 Adam Russell
#29 Grant Balfour
#30 Josh Beckett
#32 Matt Lindstrom
#43 Frank Francisco
#45 Justin Verlander
#50 Zack Greinke's other fastball

Permalink | Comments (3)

[Editor's Note: Dave Baldwin is a former MLB pitcher. He pitched for the Washington Senators (1966-1969), Milwaukee Brewers (1970), and Chicago White Sox (1973). His best season was 1967 when he posted an ERA of 1.70 with 12 saves. Dave has been a member of the Society for American Baseball Research since 2002.]

Part of any pitcher’s job is to understand what goes on in the murky, cobwebby recesses of a batter’s head as the ball is hurtling toward the catcher’s mitt. In fact, this is a pitcher’s most formidable task because the wiring of the batter’s brain is a neuronal mishmash, poorly understood even by the best of baseball’s neuroscientists.

But let’s not be too hard on the batter’s poor brain—it is asked to do an incredibly tough job. During the first two-thirds of the pitch’s flight, the batter simultaneously collects information and performs critical calculations with respect to the ball’s trajectory. From these calculations, he predicts where and when the ball will be at the potential point of impact with the bat. When the ball is approximately twenty feet from the ball/bat contact point, a decision is made and the batter commits to taking the pitch or swinging. That decision is absolutely irreversible if the batter is taking, and if the batter is swinging, he can’t change the trajectory of the bat’s sweet spot (although he can still attempt to check the swing by pulling his hands against his body).

So Little Time

A good fastball traveling at, say, 90 miles per hour (mph) takes about four-tenths of a second or 400 milliseconds (msec) to get from pitcher’s hand to the contact point (assuming the pitcher releases the ball about five feet in front of the pitching rubber and contact is made about a foot in front of home plate). The batter’s noggin has about 270 msec or a little more than a quarter of a second to get its ducks in a row and start the swing. But, although the bat has started its journey, the batter’s conscious mind is still unaware that the batter has decided to swing.

How do we know this? In the 1970s, neurophysiologist Benjamin Libet conducted a series of experiments to determine the relationship between the conscious intention to carry out an action and the initial brain activity that must precede the action. He found that the brain lights up about 350 msec before the conscious mind is aware the action is to be taken (Libet, 1985; Libet, et al., 1983). But the batter’s brain has only 270 msec to decide whether and where to swing. If these decisions were to be made by the conscious mind, the ball would be in the catcher’s mitt before the batter could do little more than start moving the bat. In fact, the ball is only 50 msec (about seven feet) away from the contact point when the batter’s conscious mind finally realizes that he is swinging the bat. The batter can do nothing to alter the swing in that final 50 msec. Thus, he is hitting with his unconscious mind.

What we are calling the “conscious mind” is primarily the cerebral cortex. The “unconscious mind” comprises those brain components that collectively produce mental phenomena occurring without the person being aware of them. The ancient, deep-brain region called the limbic system (amygdala, hippocampus, hypothalamus, etc.) is a major part of the unconscious mind. It interacts with the cerebellum, a brain structure responsible for coordinating muscle activity during the batter’s actions. This is the same quick neural circuitry that tries to save a hiker who is the target of a rattlesnake’s strike. A hiker dodging a two and a half-foot strike of a five-foot snake has about 200 msec to come to the conclusion to jump—even less time than is granted the batter, but the hiker’s problem is much simpler, of course.

What the Batter's Brain Must Do

Let’s consider the steps the batter’s brain must take during those critical 270 msec. First, the unconscious apparatus must gather information about the behavior of the ball. If it fails in this initial task, the batter might just as well go up to the plate with a wet noodle instead of a bat.

The batter needs to begin collecting pitch information as soon as possible. To prepare for this “quick read,” the batter’s conscious mind concentrates on an imaginary “box” where he expects the pitcher’s release point to be. Thus, his cerebral cortex is thoroughly occupied and doesn’t hinder the unconscious mind. If he has guessed correctly and the ball is released from that box, he can begin to evaluate the pitch as it leaves the pitcher’s hand. Otherwise, the batter must spend precious milliseconds searching for the ball.

Not only must the batter predict where the ball will be at the instant of bat/ball contact but when the ball will arrive there, as well. To do this, the batter observes the trajectory and calculates the rate at which it is changing in each of the spatial dimensions. The visual parameters used by the batter to accomplish this are the apparent size of the ball’s image (used to estimate distance to the ball), distance of the image off the foveae of the batter’s retinas, and the horizontal angles of the right and left eyes. The time until bat/ball contact is calculated by the ratio of the image's apparent size to the rate of change of this size. These calculations are performed without the batter’s awareness.

During the early stage of the trajectory, the image seems to be coming very nearly directly at the batter’s eyes, but as the ball gets closer to the contact point, the horizontal angles of the eyes expand, and the eyes have increasing difficulty keeping the image on the foveae. In fact, the eyes aren’t able to follow the pitch all the way to the ball/bat contact—the image “outruns” the foveae when the ball is about five feet from the contact point (Bahill & Baldwin, 2004). This doesn’t matter since the batter can do nothing at that point to alter the trajectory of the bat’s sweet spot. During the last five feet of the pitch’s flight, the batter would do just as well if he had his eyes closed.

Note that the ball “appears” to approach the contact point more rapidly in the later stages of its flight, even though the 90 mph pitch actually slows by about eleven and a half mph because of drag force during the flight. The batter’s mind makes adjustments for this phenomenon. To experience this illusion, watch the median stripes on a highway as you travel at a constant speed of 60 mph. A stripe that is quite distant down the highway will seem to creep toward you, while a stripe very near the car will seem to whiz by, even though the car is moving at the same speed relative to the two stripes, of course.

Besides using the visual clues discussed above, the batter might also check out the ball’s spin pattern for indication of pitch behavior. Some batters report seeing a pattern of stripes (and maybe a dot) made by the red seam as it whirls around the axis of the ball; some say they can’t see anything but a gray blur. If a batter’s unconscious mind recognizes the spin of the pitch, it has information about the direction and magnitude of the ball’s spin-induced deflection (Bahill, et al., 2005). The trajectory of any spinning pitch (i.e., one that isn’t a knuckleball) will be deflected by the spin to some extent. Hitting a baseball is a skill of precision—the batter must adjust to even a slight deflection.

I surveyed fifteen former major league position players and found that only eight remember seeing the seam spin pattern. These results might indicate visual differences, or they might stem from variation in the way the pattern is processed and stored in the brain. Coaches generally assume that the ability to see the spin pattern will make for a better hitter, but the success of a batter doesn’t seem to be related to his ability to recall seeing this pattern. Using two Hall of Famers as examples, we note that Frank Robinson has reported he was able to see the seam, but Mike Schmidt has said he was never able to see it (Schmidt, 1994).

Taking Advantage of the Batter's Brain

How can the pitcher benefit from knowing how the batter’s brain works? For many decades pitchers have known how to “set up” the batter for an out pitch. The pitcher does this by using the residual image of the previous pitch to confound the hitter. This works because the image resides somewhere in the unconscious mind, retained in short-term memory. The pitcher sets up the batter by showing him a pitch—say, a high, inside, smoking fastball. The batter can’t help but maintain the memory for some short period—long enough to allow the pitcher, working quickly, to come back with an ever sooooo slooooow curve while smoke is still hanging around in the batter’s cranium. Psychologists call this “visual priming”—an earlier visual stimulus influences response to a later visual stimulus. Knowing how to set up the batter is an important part of knowing how to pitch.

The pitcher can also benefit from a distraction of the batter’s unconscious mind or from giving the cerebral cortex extra information to process, thus interfering with the unconscious operations. I once had a catcher who would, on occasion, toss a handful of dirt on the batter’s shoes just as the pitcher was releasing the ball. He would do this only on a crucial pitch at a crucial point in the game. This made the batter’s unconscious mind spend some milliseconds trying to deal with the surprise.

Another way to accomplish this is to startle the batter with a loud or threatening noise. A few pitchers in baseball history have developed the knack of giving out a resounding grunt just as they released the pitch. And I remember hearing of a catcher who, now and then, would blast the batter with an ear-splitting whistle at an opportune moment. Both of these tricks distracted the batter. The unconsciousness switches from processing visual information to handling the unexpected auditory information. This switch has some real-life practical applications, such as heeding the snorting of a charging rhinoceros.

Several pitchers have had success in giving the batter’s conscious mind plenty of time to make decisions. The “eephus” thrown by Rip Sewell in the 1930s and ‘40s, and Steve Hamilton’s “folly floater” of the ‘60s are prime examples of pitches that worked well in part because they allowed the batter’s clumsy cerebral cortex to get involved. These pitches were lobs that reached a height of twenty feet or more at the apex. Pitches tossed to such a height take more than a second to reach the potential contact point—long enough to give the cerebral cortex plenty of time to get wound around itself, pondering how to slant the swing.

This is a difficult problem because a swing angled with a slight uppercut (usually the most effective angle on a normal pitch) will cut perpendicularly across the path of the descending lob, making timing the swing extremely difficult. The best angle with respect to timing the lob is an acute uppercut, one that will result in a high pop-up if the batter manages to make contact. Anyone who has attempted to fungo line drives has realized that tossing the ball high makes the task very challenging. To avoid this dilemma, experienced fungo hitters, such as Jimmie Reese, would give the ball a very short toss and hit it when it is almost stationary, near its apex.

The batter’s mind usually fails to resolve the swing-angle problem of the lob. Late in his career Steve Hamilton told me that, although he had thrown the folly floater many times, it had resulted in a hit only once—Frank Howard, showing remarkable presence of mind, had tapped the pitch over the first baseman’s head for a looping single.

Researching the Batter's Brain

In this article we’ve seen that batters’ brains carry out very complex operations. Given the importance of the unconscious components of the batter’s mind, perhaps research into how they are affected by various performance enhancers would be appropriate. For example, we have evidence that some scents—those of lemon, peppermint, and cinnamon—have a beneficial affect on the cerebral cortex, resulting in improved performances in mental and physical tests (Zoladz, 2005), but little is known about how these or more powerful performance enhancing chemicals affect the unconscious mind. With advances in technology giving us extremely precise measurements of the pitch, the hitting process, and the concomitant patterns of neural activity, we might be able to learn a great deal about what happens in the batter’s unconscious mind. In the future, the batter’s box might become an indispensable neurophysiological laboratory.

Note: In this article, all times are rounded to the hundredth of a second, and distances are rounded to feet.

References:

Bahill, A.T. and Baldwin, D.G. 2004. “The rising fastball and other perceptual illusions of batters.” In Biomedical Engineering Principles in Sports. G.K. Hung and J.M. Pallis, eds. NY: Kluwer Academic / Plenum. pp. 257-287.

Bahill, A.T., Baldwin, D.G., & Venkateswaran, J. 2005. “Predicting a baseball’s path.” American Scientist, 93(3):218-225.

Libet, B. 1985. “Unconscious cerebral initiative and the role of conscious will in voluntary action.” Behavioral and Brain Sciences, 8:529-566.

Libet, B., Gleason, C. A., Wright, E. W., and Pearl, D. K. 1983. “Time of conscious intention to act in relation to onset of cerebral activity (readiness-potential): The unconscious initiation of a freely voluntary act.” Brain, 106:623-642.

Schmidt, M. and Ellis, R. 1994. The Mike Schmidt Study: Hitting Theory, Skills and Technique. Atlanta: McGriff and Bell Inc.

Zoladz, P.R. and Raudenbush, B. 2005. “Cognitive enhancement through stimulation of the chemical senses.” North American Journal of Psychology, 7:125-140.

Dave Baldwin is a former pitcher, geneticist, and engineer. He is now retired and living in Yachats, Oregon. His memoir is described at http://www.snakejazz.com/.

Permalink | Comments (9)

Hello loyal readers of Baseball Analysts. My name is Shawn Haviland and I am a right-handed pitcher in the Oakland A’s organization, currently pitching for the Kane County Cougars in the Midwest League.

Prior to being drafted by Oakland I attended Harvard University, graduating in the spring of 2008. After playing in the Northwest League for the Vancouver Canadians I began blogging about my experiences, starting with my off-season workout regimen and continuing on through the season recapping each start and discussing other parts of the minor league experience. I’ve been reading The Baseball Analysts for a while and really enjoy the work that they do so hopefully I can keep up the high standard that has been set.

I became interested in advanced metrics a few months before this season when I first heard about Batting Average on Balls In Play (BABIP) through my search for answers as to why I was striking out more than a batter per inning but still had a batting average against of over .260. It seemed like every time they put the ball in play it was going to be a hit. From there I was hooked on the “numbers behind the game.” Despite my interest, the “saber metric revolution” hasn’t really made a huge impact on minor league baseball from the standpoint of how pitchers approach the game.

Minor league pitchers focus on only a few statistics: ERA, WHIP and K/BB ratio. Our pitching instructor preaches that if you want to advance to the next level (the only thing that minor league players really care about) you need to have a below league-average ERA, a WHIP below 1.3 and a strikeout-to-walk ratio of at least 3 to 1. Seems easy enough but as I know now I have less control over these statistics than I would like to think.

For example, my season this year has been a tale of two different halves. The first half of the year I was very successful hitting each mark, I was in the top 10 in the league in ERA, had a WHIP below 1.3 and was averaging approximately 8 strikeouts and 2 walks per game. The second half of the year my strikeout-to-walk ratio has stayed around 3 to 1 (7.5 to 2.8) but my ERA and WHIP have shot up, despite the fact that I feel like I have executed my pitches better in the second half of the season than the first half. What happened, you might ask? The answer here seems to be that my BABIP has gone up almost every month all the way up to over .360 in August.

(You can check out my full month-by-month splits and other assorted numbers of interest on minor league splits.com.)

I know that BABIP is not the only factor that is affecting my ERA but it certainly is not helping me achieve the organizational goal of having a below league-average ERA. The fact of the matter and the unfortunate thing for anyone victim of high BABIP, is that these stats are not prevalent in minor league clubhouses. Coaches see a rising ERA and think that the pitcher is pitching worse, which may be the opposite of the case.

Now if I handed that last paragraph to the majority of minor league baseball players I probably would be met with a blank stare. However, if I asked minor league pitchers about their ground ball ratio, most would be able to tell you exactly what their ratio is (mine is .89) and how they are trying to improve their ratio by throwing different pitches to force ground balls.

Batted ball type is the area where advanced metrics has broken into minor league baseball. Our roving pitching instructor Gil Patterson constantly says that it is “impossible to hit a ball out of the park if it is on the ground.” During instructional league we talked a lot about if you are able to make the hitter hit the ball on the ground the worst-case scenario, unless they hit the ball directly down the line, it is going to be a single. If you can make a team hit three singles to score a run you are going to be very successful. While BABIP is slightly higher on ground balls than fly balls it is worth the sacrifice because doubles, triples and home runs are what really hurt pitchers and allow for multiple runs to be scored very quickly.

Pitching for ground balls also eliminates the effect of the ballpark you play in. Our High-A team is in Stockton, California, in the hitters’ paradise that is the California League. Every pitcher that I have talked to says, “Pick up a sinker or a cutter in Kane County because you are going to need it in Stockton.” If you turn on the television and watch any major league baseball game the number of pitchers who are throwing predominantly four-seam fastballs is dwindling. Brian Bannister is a perfect example of this, in that he as all but scrapped his four-seam fastball and instead throws a sinker and a cutter.

The majority of teams in the major leagues rely heavily on home runs as a source of run production; and after the high-powered offense era pitchers are finally catching up and realizing that velocity is not the most important factor in success (although it is nice to throw gas) but rather the ability to make the hitter hit the top of the ball truly breeds success. Armed with this information, pitchers, like Bannister, are making adjustments to force the hitters to keep the ball in the yard.

This brings up the argument as to what is more important: pitch type or pitch location. When we have our pitchers' meetings to formulate the game plans against opposing hitters, axioms like, “he can’t hit a curve ball,” or “he has a long swing, so he won’t be able to catch up to a fastball,” are consistently thrown around. I have never liked speaking in absolutes because I don’t think that there is a hitter in pro ball, or college baseball for that matter, who can’t hit a certain pitch. The players who have a hole that blatant were weeded out long ago. However, there are players who cannot hit a well-located fastball or curveball. My point being that every hitter can hit a fastball belt high right down the middle or a hanging curveball so to simply throw a pitch that the hitter “can’t hit” is not enough. As with real estate, pitching is all about location, location, and location. Although I have no statistical proof, I would argue that throwing the “wrong” pitch in a good location is going to lead to a lot more success than throwing the “right” pitch that is poorly located.

Vladimir Guerrero is one of the best fastball hitters in the game today but you will see him weakly hit a well-placed fastball. Hitters have the hard job, they need to recognize what pitch is coming and then hit a round ball with a round bat to a place that is not occupied by a defensive player. As a pitcher, all you have to do is locate your pitch and let the batter hit it at someone. Statistics tell you that more times than not the hitter is going to get himself out.

Thanks for reading. If you have any thoughts or questions, feel free to leave comments below, email me or check out my blog Ivy League to MLB.

Permalink | Comments (13)

“...in the Retrosheet era.”

There's no denying the immense drama that surrounds the walk-off home run. From Bobby Thomson in 1951 to Bill Mazeroski in '60, Kirk Gibson in '89, Joe Carter in '93, Big Papi in 2004 and more, the walk-off home run has been inspiring writers and baseball fans alike for decades. It's even helped get certain players elected to the Hall of Fame.

Thanks to SABR, we know that the current leaders in career walk-off home runs are some of the all-time greats: Frank Robinson, Mickey Mantle, Jimmie Foxx, Stan Musial, and Babe Ruth, all with 12 career walk-offs. It's a formidable group and, unlike the Thomsons and Mazeroskis above, there's not a single surprising name on that list.

But the home run is not the only way to earn a walk-off victory. For our purposes, we’ll use the most liberal definition of a walk-off victory (WoV), which is "a run-scoring event in the bottom half of the last inning of the game that gives the home team a winning margin." This means that any event that causes a run (or runs) to cross the plate can be considered a "walk-off". Base hits, ground-rule doubles, bases loaded walks, steals of home, sacrifice flies, passed balls, wild pitches, errors, balks, and even interference can all lead to a WoV.

I thought it'd be interesting, then, to do a study of these non-home run walk-off events. When you start looking at the data, you find that there are a lot of questions that can be asked: if Ruth, Mantle, Robinson, et al are the leaders for home runs, who are the leaders for the other categories? Is it a certain type of hitter? And what kind of situation leads to the most WoV's? Are there any seasons where the WoV was abnormally frequent?

And once you start poking around with those questions, more come flooding out: who has given up the most WoV's? What pitcher-batter combo has teamed up for the most WoV's in history? In that same vein, what batter-baserunner combo has teamed up to score the most WoV-runs? Does the list change if we only consider the baserunner who scored the winning run? And who is the baserunner who has scored the most winning runs in WoV's? What about non-winning runs?

As you can see, there is plenty to answer about walk-off victories if we just look at the data – and some of it is bound to be interesting. So, using the Retrosheet play-by-play data from 1954-2008, this is what I've found. I'll break the discussion into Batters, Pitchers, and Baserunners to keep it manageable. And if there's something about the data that I didn't include or that I haven't considered, please let me know.

The Basics

But first, some general information about WoV’s.

In the Retrosheet era, there have been 9,887 games ending in a walk-off fashion. The top five walk-off events in that time are so:

Error, wild pitch, fielder’s choice, and triple are the only other walk-off categories that occurred more than 100 times. Excluding the nearly 2,800 games won by walk-off home runs, the teams with the most walk-off victories (and defeats) are as follows:

Again, this data only spans the Retrosheet era. It’s still surprising to see the Astros so high on career victories, though, considering how many other teams had a seven-year head start.

Finally, before we get too deep into the details of the batter and pitcher data, it seems like this is a good place to list the single-season leaders for walk-offs, for both pitchers and hitters. As with most everything else, this list excludes walk-off home runs:

The Batters

Looking at the remaining 7,100 non-home run walk-off events, the vast majority were officially scored as singles (4,805 walk-off singles). Many are more complicated than a mere base-hit (one-, two-, and even three-base errors, etc) but, for our purposes, they will be counted as a single.

We also find plenty of non-batting events in the data: stolen bases, balks, wild pitches, and passed balls are all there in the data. If we remove those from consideration for now - so that we don't credit, say, Cliff Floyd with a walk-off hit when John Rocker balks in the winning run - then the leaderboard for most career walk-off victories, non-home run variety looks like this (and, yes, we do count HBP, BB, errors, and other events that the batter initiated in this list):

There are quite a few unsurprising names on that list, Hall of Famers known for their run producing ability. But there are also a number of very surprising names. Manny Mota is number one? Dusty Baker tied with Pete Rose for number two? Rusty Staub? Ted Simmons?

A couple of interesting things to note: nearly half of Mota's non-home run WoV's came as a pinch hitter (he also has one walk-off HR to his credit). That's nine times he was called in from the bench in a game-changing role in which he came through to win the game. Talk about your go-to guy off the bench. Also, Frank Robinson appears in the top 10 on this list, with 15 non-home run WoV's (including one sacrifice), which is very impressive in itself. However, he also sits atop the walk-off home run leaderboard with 12. Combining the two, he sits all alone at the top of the WoV leaderboard, with 27 homers and non-homers alike. Yet another reason to love the career of baseball's most underrated superstar.

Breaking those down even further, here are the walk-off leaders in each of the more standard offensive categories:

And the less-than-standard offensive categories:

It should be noted that there are no players with more than one walk-off HBP. And please also note Frank Robinson atop the walk-off doubles list. That's 17 career walk-off extra base hits. He's the walk-off king.

But what about the inning/outs situation? When are WoV's most likely to happen? The table below shows the frequency of non-home run WoV's in the 9th through 14th innings, broken down again by the number of outs.

And, finally, who is most likely to get that WoV? Is it the high-average/high-OBP guys in the leadoff spot or the sluggers in the middle of the lineup, or does it even matter? With Manny Mota, Pete Rose, Andre Dawson and Frank Robinson all atop the leaderboard, it's hard to say.

The Pitchers

The "walk-off hit" has a very different meaning when you flip it around and start talking about the man on the mound. Whereas the batter and his teammates are thrilled by the moment - the journey from tension and worry to joy and exuberance is as quick as the flight of the ball - the pitcher and his teammates are devastated, walking off the field with heads hung down. As a pitcher, that is the one situation that you do not want to be in: the guy giving up the lead completely and for good, with no chance to recipricate.

Being the all-time leader in this category, then, is one of the more dubious honors in baseball. Who do we find on the leaderboard?

Similar to the leaderboard for hitters, this includes all events a pitcher might be considered responsible for, including wild pitches and HBPs. Passed balls and errors are excluded. We also continue to exclude home runs from the discussion.

Seeing Hall of Famers Rollie Fingers and Goose Gossage on the list shouldn't be too much of a surprise, considering the number of the games that they closed out. Frank Linzy and Ron Perranoski are the biggest surprises, as they only finished 342 and 458 games, respectively. After them, it's Mike Marshall who finished the fewest games in his career, with 549.

The fact of the matter is, if you keep putting the same guys out time and again in the ninth inning (and later) of tight ballgames, they're inevitably going to lose some games. It's almost amazing that, of Rollie's 709 games finished, he only gave up the walk-off in 36 of them (49 if you include home runs).

Not all walk-off losses (WoL) are the same, though. In the table below, the data is broken down by the size of the lead that was blown.

And, in the interest of thoroughness, the same list, but with walk-off home runs included, is provided below:

Finally, the question needs to be asked, what batter-pitcher matchup has ended in the most walk-offs?

Maybe not surprisingly, we don't have to go too far back to find the answer: between Sept 12, 2004, and Sept 1, 2005, Atlanta's Andruw Jones earned the walk-off victory in extra innings from Montreal's/Washington's Luis Ayala three separate times. Here are the three games (I had to include HRs in this search to find a unique candidate):

• Sept 12, 2004: Montreal @ Atlanta, 8-8, bottom 12, no outs, runner on first - RBI Double
• July 26, 2005: Washington @ Atlanta, 2-2, bottom 10, 2 outs, bases loaded - four pitch walk
• Sept 1, 2005: Washington @ Atlanta, 7-7, bottom 10, 0 outs, bases empty - solo home run

No other batter-pitcher matchup ended in a walkoff more than twice.

The Baserunners

One thing about walk-off's is that we remember them for the batter. The runner who earned his way onto the basepath and actually scores the run is easily ignored. For example, when we think back to Game 7 of the 2001 World Series, it's not Jay Bell that we remember for scoring the winning run, it's Luis Gonzalez.

But in the long history of the Major Leagues, it seems certain that there are some players who found themselves in these situations over and over again. At some point, you have to start thinking that they may have some actual skill at it. The leaders for most walk-off runs scored (and most walk-off winning runs scored) are as follows (excluding batter-runners scored via home runs):

Now there's a list that shows some greatness. Nothing but Hall of Famers and quality run scorers. It makes perfect sense that they would be on base for so many WoV's.

Eyeballing the list, it seems that it’s the top of the order guys – the #1 and #2 hitters like Rickey and Rose – who cross the plate the most. And while this makes intuitive sense, it seems worth checking. The list, excluding batter-runners scoring themselves via home runs, is below:

Okay, so no surprise there. But where do the winning runs come from, though? From what base?

It should be obvious that, across all WoV's, the winning run scores from third more often than any other base. But does this carry across all walk-off types, though? The table below shows the frequency in which the winning run scored from each base for the major offensive categories. If the game is tied, the first runner to cross home plate is considered the 'winning run'; if down by 1, it's the second runner to score, and so on.

And just for kicks, here's a list of players who scored the most winning runs by driving themselves in via the home run. I know that we're not really focusing on the walk-off home runs in this post, but it seems worth exploring for a minute. It's good to see Frank Robinson at the top of the list again.

And finally, as with the pitchers, the question has to be asked, what is the most prolific walk-off batter-baserunner combo, and does it change if we look only at the winning runs? Excluding walk-off home runs, the list looks like this:

The most surprising thing about those lists is how none of the top walk-off run-scorers show up. It's probably a product of player movement, but it's hard to say for sure. Don Kessinger and Kirby Puckett are the only players on the list who were also driven in three different times by an additional player. Pete Rose and Rickey Henderson, while never being driven in by the same guy four times or more, do have two different teammates who they matched up with three times each.

(Oh, and I’d talk about the stolen base leaders right here, but, sadly, they aren’t all that interesting. Of the 22 walk-off steals, no player has done it more than once. George Brett, Pete Rose, Rod Carew, and Eddie Murray are the biggest names on the list, with no Rickey Henderson or Tim Raines to be found. A few are recorded as steals of home, but many are also due to errors. In short, it’s a mish-mash.)

Conclusion

Well, that’s about all I can manage to squeeze into this post without delving into utter minutiae. (How often has a game been won with a walk-off single by the number 7 hitter with a runner on second with one out in the 10th and the home team down by one run? Who scored the most winning runs from first base in 1973?) There seems to be an unending amount of information to be found in the walk-off listings. I just hope I’ve been able to share the interesting facts.

In the end, though, I don’t think there’s a typical walk-off scenario to be found. The hitters at the plate, the baserunners who score the winning runs, and the pitchers who are responsible for the loss are all sufficiently varied in their notoriety/stats/skills that it really does seem to be “the luck of the draw.”

If I did have to describe the “typical” walk-off victory – with the caveats above – it would be this: it’s a tie-game in the bottom of the ninth and the top of the order is coming up. The leadoff hitter (or #2 hitter) gets on base and is moved into scoring position, where he is driven in by either a base hit or home run from the middle-of-the-order power guys. It helps to have all-star-or-better quality players batting in either of those lineup positions.

I’m guessing you probably could’ve guessed that. Still, it’s always nice to have the data to back it up. Now, the next time you see your team get that walk-off hit, you can say that you saw it coming.

Larry Granillo lives in Milwaukee and writes the blog Wezen-Ball.com, where he uses some do-it-yourself statistical analysis and various contemporary accounts (including newspapers and magazines) to look at the game of baseball, both past and present - and, whenever possible, at where the two meet.

Permalink | Comments (18)

A good deal of words have been written decrying the increased home run numbers thanks to the unfortunate placement of outfield walls in the new Yankee Stadium. In their efforts to faithfully reproduce the exact dimensions from the old park across the street, the Yankees nailed the distance from home plate in almost all of the right places. Right field corner, left field corner, straight-away centerfield, and the halfway marks between. However, they failed to take into account a nifty new scoreboard that covers part of the wall in right field and, unfortunately, causes the wall to lose its gentle curve. In effect, a good deal of the right field wall is about nine feet too close to home plate. What you have, in effect, is a straight wall in right field that simply begs left-handed hitters like Johnny Damon to deposit an easy homer above its shallow border. But really, is this really part of some sort of dastardly plan by the Yankees to grab advantage over their foes? I think not.

To date, there have been a whopping 185 home runs hit at New Yankee Stadium, already 15% more tater tots than were hit at the old place last season. But while 50% of the homers last year were hit with no runners on base, that figure has risen to 65% in the new place. On average over the past few years in the MLB, about 58% of home runs are of the solo variety. Is there something about the new park that decreases scoring overall even as homers fly out at a record rate? To wit: New Yankee Stadium is only seventh in the league for scoring; last year, the old place was ninth. Scoring is up only 0.5 runs per game between the old park and the new park. If the Yankees and their opponents keep up their current pace of slamming homers, the new place will end up with 240 homers hit, a full 50% more than last year, or about one extra homer per game.

Those two increases don't seem to mesh well. If the Yanks and their opponents are hitting an extra home run per game but scoring is only up half a run per game, where is that extra run going? Obviously, the huge percentage of solo home runs is providing solace to opposing pitchers who have been victims of the short dimensions in right field. Take Indians starter Anthony Reyes. On April 17th, the Indians lost to the Yankees by one measly run, 6-5, despite Reyes and two relievers allowing five homers to the Yanks. But, all five homers were solo shots, which kept the Indians alive in the game (they only had one home run in the game, a solo shot).

So what explains the high percentage of solo home runs in the New Yankee Stadium? One explanation is almost so obvious that I missed it at first: when a guy who hits in front of you hits a home run, he is unclogging the bases of those pesky baserunners. That leaves you, the batter, with an empty canvas on which to paint your own home run. Sorry, but that will only be one RBI for you, sir. In fact, Johnny Damon and Mark Teixeira have accomplished the back-to-back trick six times already this year, a franchise record. They've done it three times at home and the rest of the team has done it four more times, plus one occurrence of back-to-back-to-back home runs. That's nine home runs that must be solo shots because the gentleman ahead did the hitter a favor and cleared the bases.

Not that allowing all these solo home runs is going to get any pitcher off the hook, but if scoring is only up by half a run per game, then at least any wary pitcher nervous about giving up the farm when visiting Yankee Stadium can relax. You might give up a bunch of home runs, but if you're smart, you'll wait until the bases are empty.

==========

Rob Iracane co-edits Walkoff Walk, a thoughtful blog dedicated to baseball and the human condition. He and Kris Liakos have been active for over 18 months and their biggest claim to fame is posting a video of a shrimp running on a treadmill backed by "Yakety Sax" whenever an MLB team wins on a Walkoff Walk.

Permalink | Comments (2)

There's something human in static. Record collectors are fond of saying vinyl recordings have a warmer sound than their digital brethren, but I think the real humanity is in the airwaves.

I.

Medium wave amplitude modulation radio broadcasting was invented just a few years after the dawn of the modern era in baseball (when the rules we are familiar with today became codified). Guglielmo Marconi was awarded the first patent for the radio in the United States in 1900. Six years later, Reginald Fessenden propagated the first AM transmission from Brant Rock, Massachusetts. Radio remained a hobbyist's pursuit until it exploded in the wake of World War I. The 1920s heralded the beginning of the Golden Age of radio. It is no coincidence that the 1920s also represented the Golden Era of baseball.

Radio represented one of the first mass-media in the United States. Just as mass media were fueling national culture and the development of full-fledged consumer culture in the 1920s, so too was radio building the very first media markets. The first radio call of a live baseball game was broadcast on the first commercial radio station, Pittsburgh's KDKA. On August 5, 1921, Harold Arlin used a shoestring setup (he used a modified telephone) at Forbes Field to announce a contest between the Pirates and the Phillies.

The Pirates won 8-5. It was a brief game, lasting less than two hours, but featured a home run by Phillies centerfielder Cy Williams and a triple by Pirates third baseman Clyde Barnhart. It must have been thrilling to hear Arlin describe that moment when a runner approaches second base so fast that it dawns upon the announcer that the runner might just be headed for third.

For several years, subsequent broadcasts were not conducted live, but rather were recreations from play-by-play wire accounts. They often lagged innings behind the action on the field. But they also opened up the game to a broader audience. Despite owners' fears that radio would discourage fans from showing up at the ballpark in person, the prevalence of baseball radio broadcasts grew apace. As radios became centerpieces of the American living room, baseball enmeshed itself as part of the daily life of millions.

II.

The reality of a live broadcast is that the time is difficult to fill, and the long pauses or awkward attempts at filler make the broadcasts intimate. Indeed, Harold Arlin remembered not being exactly sure what to do or say:

"Nobody told me I had to talk between pitches [...] Sometimes the transmitter didn't work. Often the crowd noise would drown us out. We didn't know whether we'd talk into a total vacuum or whether somebody would hear us."

What's remarkable about baseball on the radio is just how much sense it makes. Most sports are chaotic, with infinite possible constellations of players on the playing surface. In baseball, there is only the count (of which there are only twelve states), the base/out situation (of which there are 24 states), and the inning (which of course there are usually nine). When the announcer relays that the shortstop, batting in a 2-2 count with runners on the corners, has roped a line drive down the third base line, you can imagine just what it looks like. With that sort of information alone, millions of boys and girls have surreptitiously used a transistor radio to reconstruct the Polo Grounds or Shibe Park right there in English class.

For decades' worth of Opening Days, the transistor radio was a shibboleth for manic baseball fans celebrating for the first time all winter the rich sounds of staticky play-by-play in their ear. You can make us work or go to school, they secretly shared, but you cannot make us pay attention.

And the broadcasters were our friends. They spent so much time talking into the emptiness and to each other that radio broadcasts became intimate. Radio announcers Graham McNamee, Red Barber, Mel Allen, Jack Brickhouse, Vin Scully, Harry Caray, and Harry Kalas (and countless others) became as members of an extended family.

III.

A few select stations pumped their frequencies with such potency that their broadcasts arced along the contours of the earth, through hills and mountains all but unimpeded, to even rural communities (the places we today call exurbs). Clear channel AM stations (like New York's WFAN and Chicago's WGN today) had no competition on their particular frequencies for hundreds of miles, allowing them to reach hundreds of thousands of households with every broadcast.

Slowly, radio broadcasters cottoned on to the cadence and style of a live broadcast. They began to fill up the empty space between pitches with players' statistics, provided to them on mimeographed sheets reproduced from media guides. Their catchphrases became just as reconstructable as the base-out state on the field. They were indelibly marked into memory.

Slowly, media markets emerged. Regional rivalries heightened as fans followed every play of every game and homer announcers embellished and enlarged the truth. Before there were regional television deals or network-neutrality violating online streaming video websites, a team's radio station provided the crucial link between fans and teams that remains the solitary reason why baseball became America's pastime.

IV.

The beginning of the decline of baseball on the radio was marked by one of baseball's iconic moments. It was one of those giants of broadcasting, the voice of the Giants, Russ Hodges, who penned its first epitaph. On October 3, 1951, Bobby Thomson roped a line drive off Ralph Branca over the left field fence at the Polo Grounds, giving the Giants a ticket to the World Series. Even to someone like me, much too young to have experienced the Shot Heard 'Round the World myself, it sounds more like this:

"There's a long drive--it's gonna be, I believe--THE GIANTS WIN THE PENNANT! THE GIANTS WIN THE PENNANT!"

Coincidentally, the third game of the three-game tiebreaker was also the first coast-to-coast live broadcast of a baseball game on a different frequency band: VHF television. NBC broadcaster Ernie Harwell's pedestrian call ("It's gone!") goes unremembered. In fact it is a sort of cosmic accident that Hodges's radio call was recorded at all, as a fan happened to record the final few innings to share with a friend.

Even though millions caught the game on the radio, the fact that something so spectacular happened on the live television broadcast made everyone who saw it an instant convert. Brian Biegel, in Miracle Ball (which chronicles his search for the Thomson home run ball) quotes Hall of Fame curator Ted Spencer:

"It was a special moment because it may have been the first thing we saw on TV in our house--1951 was the year we got a TV. I've always talked about it as baseball's first TV event. That home run was played continually all that night. Remember, there's no satellite, there's no twenty-four-hour-a-day news. News was fifteen minutes in those days--6:00 to 6:15 local and 7:00 to 7:15 NBC. But it was all over the place. It was fabulous. I think from that point on, baseball and TV really came together."

Regularly scheduled television programming had begun just four years prior to the Shot Heard 'Round the World. In 1950, just 9.0% of American households had a TV set. By 1951, the number was 23.5%, the largest year-over-year percentage point increase on record. And for all those early adopter households, this was one of the first "event television" moments. While radio remained an important part of baseball broadcasting, it never again held the place it once did.

V.

My experience with baseball on the radio has been very personal. As a young boy (an only child, no less), I would sneak to my family computer, which was the first I had used with a microphone. I would imagine a situation--inevitably the ninth inning and certainly with the bases loaded. Somehow it always seemed that Darren "Dutch" Daulton was at the plate (although on his nights off, John Kruk could pinch hit). Huddled next to the Macintosh SE, I would record myself doing Harry Kalas's home run call over and over again: "Outta heeeeere!" I can only imagine how many other kids have done the same thing (or perhaps some slightly less technological analog) since baseball was first broadcast over AM radio.

I don't dislike baseball on television; of course I enjoy watching it. I enjoy following a game on the computer with Gameday because it allows me the same sort of constructed reality that the radio did. Now that streaming video and audio are available on cell phones and laptops I wonder about the fate of that essential baseball institution, the radio broadcast. We live in a world of blackouts and interrupted coverage, of Joe Buck and Scooter the animated baseball. They spend so much time filling the pauses, and they say so little of much importance, because they really don't have to say anything. The action, after all, is right there to watch on the field. With the recent news that Vin Scully plans to retire after the 2010 season, I worry that we may be witnessing the final years of baseball on the radio.

I hope that the radios--the ones on workbenches and in cars, the ones stowed away in school lockers and backpacks, the ones perched on radiators in bathrooms and high up on the shelf at gas stations--I hope they don't disappear. Because to listen to baseball on the radio is to imagine the game, to imagine yourself there, to imagine the men in the booth. If it dies, I fear we will lose that imagination as well.

----------
Tommy Bennett writes for Beyond the Boxscore. He is a law student living in New York and a lifelong Phillies fan.

Permalink | Comments (8)

Johan Santana - have you heard of him? He's pretty good. The man is the ace of the Mets, was the ace of the Twins, and is one of the best left-handers in the game. He does it with a consistent, metronomic delivery that pumps out four difficult pitches.

Notes: PITCHf/x data from Gameday, classifications by the author ("cfx"); data covers 2007 (partial), 2008 and 2009; mph is the average speed at 55 ft. from the back of home plate; pfx_x and pfx_z are the lateral and vertical deviation from the path of a spin-less ball (inches); deg is the angle of the spin axis

Santana's slider is one of the best in baseball, which is a fine indication of the consistency of his delivery. But that's all old news. What brings me here is to explore Johan 2009. He's off to a great start, even better than years past, which begs a simple question. What's he doing differently? If anything, that is.

It's early, and I'm only looking at games through May 6, so this doesn't include Johan's most recent start. Some trends have emerged that merit watching. That's about all you can do with most early season returns. Keep that in mind.

The biggest change is in pitch selection. Johan is throwing far more four-seam fastballs (or simply "fastballs") and far fewer two-seam fastballs ("sinkers"). Santana also appears to be throwing fewer sliders, a pitch he mostly uses against lefties. His change-up is primarily a gift to right-handed hitters everywhere (the gift of zilch, that is) but got a little extra use against lefties in 2008.

That's a siginficant increase in heaters. Another look is from a four-start moving average of pitch mix.

I made sure to include this chart, because, when you squint, you can see a giraffe. But why is he doing this? Santana's four pitches are all above average. The change is one of the best, and both of his fastballs and the slider are solid pitches.

    rv100
CH  -3.7
F2  -1.7
F4  -2.0
SL  -1.5

If you're going to cut back on two pitches, they'd be the sinker and slider. I'm not sure why you would, neither pitch is hurting anyone but Santana's opponents. Breaking it down by season and, for good measure, batter hand, you do start to get the idea that the sinker and slider aren't what they used to be, while the change and fastball may be even better.

It's early, Santana is one of the greats and can beat you a few ways, so I'm not reading too much into this. I'm working with a short season and a partial data set (2007 didn't have full PITCHf/x coverage), too. But he's pitching well, he is throwing more heaters and fewer sinkers, and Santana's change-up is still a world beater.

Harry Pavlidis writes for Beyond the Box Score, The Hardball Times and Out of the Ivy. His own blog, Cubs f/x, feels neglected once in a while.

Permalink | Comments (4)

Baseball fans love to argue. Did Dustin Pedroia really deserve the MVP award last year? (After all, he was only 18th in the AL in OPS.) Sure, Manny can hit (can he ever!), but he gives it all back with the glove, right? On the flip side, is Adam Everett, with his fabulous defense, a valuable player? We older folks like to argue about the players of our youth: For example, who had the better career, George Brett or Wade Boggs? In the end, it usually comes down to putting a value on a player, a total value that includes hitting, defense, baserunning and everything else.

Well, Sean Smith -- you know, the guy who does the CHONE player projections -- is putting an end to some of these arguments. What Sean has done, bless his soul, is evaluate players on just about every aspect in which a player contributes to winning. And he's done this for all players going all the way back to the middle of the last century. Bravo, Sean!

So, what are these different aspects of baseball, the important contributions a player can make towards winning? Here's the list:

o batting
o baserunning
o avoidance of grounding into double plays
o defensive range
o catcher defense
o defensive arm for outfielders
o double-play proficiency for infielders

Sean has analyzed over 50 seasons of play-by-play data available at Retrosheet and determined each player's value in the above categories, expressed in runs above or below that of an average player. For the defensive categories, players are compared to the average for that position. I won't go into the methodology for all these categories, you can refer to Sean's explanations here. I do want to mention Sean's Total Zone system, which he uses to measure defensive range. After hitting, defensive range (and catcher defense) is the biggest contribution to a player's value. Total Zone uses Retrosheet play-by-play data to evaluate defensive range for all players of the last 55 years or so. It's a clever system that squeezes just about every bit of information from the play-by-play data, data that is not as complete as modern play-by-play data from professional statistics providers like Baseball Info Solutions or STATS, Inc. See here for more details on Total Zone.

Of, course there's a lot more here than just defense, as you can see in the list above. Now, we've known how to measure baserunning and outfield arm proficiency for a while and the other categories, given the Retrosheet data are treated in a similarl way. The important thing that Sean has done is to 1) put in the dirty work to make all these different evaluations and 2) put them altogether to allow us to get a total picture of player value. Oh, and 3) he's posted it all on the web for all to use (at no charge).

Do you realize how great this all is? I recently wrote an article for the Hardball Times that did an in-depth comparison of Carl Yastrzemski and Manny Ramirez. I got the hitting from baseball-reference.com, defensive range from Sean's own Total Zone system and the outfield arm ratings came from my own work at THT. I couldn't locate comprehensive baserunning information, so I had to work that out (a less complete analysis) on my own. Now, to write that article, I would could do all my "shopping" at Baseball Projection.

Sean then goes a couple of steps further with the data he has compiled. He translates "runs above average" to "runs above replacement", since a player's true value is best measured against a replacement level player. Along the way he gives each player a "position adjustment". Remember when I wrote that range is measured against the average defender at the same position? Well, the position adjustment accounts for the fact that the value of an average fielder is not the same for each position.

The last step is translating runs into wins and, since we are now relative to replacement, these are Wins Above Replacement, or WAR. I've been very brief in describing the system, if you want more info about determining overall player value, I heartily recommend a series of posts at FanGraphs, which goes through the process step-by-step, starting here.

Speaking of FanGraphs, those good folks have been doing similar work. They also produce WAR values for all players, using a different fielding system (known as UZR) and play-by-play data purchased from Baseball Info Solutions. Their data set goes back only a few years, though, so you need to use Sean's WAR database, if you want to look at, I dunno, who really should have won the MVP awards in 1974...

-------------------------------------------------------------

Jeff Burroughs is the guy who, when reciting the names of MVP winners, you always leave off the list. Well, him and Zoilo Versalles, I guess.* It's not that he was underserving of the award, although, he was, as we shall see shortly. It's just that looking back, he doesn't seem like much of a star. He actually was a very good hitter for a few seasons and I'm sure he's not the MVP-winner with the worst career.

*What? You mean, you don't find yourself reciting the names of AL MVP winners? That's strange, I do it all the time. Pennant winners and World Series champs, too. Just don't ask me who the 13th President of the United States was.

Jeff Burroughs in 1974 was probably the best hitter in the American League. The 23-year-old Texas Ranger hit .301/.397/.504, which is even better than it looks, since offensive levels were quite a bit lower 35 years ago. Burroughs finished third in on-base average and slugging percentage and finished among the top ten in just about every important offensive category. He only led the league in one category, but it was the right one for garnering MVP votes: RBI.

We can get an overall measure of Burroughs' hitting by considering the Batting Runs part of the WAR database. Here are the AL leaders for 1974:

 ------------------ ------ --------- 
| Name             | Team | BatRuns |
 ------------------ ------ --------- 
| Jackson_Reggie   | OAK  |      49 | 
| Burroughs_Jeff   | TEX  |      48 | 
| Carew_Rod        | MIN  |      35 | 
| Allen_Dick       | CHA  |      34 | 
| Rudi_Joe         | OAK  |      34 | 
| Yastrzemski_Carl | BOS  |      33 | 
| Bando_Sal        | OAK  |      27 | 
| Tenace_Gene      | OAK  |      27 | 
| Gamble_Oscar     | CLE  |      27 | 
| Grich_Bobby      | BAL  |      27 | 
 ------------------ ------ --------- 

Burroughs is right there with Reggie Jackson at the top of the list. Jackson finished fourth in the MVP balloting, which may be explained by Burroughs' advantage in RBI, 118 to 93. In any case, from a hitting standpoint, Burroughs was certainly not a bad choice for MVP.

But, baseball is more than hitting, of course — how did Burroughs do in the non-hitting categories? Burroughs was not a fast player, at all, so we don't expect him to excel at baserunning, defensive range and avoiding the GDP. But did he at least hold his own? Did the 1974 American League MVP at least approach the average players in the "extra" categories? I'm sorry to report that he did not.

Here's how Burroughs fared in the non-hitting categories:

o Defensive range - Burroughs was 17 runs worse than an average right-fielder. That's the worst range mark of any AL player in 1974.

o Outfield arm - sometimes slow guys have good arms. Not in this case. Burroughs cost his team an additional five runs with an ineffectual throwing arm.

o Baserunning - Two stolen bases and three caught stealings give you an idea of Burroughs' speed. He was also below average in advancing on the basepaths, giving him a net baserunning value of -3 runs.

o GDP - Burroughs grounded into 17 double plays in 1974, a few more than the average batter would have, given the same opportunities. Good for -2 runs.

o Position - it's not his fault, of course, but Burroughs played right field in his MVP year, which is an offense-first position. The adjustment for right fielders is -8 runs.

The 1974 AL MVP was below average in every single non-hitting category for a grand total of -35 runs. Yikes, that negates a good chunk of his batting runs (which was +48, you'll recall). In fact, without considering hitting, Burroughs was the very worst player in all of baseball in 1974 and he was one of only four players who was below average in each of the non-hitting categories. This dude was seriously one-dimensional.

So, who should have won that 1974 AL MVP? Well, if you don't require your MVP to play on a playoff team (Burroughs's Rangers did not make the playoffs), then you could rank MVP candidates according to their overall win value, or WAR:

 ----------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
| Name            | Team | Batting | Range | Arm | BsRn | GIDP | Position | WAR  |
 ----------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
| Grich_Bobby     | BAL  |      27 |     5 |   3 |    5 |   -2 |        4 |  6.9 | 
| Jackson_Reggie  | OAK  |      49 |     0 |  -2 |    0 |    2 |       -8 |  6.7 | 
| Carew_Rod       | MIN  |      35 |    -9 |   2 |    5 |    2 |        4 |  6.6 | 
| Rudi_Joe        | OAK  |      34 |     0 |   3 |    1 |    1 |       -8 |  5.6 | 
| Campaneris_Bert | OAK  |      13 |     6 |   1 |    4 |    1 |        8 |  5.4 | 
| Money_Don       | MIL  |      19 |     0 |   2 |    3 |    0 |        4 |  5.4 | 
| Maddox_Elliott  | NYA  |      19 |     4 |   6 |    4 |   -1 |       -2 |  5.1 | 
| Bando_Sal       | OAK  |      27 |    -4 |   0 |    1 |    0 |        3 |  5.0 | 
| Tenace_Gene     | OAK  |      27 |     4 |   0 |   -5 |   -1 |       -2 |  4.6 | 
| Robinson_Brooks | BAL  |       5 |    14 |   1 |    0 |   -1 |        4 |  4.4 | 
 ----------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
BsRn - baserunning runs
Range - includes catcher defense 
Arm  - includes infield DP rating

For me, it comes down to Bobby Grich, Jackson and Rod Carew. Pay no attention to the 0.3 wins separating these three — no system is accurate enough to distinguish players this close. Grich played a prime defensive position and played it exceptionally well. He won a Gold Glove at second base in '74, and was excellent with the bat and on the basepaths. Reggie, we already saw, was one of the top two hitters in the league, and he hangs on to those batting runs by coming out average in the other categories (except for position adjustment). Carew was top notch in everything except defensive range (he was still playing second base at this point).

In the actual vote, Grich finished ninth and Carew seventh. You might notice the absence of somebody from the above list: Jeff Burroughs, who totaled 4.0 wins over replacement for the season.

-------------------------------------------------------------------

Over in the National League, the voters did not fare much better: they elected Dodger first basement Steve Garvey over several more valuable players. The problem in this case was not neglecting the other categories (although I suspect many writers did so), but rather not doing a good job of evaluating offensive value.

Sean Smith's WAR database rates Garvey as the NL's ninth most productive hitter in 1974:

 --------------------- ------ --------- 
| Name                | Team | Batting |
 --------------------- ------ --------- 
| Schmidt_Mike        | PHI  |      49 | 
| Wynn_Jimmy          | LAN  |      47 | 
| Morgan_Joe          | CIN  |      46 | 
| Stargell_Willie     | PIT  |      46 | 
| Smith_Reggie        | SLN  |      40 | 
| Zisk_Richie         | PIT  |      33 | 
| Bench_Johnny        | CIN  |      32 | 
| Garr_Ralph          | ATL  |      31 | 
| Garvey_Steve        | LAN  |      29 | 
| McCovey_Willie      | SDN  |      28 | 
 --------------------- ------ --------- 

Why did the voters elect Garvey over these other superior hitters? Well, some of these guys were on non-contending teams, including Mike Schmidt, but that doesn't explain why Garvey's teammate Jimmy Wynn finished fifth in the voting (not to mention the Pirates, Reds and Cardinals in the above list).

Garvey batted .312/.342/.469 on the year, with 21 homers and 111 runs driven home. He did not lead the league in any category, though he was Top 10 in several. Here's my take on how he won the MVP: he batted over .300, knocked out 200 hits and had the highest RBI total of players on an NL playoff team (the other being the Pirates). That and the great hair, of course.

Did Garvey do anything in the non-hitting categories to boost his case and vault him over the better hitters in 1974? No, not really. Here are the numbers:

 --------------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
| Name                | Team | Batting | Range | Arm | BsRn | GIDP | Position | WAR  |
 --------------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
| Garvey_Steve        | LAN  |      29 |     0 |   0 |    3 |    2 |      -10 |  4.8 | 
 --------------------- ------ --------- ------- ----- ------ ------ ---------- ------ 

I don't think of Garvey as a speedster, but he was above average in the speed categories of baserunning and avoiding double plays. He was average in defensive range and arm (although he was famous for having a very weak arm), but he takes a -10 run hit for playing first base. An overall WAR value of 5 is nothing to be ashamed of, but Garvey was not among the ten most valuable National League players in 1974:

 --------------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
| Name                | Team | Batting | Range | Arm | BsRn | GIDP | Position | WAR  |
 --------------------- ------ --------- ------- ----- ------ ------ ---------- ------ 
| Schmidt_Mike        | PHI  |      49 |    17 |   1 |    1 |    2 |        4 | 10.0 | 
| Morgan_Joe          | CIN  |      46 |     3 |   1 |    8 |    1 |        4 |  8.8 | 
| Wynn_Jimmy          | LAN  |      47 |    12 |   2 |   -1 |    2 |       -2 |  8.4 | 
| Bench_Johnny        | CIN  |      32 |    11 |  -1 |   -1 |    0 |        9 |  7.5 | 
| Evans_Darrell       | ATL  |      18 |    18 |   2 |    2 |    1 |        4 |  6.8 | 
| Stargell_Willie     | PIT  |      46 |     1 |   1 |   -2 |    0 |       -7 |  6.2 | 
| Rose_Pete           | CIN  |      18 |    15 |   5 |    4 |    1 |       -9 |  6.0 | 
| Smith_Reggie        | SLN  |      40 |     8 |   0 |   -2 |   -3 |       -7 |  5.7 | 
| Cedeno_Cesar        | HOU  |      20 |     4 |   4 |    7 |    1 |       -2 |  5.7 | 
| Oliver_Al           | PIT  |      28 |     6 |  -4 |    6 |   -3 |       -4 |  5.2 | 
 --------------------- ------ --------- ------- ----- ------ ------ ---------- ------ 

Wow, look at the fabulous season that Mike Schmidt had. Best hitter in the league, one of the best defensive players and above average in all the other categories. Achieving a WAR of 10 is no small feat: it has only been done 36 times since 1955.

The fantastic thing about having this WAR database (did I thank Sean for this yet?) is it makes clear just how some very good players end up getting underrated, because a lot of their value comes in the non-hitting categories. Jimmy Wynn, Darrell Evans and arguably Cesar Cedeno fall into this group. Wow, just noticed that Pete Rose had a great year with the glove in 1974.

In case you were wondering, Steve Garvey ranked 14th in WAR in the NL in 1974.

-------------------------------------------------------------------

So, I hope I have given you a flavor for just how useful Sean's WAR database really is. You could use it to answer many, many questions, of course. Which players are underrated because much of their value is in the non-hitting categories? Which players were the most well-rounded or one-dimensional? Who had value because of speed and who despite of a lack of it? Or let's talk about teams: The 1985 Cardinals stole 314 bases — how much impact did their baserunning have on their offense? Were they the best baserunning team of the last half-century? Who were the best defensive teams and the worst?

Oh, the mind reels at the possibilities. All the numbers are there, waiting to be looked at. Thank you, Sean.

John Walsh is a regular contributor to the Hardball Times. He welcomes comments via email.

Permalink | Comments (4)

Perhaps the widest and deepest pitfall lying in wait for any who deal in numerical analyses is forgetting the distinction between precision and accuracy. If I state that Team X's opening-day first pitch was delivered at 1:07:32 pm, I am being quite precise; but if in fact it was a night game, then the statement that the pitch was made sometime between 7:35 and 7:40 pm, though far less precise, is far more accurate.

It is all too easy to be hypnotized by the ability to calculate some metric to a large number of decimal places into believing that such precision equates to accuracy. As a case in point, let us look over the concept of "park factors". It is undoubtable that ballparks influence the results that players achieve playing in them, and in many cases--"many" both as to particular parks and as to particular statistics--those influences are substantial. Park factors are intended as correctives, numbers that ideally allow inflating or deflating actual player or team results in a way that neutralizes park effects and give us a more nearly unbiased look at those players' and teams' abilities and achievements. So much virtually everyone knows.

The idea behind the construction of park factors, stated broadly, is to compare performance in a given park with performance elsewhere. As an example, a widely used method for educing park factors for a simple but basic metric, run scoring, is the one used by (but not original to) ESPN. The elements that go into it are team runs scored (R) and opponents' runs scored (OR) at home and away, and total games played at home and away.

           (Rh + ORh) ÷ Gh 
  factor = ───────────────
           (Ra + ORa) ÷ Ga

That comes down to average combined (team plus opponents) runs scored per game at home divided by the corresponding figure for away games. Let us see what some of the things wrong with that basic approach are, and if we can improve on it.

A "park factor" is supposed to tell us how the park affects some datum--here, run scoring. Perhaps the most obvious failing of the ESPN method is made manifest by the simple question compared to what? In the calculation above, run scoring at Park X is being compared to run scoring at all parks except X. Thus, each park for which we calculate such a factor is being compared to some different basis: the pool of "away" parks for Park X is obviously different from the pool of "away" parks for Park Y (in that X's pool includes Y but excludes X itself, while Y's includes X but excludes Y itself). Now that rather basic folly can be fairly easily corrected for; let's call the average combined runs per game at home and away RPGh and RPGa, respectively. Then, if there are T teams in the league,

                        RPGh 
  factor = ───────────────────────────────
           {[RPGa x (T - 1)]   [RPGh]} ÷ T

But there remain considerable problems, the most obvious being that the pools are still not identical, in that schedules are not perfectly balanced: Teams X and Y can, and probably do, play significantly different numbers of games in each of the other parks. Even if we throw out inter-league data, which is especially corrupt owing to the variable use of the DH Rule, we still have differing pools for differing teams, at least by division (and possibly even within divisions, owing to rainouts never made up). Well, one thinks, we can see how to deal with that: we would normalize away data park by park, then combine the results, so the "away" pool would, finally, represent the imaginary "league-average park" against which we would ideally like to compare any particular park's effects.

Let us remain aware, however, before we move on, that there are yet other difficulties. We have been using the simple--or rather, simplistic--idea of "games" as the basis for comparing parks' effects on run scoring. But even at that level, there are inequalities needing adjustment, in that the numbers of innings are not going to be equally apportioned among home batters, away batters, home pitchers, and away pitchers, in that a winning team at home does not bat in the bottom of the last inning. There is also the further question of whether innings are the proper basis for comparison. For most stats, the wanted basis for comparison is batter-pitcher confrontations, whether styled PA or BFP. But there are complexities there, too. A batter's ability to get walked, or a pitcher's tendency to give up walks, might seem best based on PAs or BFPs; but higher numbers of walks mean a higher on-base percentage, which means that more batters will get a chance to come to the plate (it is that "compound-interest effect" of OBA that is often not properly factored into metrics of run-generation, individual or team: not only is the chance of a batter becoming a run raised, but the chance of getting that chance is also raised). That will increase run scoring in a manner that a metric measured against PAs will not fully capture. And there are yet other questions, such as whether strikeouts should be normalized to plate appearances or to at-bats.

But for our purposes here--getting a grand overview of the plausibility of "park factors"--such niceties, while of interest, can be set aside. Let's look at the larger picture. Let's say we want to get a Runs park factor for Park X. We have seen that we need to use normalized runs per game on a park-by-park basis if we are to avoid gross distortions from schedule imbalances and related factors. How might that look for a real-world example? Let's take, arbitrarily, San Francisco in 2008. Here are the raw data:

And here are the consequent paired raw factors:

But, because we have used a particular park for these figurings, all those numbers are relative to that park. What we want are numbers relative to that imaginary "league-average" park. For example, if we had chosen the stingiest park in the league, all the factors would be greater than 1; had we chosen the most generous, all the factors would be under 1. But all we have to do is average the various factors--in which process we assign the park itself, here San Francisco (I refuse to use the corporate-name-of-the-day for that or any park), a value of 1, since it is necessarily identical to itself--and then normalize the factors relative to that average. When we do that, we get what ought to be the runs "park factor" for each National-League park relative to an imaginary all-NL average park:

The average is not exactly 1.000 owing to rounding errors, but it's close enough for government work. If we sort that assemblage, it looks like this:

But before we jump to any conclusions whatever about those results, let's ponder this: they were derived from data for one park, one team. Yet, if the methodology is sound, we ought to get at least roughly the same results no matter which park we initially use. Imagine a Twilight-Zone universe in which the 2008 season was played out in some timeless place where each team played ten thousand games with each other team, yet still at their natural and normal performance levels as they were in 2008. Surely it is clear that we then could indeed use any one park as a basis for deriving "park factors" since, in the end, we normalize away that park to reach an all-league basis. In that Twilight Zone world, any variations from using this or that particular park can only be relatively minor random statistical noise. San Francisco is to Los Angeles thus, and San Francisco is to San Diego so, hence Los Angeles is to San Diego thus-and-so (in a manner of speaking). So what do we see if we try real calculations with real one-season data? Let's continue with the National League in 2008. Shown are the "park runs factors" for each park as calculated from each of the other parks as a basis. If the concept is sound, the numbers in each row across ought to be roughly the same. Ha.

Well, now we know something, don't we? This just doesn't work. But it's not the methodology. Nor is it the various minor factors we saw earlier: those don't produce 3:1 and greater spreads in estimation. No, what we are dealing here, plain and simple, is the traditional statistical bugaboo--an inadequate sample size. Here is a possibly instructive presentation: the averaged run-factor values from that table above compared to what the simplistic ESPN formula yields:

Instructive, indeed. The agreement is not perfect, as we would not expect it to be. The "average" column is a little better than the ESPN column because it allows better for the differing numbers of games on the schedule, but by using the average for each park of the values derived from all the other parks we are approximating the ESPN method.

The entire point of this lengthy demonstration has been to lift the lid off those nice, clean-looking, precise park-effect numbers to show the seething boil in the pot. The end results are not totally meaningless: we can say with fair credibility that San Diego's is a considerably more pitcher-friendly park than Colorado's, and that the Mets and the Marlins were playing in parks without gross distorting effects. But to try to numerically correct any team's results--much less any particular player's results--by means of "park factors" is very, very wrong.

But wait, there's more! (As they say on TV.) If the problem is a shortage of data, why not simply expand the sample size? Use multi-year data? That would be nice, and useful, were no park changed structurally over a period of some years. But consider: not even counting structural changes, in the last ten seasons (counting 2009), a full dozen totally new ballparks have come on line. When one considers that pace, plus the changes (some even to a few of those new parks), it becomes painfully obvious that trying multi-year data is as bad or worse. Even for a particular park that might itself not have been at all changed for many years, there remains the issue that the standard of comparison--that imaginary league-average park--will have changed, probably quite a lot, over that time, owing to changes in the other real parks. So we can't use multi-season values, and single-season values are comically insufficient for anything beyond broad-brush estimations, estimations more qualitative than quantitative.

I should point out that none of this is today's news. In 2007, Greg Rybarczyk at The Hardball Times noted that the home-run "factor" for the park in Arizona was 48 in one season and 116 in the next. Back in 2001, Rich Rifkin at Baseball Prospectus remarked that "Unfortunately, it is problematic to average out a park factor over more than a few years because the conditions of one or more of the ballparks in a league change. New stadiums are built, existing stadiums change their dimensions, and abnormal weather patterns have an impact." (Regrettably, the next sentence was "Nonetheless, a 10-year sample is likely to be more accurate than a one-year accounting.") Probably the defining essay on the subject is the 2007 paper titled "Improving Major League Baseball Park Factor Estimates", by Acharya, Ahmed, D'Amour, Lu, Morris, Oglevee, Peterson, and Swift, published in the Harvard Sports Analysis Collective. But, justifiably proud as they are of their improved methodology, even they concluded that "Unfortunately, the lack of longer-term data in Major League Baseball . . . makes it extraordinarily difficult to assess the true contribution of a ballpark to a team's offense or defensive strength."

Precisely accurate.

Eric Walker has been a professional baseball analyst for over a quarter-century. His paper "Winning Baseball", commissioned by the Oakland A's for the purpose, first instructed Billy Beane in the concepts later called "Moneyball"; Walker has also authored a book of essays, The Sinister First Baseman and Other Observations. Walker is now retired, but maintains the HBH Baseball-Analysis Web Site.

Permalink | Comments (13)

Back in 1988, in an attempt to make a little extra money during graduate school at UC Berkeley, I tried out to be an umpire for intramural softball. We were given a brief instruction on what to do and a mock game was set up as a tryout.


I was working first base and there was a grounder hit to the second baseman. I tried to remember where I was supposed to stand (about 15 feet behind the bag at a 45 degree angle to either side depending upon whether or not the throw was coming from the left or right side of the infield). The ball was hit... somewhere... and I ran to stand in position. Except I stood near the pitcher in the middle of the play. And then I tripped over my own feet and fell over. I found other part-time employment.



Bruce Weber, a New York Times reporter, had a bit more success when he visited the Jim Evans Umpire School back in 2005 and he ended up writing an interesting book about the lives of umpires, both minor and major leaguers, in his As They See 'Em: A Fan's Travels in the Land of Umpires (Simon and Schuster, $26).



Starting with the bizarre world of umpire school (one student's employer told him "they have a school for that?"), where prospective umpires are put through drill after drill to get them to see a game as an umpire does, instead of as a fan. Weber also has some interesting stories about how umpires are drilled in how to argue with managers and players, and even more importantly, how to take off their mask without having their cap fall off. The latter is extremely important it turns out, although if more umpires start using the hockey style masks, that arcane art may disappear.

Like players, umpires are taught where to position themselves and how to anticipate plays. The most common time you will see an umpire out of position is when a player does something completely unexpected, such as throwing to the wrong base. After all, if the player shouldn't throw to a certain place, why should they be in position to cover a situation caused by a player's mental error.



As Weber points out, umpires are part of baseball that has no constituency that likes it. Players and managers don't like umpires, and umpires like to call players "rats." Front offices don't like umpires. Even the Commissioner's Office, which employs umpires, really doesn't like them. Former Commissioner Fay Vincent says that teams view umpires like they were bases, just pieces of equipment that you have to have to play the game.



One of the hardest things Weber faced in writing his book was getting people to talk to him. Players and managers generally didn't want to speak to him because they feared payback from umpires. Even Earl Weaver, long out of the game, wouldn't speak to Weber about umpires. Umpires didn't want to speak too much out of turn because they feared for their job security.

Umpires who graduate at the top of their classes at one of the two umpire schools (Harry Wendlestedt operates the other one), are given jobs in Rookie or Short-season A leagues as parts of two-man crews who drive hundreds of miles between cities and stay in motels that often appear as if they have hourly rates. MLB views minor league umpiring as "seasonal work" so the pay is low, sometimes around $800 per month. It's a job you have to love somewhat because most people could make better wages at McDonald's.

For the privileged few who make it to the majors (there are 68 full-time MLB umpires), the job becomes even more tense. Every call is scrutinized and there is nothing positive that an umpire can do. They can only screw up.



Since an MLB umpire's job is so coveted, Weber could only get a few umpires to speak to him on the record and even some were not entirely forthcoming. The disastrous mass resignation plan of 1999 has left deep wounds among the corps of umpires. Interestingly, Weber points out that even though umpires were no longer separated by league at the time, the battle lines in that dispute split along AL-NL lines, with the AL umpires (who long felt that they were below the NL in the pecking order) taking the opportunity to assert leadership in a new union.

I found the best parts of the book when Weber goes into some detail about the mechanics of umpiring. It's one part of baseball that few people seem to care about, unless they think an umpire screwed up. Then people are experts on the matter.



For example, when there is a bunt play going on and the defense puts on "the wheel" play, watch the umpires. They don't move. They have to watch the bases. But if there is a ball hit down the left- or rightfield lines, the umpires will wheel around, while the infielders will generally stay by their bases to make a play on a runner or the batter-runner. (If you want to be an umpire, learn to say "batter-runner," "ball-strike indicator," and don't let anyone call you "Blue.") Umpires also have responsibilities to make sure that all the runners touch their bases and it's a subtle skill that they pick up over time.



Weber also gets umpires to explain how pitchers like Greg Maddux and Tom Glavine get seemingly wider strike zones than other pitchers. Briefly, it's because those pitchers have such good control that they can keep placing the ball further and further on the corner of the strike zone. And then they are able to work inside and outside the edge until the outside edge of the strike zone gets wider because of the umpire's perception of where the pitches go. Maddux and Glavine in a sense have earned bigger strike zones because of their skill, and not just because of their reputation.



One thing that did surprise me is how open umpires were to technological improvements in the game. Replay review of home runs was welcomed because the umpires know how difficult some parks were for making those calls. It's likely that in 2009, umpires will err on the side of calling a ball in play rather than a home run because it is simpler to remedy that call with replay rather than the other way around.



The final chapter of the book includes interviews with umpires who have made some of the most controversial calls in recent history: Larry Barnett (who didn't call interference on Ed Armbrister in the 1975 World Series, despite Carlton Fisk's protestations), Doug Eddings (of the 2005 ALCS call involving A.J. Pierzynski and Josh Paul and the dropped third strike), Richie Garcia (of Jeffrey Maier fame), Tim McClelland (who was the umpire for the George Brett Pine Tar Game and The Did Matt Holliday Touch The Plate Game), and Don Denkinger (1985 World Series Game 6, bottom of the 9th).

Each umpire gets a chance to explain what they did and didn't see or what they did or didn't do. Denkinger freely admits blowing the call on Jorge Orta, but explains how it came about. But that will likely not satisfy Cardinals fans. Some of them still want blood 24 years after the fact.



Weber wants fans to have a greater appreciation for the work that umpires do. The umpires are far from a perfect lot. They are profane. They are sexist (the few female umpires who have been in the minors were treated horribly). They aren't there to make the fans or players happy. They are at games to keep them under control. It's a job that not many people have the ability or temperament for. But those that do it, do care about doing their jobs well. Nevertheless, I predict plenty more complaining about umpires this year from just about everybody. It's one of baseball's constants.



From the benches, bleak with people, there went up a muffled roar,

Like the beating of the storm waves on a worn and distant shore.

"Kill him! Kill the umpire!" shouted someone in the stands,

And it's likely they'd have killed him had not Casey raised his hand.


- From "Casey at the Bat" by Ernest Lawrence Thayer, 1888

Bob Timmermann, formerly of The Griddle, is a senior librarian for the Los Angeles Public Library and runs One Through Forty-Two or Forty-Three.

Permalink | Comments (4)

[Editor's note: John Brattain, a writer for The Hardball Times, Baseball Digest Daily, and his own blog Ground Rule Trouble, and a sincere friend of Baseball Analysts, passed away on Monday due to complications from heart surgery. John, who is survived by his wife Kelly and two daughters, was 43 years old. Known as "The Bones McCoy of THT" at the Baseball Think Factory, his signature line was "Best Regards, John." In sympathy and as a tribute to John and his family, we present his guest column — a terrific piece about Robert Lee "Indian Bob" Johnson — from December 22, 2005. Best Regards, John. - Your Pals at Baseball Analysts.]

One of the great oddities in baseball is how we perceive players. If a player does one or two things spectacularly well, he ultimately ends up being better regarded than players who do a lot of things well. Of recent vintage was 1998 and 1999 when home run behemoths Mark McGwire and Sammy Sosa got all the ink over players like Barry Bonds and Ken Griffey Jr. Earlier in the decade in Canada RBI man Joe Carter had a higher profile than Larry Walker. Or, if you wish to go back to the 1970's and 1980's, you'll find more casual fans have heard of Dave Kingman over Dwight Evans.

For that matter, don't you find it odd that Tim Salmon never went to an All-Star Game? Not one.

Bill James said in his book Whatever Happened To The Hall of Fame--The Politics Of Glory that players who do one or two things well tend to be overrated while those who do a lot of things well tend to be underrated.

Today we're going to talk about an historically underrated player. He didn't have one ability that defined him but didn't have a single hole in his game: he could hit, hit with power, run, field and throw. Baseball-Reference has tests that involve Black Ink and Gray Ink. Black Ink describes how often a player led the league in some statistical category; Gray Ink describes how many times he finished top ten in the league. This player has two points of black ink but 161 points of gray ink.

In other words, he was never the best, but consistently among the best.

We're talking about Robert Lee "Indian Bob" Johnson.

Johnson was born in Oklahoma in 1906, and his family soon moved to Tacoma, Washington. He left home in 1922 at age 15 and began his baseball career with the Los Angeles Fire Department team. Because Johnson was part Cherokee, he was subjected to the nickname "Indian Bob," just as other players of Native American ancestry had similar epithets foisted upon them in this era.

Johnson was soon playing semi-professional ball. When his brother, Roy Johnson, became a professional, he felt buoyed. He said, "When Roy became a regular with San Francisco in 1927 I knew I could make the grade in fast company. I had played ball with Roy and felt I was as good as he was."

However, Johnson failed trials with San Francisco, Hollywood, and Los Angeles. He did not play professionally until Wichita of the Western League signed him in 1929. Johnson played in 145 games at two levels and batted .262 with 21 HR while slugging .503. After again hitting 21 HR (in just over 500 AB) the following season in Portland, he went to spring training with the Philadelphia A's but didn't make the roster due to his inability to hit the curveball. Over the next two seasons in the minors, Johnson batted a combined .334 with 51 HR while slugging .567 and showing both patience at the plate and a powerful throwing arm in the outfield.

Opportunity knocked in 1933 as Connie Mack sold off veteran Al Simmons to the White Sox leaving Johnson and Lou Finney to battle for the leftfield job in spring training. Johnson won the job and had an excellent freshman season at age 27...

 AVG/ OBP/ SLG  Runs 2B 3B HR RBI OPS  RCAA
.290/.387/.505  103  44  4 21  93  134   37

...and was generally considered the league's finest rookie.

Johnson would quickly prove that 1934 was no fluke. On June 16th, the A's and White Sox played a twin bill. After losing the opener 9-7, the A's come back to win game two 7-6. Johnson went 6-for-6 with two home runs (both off Whit Wyatt), a double, and three singles. Four days later, he hit his 20th round tripper of the season against the Browns giving him the league lead (he finish fourth). He also enjoyed a 26-game hitting streak. After two fine seasons, Johnson was beginning to get recognition as he was named the starting left fielder of the American League All Star team in 1935. Johnson also finished fourth in the loop in home runs for the third time in his first three seasons and enjoyed his first 100 run/100 RBI season (he had topped 100 runs in both 1933 and 1934).

Despite turning 30 in 1936, Johnson kept right on raking and showed a little extra speed on the base paths, hitting a career high 14 triples. In both 1936 and 1937, he ripped 25 HR driving in 100 runs despite not getting 500 AB in '37; of interest, on August 29 he again victimized the White Sox in a doubleheader as the A's set a new AL record in the opener of a twin bill by scoring 12 runs in the opening frame, six of which were driven in by Johnson. After four years in the majors, other aspects of Johnson were becoming known around the league. Johnson was a bit of a practical joker, and it was in 1937 when Yankees' HOF second baseman Tony Lazzeri pulled a prank on him, knowing he would probably appreciate the joke.

Lazzeri doctored a ball over the course of two weeks by pounding it with a bat, soaking it in soapy water, and rubbing it extensively with dirt and finally coating it with white shoe polish to make it look like new. Bill James described it as a ball that was "as dead as Abe Lincoln." It was so heavy and lifeless that it would plop down harmlessly once struck with a bat.

Lazzeri sprang his joke on September 29 long after the Yanks had clinched the pennant. During an inning in which Johnson was due to bat, he ran out to second base with the gag ball in his pocket. When Johnson stepped into the batter's box, he trotted out to the mound and switched balls with Yankee southpaw Kemp Wicker. Wicker grooved Lazzeri's "mushball" down the pipe and Johnson took a mighty cut and hit it on the screws. However, rather than hitting a prodigious moonshot, the ball plopped harmlessly foul behind the plate while a perplexed Johnson stood there wondering just what the hell happened while the other players and the crowd burst into laughter.

Johnson continued to get better as he aged as he put together his best two seasons at 32 and 33, topping 110 runs/RBI both years while batting at least .300/.400/.500. On June 12, 1938, Johnson was a one-man wrecking crew against the St. Louis Browns, hitting three bombs (and a single) and driving in all eight runs.

1938 and 1939

 AVG/ OBP/ SLG  Runs  2B 3B HR RBI OPS  RCAA
.325/.422/.553  229   57 18 53 127  146   95

Johnson was also developing the reputation of being an athletic fielder. He lead the AL in assists twice (in The New Bill James Historical Baseball Abstract, the best outfield arm of the 1940's is said to be either Johnson or Dom DiMaggio and he was also 4th all-time in outfield assists per 1000 innings) and also filled in occasionally at second and third base (poorly it should be added). He was named to the AL All-Star team both years.

Johnson finally began to show the effects of age during his age 34 and 35 seasons and started to lose some bat speed. Connie Mack even felt the need to give his star slugger time off from covering the expansive left field pasture at Shibe Park, playing him 28 games at first base in 1941. He still had power and a sharp batting eye and remained a potent RBI man, topping 100 RBI in both 1940 and 1941--the latter his seventh straight season over the century mark.

Johnson's power started to wane in 1942 as he suffered through his worst season statistically to that point in time, failing to hit 20 HR or 90 RBI for the first time in his career. However, part of this was attributable to the fall of offense across the board due largely to players enlisting in the military for WWII. His OBP and SLG marks were still good for top 10 finishes in the Junior Circuit and good for fifth in MVP voting. After continually clashing with Mack over pay, the manager finally said goodbye, sending him to the Washington Senators for third sacker Bob Estalella and Jimmy Pofahl. Baseball Almanac notes that this was the only time in baseball history where a player who led his team in RBI for seven straight years was traded.

Johnson lasted one year with the Senators where age and huge Griffith Stadium all but neutered his power as he slugged a career low .400, and for the first and only time in his career he failed to hit at least 10 home runs (7). He was sold to the Boston Red Sox by Griffith who later regretted the move. The diluted war-time talent in the majors coupled with Fenway Park's hospitable climate for right-handed hitters allowed Johnson to finish out his major league career in style. In a season which either spoke highly of Johnson's ability at age 38 or spoke poorly of the level of war-time talent left in the majors by 1944--*cough* Browns win the pennant...Browns win the pennant *cough*--Johnson enjoyed his finest statistical season (including hitting for the cycle on July 6):

 AVG/ OBP/ SLG  Runs  2B 3B HR RBI OPS  RCAA
.324/.431/.528   106  40  8 17 106  174   61

Still, a lot of other fine players also played through the war years including HOFers Paul Waner, Chuck Klein, and Joe Medwick and didn't play as well as Johnson. Further, he was able to play 142 games in left field and enjoyed his first season on a team .500 or better since his rookie year as the Red Sox finished 77-77. For his efforts he was named to his seventh All Star team and finished 10th in MVP voting. As World War Two dragged on to 1945, Johnson was able to enjoy one last moment in the major league sun. He played 140 games in left field and provided the Red Sox with 82 runs created (AL left fielders averaged 67 RC in 1945), which earned him his eighth and final All Star nod. With the war over, Johnson pushing 40, and the return of Ted Williams, the Red Sox and Johnson parted company and he continued his career with the Milwaukee Brewers in the American Association.

Despite his advanced athletic age, Johnson managed to hit .270 with 13 HR and a .456 SLG in 94 games. He moved on to Seattle of the Pacific Coast League for the next two years, batting .292 with 35 doubles, 12 HR and a .441 SLG in 487 AB. Johnson, now 44, went home to play for and manage the Tacoma Tigers in the Western International League where he wielded a potent bat, hitting .326 with 13 doubles, five homers and a .463 SLG in 218 AB. He didn't play in 1950 but resurfaced briefly in Tijuana the following year at age 46. Johnson batted .217 in 21 games, then hung up his spikes for good.

So how do we measure Johnson's career? He probably missed being a Hall of Famer by a whisker. Johnson was hurt perceptually due to playing on second-division teams never reaching the World Series or even coming particularly close to one. He was also overshadowed by all-time great outfielders like Joe DiMaggio and Williams. Further, he finished his career during the second World War. Also working against him was his consistently high level of play; his OPS never going higher than 174 or dropping below 125 and always provided above-average offense for his position. He never had an eye-popping, jaw-dropping season that nets players MVP awards. He is also perceived by many to be the equivalent of the Phillies fine outfielder of the 1940's and 1950's, Del Ennis.

In short, he was invisible.

However, when we examine his record, he fits right in with four contemporary outfielders who are in the Hall of Fame and three of whom--like Johnson--finished their careers during WWII: Earl Averill, Klein, Medwick, and Paul Waner.

Player              AVG   OBP   SLG Runs   HR  RBI  OPS  RCAA* 
Bob Johnson        .296  .393  .506 1239  288 1283   138  413 
Earl Averill       .318  .395  .533 1224  238 1164   133  391 
Chuck Klein        .320  .379  .543 1168  300 1201   137  409 
Paul Waner         .333  .404  .473 1190  139  957   134  588**
Joe Medwick        .324  .362  .505 1198  205 1383   134  368 
Del Ennis          .284  .340  .472  985  288 1284   117  145

* Runs Created Above Average is a counting stat
**Waner's career length is the longest of the six players

As mentioned, a lot of folks dismiss Johnson's achievements because of a superficial statistical similarity to Del Ennis. I threw Ennis in here to show that he's not at all comparable to the above group. His HR/RBI totals are similar but he's last in AVG/OBP/SLG, runs, OPS and RCAA. The difference between Johnson and Ennis' respective levels are about the same as Rusty Greer (120 OPS /149 RCAA) and Chipper Jones (141 OPS /429 RCAA); nobody suggests that Greer and Jones are similar as hitters. In the chart above, we can see how close Johnson's level of play was to Hall of Fame quality. His eight All Star selections reflects the high regard contemporaries viewed Johnson. After Al Simmons was sold to the White Sox, Johnson all but became the Athletics offense. During his ten years with the A's, the team created 7612 runs. Johnson was responsible for 1162 (15.26%). The roster over that ten years were -420 RCAA while Johnson had 317 RCAA.

Although never topping statistical lists, Johnson was consistently among the leaders. From the period 1930-50, Johnson was tied for second in doubles (396), eighth in triples (95), third in home runs (288), third in runs (1239), second in RBI (1283), sixth in OBP (.393), sixth in SLG (.506), and fifth in OPS (.899). Here are the top ten finishers in RCAA (totals accumulated before 1930 and after 1950 are not counted):

1.    Ted Williams                908   
2.    Joe DiMaggio                695   
3.    Babe Ruth                   460   
4.    Bob Johnson                 413   
5.    Charlie Keller              394   
6.    Earl Averill                356   
7.    Tommy Henrich               274   
8.    Jeff Heath                  261   
9.    Al Simmons                  250   
10.   Roy Cullenbine              215

Johnson's RCAA is 73rd all time. When you consider that, along with being a fine fielder with a terrific throwing arm, you begin to appreciate the complete package that was Robert Lee "Indian Bob" Johnson. Truly an All Star in the fullest sense of the word and an unappreciated talent. When you look back at some of the superb players to grace the diamond in the 1930's and 1940's, don't forget about the man that patrolled left field at Shibe Park for a decade.

John Brattain writes for The Hardball Times and his work has been featured at About.com, MLBtalk, Yankees.com, Replacement Level Yankee Weblog, TOTK.com, Bootleg Sports, and Baseball Prospectus.

[Additional reader comments and retorts at Baseball Primer.]

Permalink | Comments (6)

One option would be to stay away from the games, to stop caring altogether. Another would be to wallow in the hangover of 99 losses and declare all decisions a disaster before they are even conceived, let alone executed. The more radical among you might prefer simply to enjoy a fine day at the ballpark and the respite it brings from more mundane concerns.

Losing sucks, but it beats going to work.

Enough with the pep talk. What's actually happening with the Padres?

There is a theory, backed by data, that Petco Park significantly benefits pitchers. There is another theory that every theory breaks at some point. Well, maybe; I just made that up. The important point is that the current staff is going to crank every faucet in the house at the same time and see if the pipes hold. But it won't be a one-time test; it'll be a way of life.

If you like offense, you go to Coors Field. If you like pitching, you go to Petco Park. If you can't figure out what the heck you like, try watching the Padres this year. Ask yourself exciting philosophical questions such as, "How bad can a pitcher be and still derive benefits from that ballpark?" Perhaps the environment -- when inhabited by the likes of Cha Seung Baek, Kevin Correia, and Josh Geer -- will collapse. It could be that both Petco Park and the rotation will be annihilated when they collide. I'm not saying it's likely, but you have been warned.

Silk Print Shirts and Bowlers

On the bright side, Jake Peavy and Chris Young are still here for now. Peavy is very outspoken and Young is very tall. If baseball doesn't work out for them, they would make a great comedy team. I have visions of Peavy cracking wise and Young playing the straight man. Maybe they could solve murder cases together and have a boss who can't abide by Peavy's behavior but who can't afford to part with him either. Peavy would wear silk print shirts and Young would don a bowler. Wackiness would ensue, probably over some minute misunderstanding.

Meanwhile, the bullpen is going to get a lot of work. That is thrilling if your name is Chris Britton or Mark Worrell, and you've always wanted to pitch in the big leagues. It is thrilling also if you are a fan. I am obligated here to mention that an old definition of "thrill" is "To perforate by a pointed instrument; to bore; to transfix; to drill."

I didn't say it would be fun. I said it would be thrilling.

Amusingly, and a point that is missed by many, the strength of this team will continue to be the offense. It will be disguised by Petco Park, of course, but Brian Giles will get on base, Adrian Gonzalez will mash, and Chase Headley will have worked through his awkward phase -- at the plate, at least; defense is a different story. Pray for everyone's health when the ball is hit his way. It may not help, but at least you'll feel proactive.

Like a Slow Corey Patterson

Kevin Kouzmanoff puts another theory to the test. Seven men have struck out 130 times or more in a season while drawing 25 walks or fewer (arbitrary points, but you get the idea):

Bo Jackson, 1988, age 25: .246/.287/.472, 25 BB, 146 SO
Cory Snyder, 1989, age 23: .215/.251/.360, 23 BB, 134 SO
Alfonso Soriano, 2002, age 23: .300/.332/.547, 23 BB, 157 SO
Corey Patterson, 2002, age 22: .253/.284/.392, 19 BB, 142 SO
Jeff Francouer, 2006, age 22: .260/.293/.449, 23 BB, 132 SO
Kevin Kouzmanoff, 2008, age 26: .260/.299/.433, 23 BB, 139 SO
Carlos Gomez, 2008, age 22: .258/.296/.360, 25 BB, 142 SO

We can learn two things from this: First, do not name your kid Cor(e)y. Second, it's easier to get away with these things if you have football in your hip pocket as a backup plan. Sorry, did I say hip? My bad.

Oh, you were looking for a useful lesson. Okay, here's one: If you are not Alfonso Soriano, don't attempt this strategy.

The stupid part is I actually think Kouzmanoff can hit. But that's just from watching him; the numbers make my head explode. It's like the tired old saw, "I need that like I need a slow Corey Patterson." And if that isn't a tired old saw, it should be.

Irresistably Immovable

The shenanigans aren't limited to on-field activities either. Matt Vasgersian hopped in his El Camino of the Imagination (with apologies to Carl Sagan and anyone who lives in Missouri) and schlepped off to Jersey to do the MLB Network thing.

Ownership is changing hands as we speak. John Moores, who once rescued San Diego from Roseanne Barr's former boss, is now being rescued by Manny Ramirez's former agent. As they say, the dreams in which I'm dying are the best I've ever had.

Payroll isn't expected to change. Neither is fan cynicism or disinterest. Weather will continue to be numbingly benign, and most of us will have our health. One hundred losses is a possibility, as is a World Championship. Other possibilities include, but are not limited to:

• Completing a triathlon
• Winning the lottery
• Flying to the moon
• Getting trapped in an oil painting

Be ready. Lack of preparation is not an excuse.

Still, I find the irresistible/immovable nature of this year's pitching staff at Petco Park... irresistible. Hey, we all have our perversions -- some are more interesting than others.

I want to see how far a Geer fastball will travel in that ballpark. I want to watch Headley ride around on his unicycle in left field. I want to bask in the glow of my own delusion.

I want to hang out and enjoy the games, no matter how hard anyone tries to kill my buzz with their so-called "reality." Is that so much to ask? Well, is it?

Geoff Young covers the San Diego Padres at Ducksnorts, and is a regular contributor to Baseball Daily Digest and Hardball Times. He has written three books about the Padres, the most recent being the Ducksnorts 2009 Baseball Annual, published in March 2009. Geoff lives in San Diego with his wife and two dogs.

Permalink | Comments (5)

Last week, we looked at how we can interpret groundball averages and what they tell us about the defensive overshift. Now, we'd like to examine some of the more interesting points in our dataset. Of all left-handed batters with at least 200 grounders since 2002, who had the most success with the worm-burner?

The chart is sorted by groundball average, which for lefties averages out around .225-.230. It is followed by expected groundball average based on pull-to-opposite-field-groundball ratio, speed score, percentage of groundballs to center field, homers per ball in air, and bunts per plate appearance.

Fred Lewis is quite the ballplayer. He has one of the top speed scores in our sample, and according to Pizza Cutter’s speed scores, he was one of the top 35 fastest players in the game last year. But he makes the most of his abilities. Not only can he leg out grounders, but by advanced metrics, he’s an above average left-fielder and baserunner. He stretches hits into triples and is willing to draw a walk to boot. Just wanted to make that observation before we get to...

Land of the Rising GBAVG

Ever notice that all four current Japanese Major League regular position players bat left handed? Though Ichiro Suzuki, Akinori Iwamura, Hideki Matsui, and Kosuke Fukudome all slugged at least 95 points higher in Japan than they have in America, there is one department in which they presumably haven’t suffered since coming overseas. All four players have a strong propensity to reach base via the groundball. Iwamura, Ichiro, and Fukudome all show up on the top 10 list, while Matsui checks in with a .246 groundball average, impressive considering his affliction going the other way. Calculating the difference between their groundball average, and their “expected” groundball average, all four come up in the 20 most “lucky” hitters. However, we wouldn’t attribute their success to luck at all. Ichiro is famous for his unique swing, in which he opens his bottom half and basically is halfway down the line by the time he makes contact. Could this be a method that is taught in Japan? If so, it would probably give someone a much better chance than other lefties of reaching base on grounders. Looking at cherry-picked at-bats, we can say that Iwamura, Matsui, and Fukudome all at times follow similar approaches.

We can estimate that without this skill, over the observed years, Iwamura would have a .260 batting average instead of .280, while Ichiro would be a .310 hitter instead of .330, Matsui .285 instead of .295 and Fukudome .245 instead of .255. This is a remarkable ability. It would be difficult to quantify, but perhaps teams can start timing how long it takes for a batter to get to first following contact. While Matsui has yet to bunt in his career, Ichiro, Iwamura, and Fukudome all get hits on over half their bunt attempts. Perhaps in Japan they emphasize getting down the line, and perhaps in America they should start looking into that. (Cough, Manny, Cough.)

The players we've looked at so far all make the most of their speed and groundball opportunities. But who doesn't? Without further ado...

The Willie Mays Hayes All-Stars

“You gotta stop swingin’ for the fences though, Hayes. All you’re gonna do is give yourself a hernia. With your speed you should be hittin’ the ball on the ground, leggin’ ‘em out. Every time I see you hit one in the air, you owe me twenty pushups.” --Lou Brown (Major League)

Disclaimer: It would be quite a rare instance to find a player who would actually benefit from hitting more grounders than flyballs. We suggest referencing The Hardball Times Baseball Annuals to find specific run values for players' different batted ball types. These are simply players who do a great job reaching base on grounders but fail to do so often.

Chone Figgins: From the right side, it’s acceptable that he doesn't hit many groundballs. Batting righty, he has hit only .230 on grounders over the last six years, while he is also more likely go earn a hit when he gets underneath the ball from that side of the plate than when he does so from the left side. Meanwhile, Figgins not only bats a robust .290 on grounders from his left side but is also very successful bunter. So when Figgins swings for the fences with his career .100 ISO from the left-handed box, know he might be better off legging out grounders.

Iwamura: Aki may have been a 30 homerun a year hitter in Japan, but not anymore, as he is twice as likely to have his groundballs go for hits than his fly balls. His homerun per flyball ratio has decreased to 3.7% this year, and the average true distance of his homeruns has gone down nearly ten feet as well, according to hit tracker. But he’s still a monster when he puts the ball into the turf, except he does so at only a league average rate.

Mark Bellhorn is the final player on this list, and oddly, another 2b/3b combo. Bellhorn may never get another cup of coffee, so it is likely too late for him to change his approach. But it warrants mentioning that he's always been underappreciated in his career due to his strong secondary skills, and he's been able to compile a nice groundball average despite a low groundball percentage.

Curtis Granderson and Brian Roberts could also be on this list, except that they're able to hit however they please and remain successful. Both players hit balls in the air almost twice as often as on the ground, though they hold solid career GB averages in the .265-.275 range. But Roberts consistently hits for decent power, and while Granderson has been excellent at reaching base on ground balls all four full years of his Major League career, he has done a good job of decreasing his groundball percentage as his power has increased--perhaps a conscious decision. Take a look at these graphs:

Follow the green lines. As his groundball percentage decreases, his production as measured by wOBA has increased. Though he hit .305 on grounders this year, putting the ball on the ground actually hurt his overall line it appears. He's a better hitter when hitting fewer groundballs, or he hits fewer groundballs to be a better hitter. Either way, he's done a great job improving at the plate

Taking a quick look at righties who weren’t in our dataset: Over the last three years, the only player to have popped up 20% of his fly balls was Eric Byrnes, with a 25.2 infield flyball percentage. As one of the faster players in the game, he could probably use to hit a few more grounders, and he has hit .296 on them since 2002. Carlos Gomez has a similar batted ball profile to that of Byrnes, except without the same type of pop, so he'll either want to develop some muscle or stop racking up 140 strikeouts with a .360 SLG when he might be better off at times pounding the ball into the ground and beating out the throw.

On the reverse end, grounders have been death to Mark Sweeney, Casey Kotchman, and Russ Adams, to the tune of a sub-.200 average, yet they still hit more balls on the ground than in the air.

That's it for our findings on batted ball data. Big thanks to FanGraphs and BillJamesOnline for making this type of data available. And we'd also like to express our deepest gratitude to Rich Lederer for hosting our research.

Leanne Brotsky, David Estabrook, Jeremy Greenhouse, Kimberly Miner, and Steven Smith assisted in writing this article. We would also like to thank Evan Chiachiaro and Dan Rathman, and Anthony Doina who participated in Baseball Analysis at Tufts’ research committee. Any questions can be directed to TuftsBAT@gmail.com.

Permalink | Comments (8)

A couple of weeks ago, Rich Lederer asked what variables account for extraordinarily low groundball out rates. So, using a similar method to that which Peter Bendix and Chris Dutton used to find expected BABIP, we dug deeper and ran a regression to find expected average on groundballs.

Intuitively, one would think that faster players with the ability to find holes in the infield have the best success rates on groundballs. As Lederer pointed out, defensive alignments and batter handedness are also variables that will affect groundball average. While infield shifts are difficult to quantify, we still attempted some statistical approaches to analyze their effects. And to account for handedness, we limited our sample to only left-handers or switch-hitters batting lefty. Our sample included 206 players with at least 200 total ground balls since 2002. We then ran a linear regression to find the factors that influence a batter's groundball average.

Five variables were significant at a one percent level in our regression—a ratio of pulled groundballs to opposite field groundballs, the percentage of grounders hit to center field, a speed score developed by Bill James, bunt hits per plate appearance, and homers per ball in air. The R-squared is .4648. Here is the regression output, if you're into that sort of stuff.

The location of groundballs along with the batter’s speed seem to have the most influence on groundball hit rate, confirming our suspicions. Hitting the ball the other way forces a longer throw, and busting it down the line on grounders is probably the most advantageous way a player can utilize his speed. Velocity of groundballs was difficult to account for. Line drive percentage and grounded into double play percentage, which are likely tied with the hardness of a groundball hit, proved insignificant. Many of you might know the split in batted ball hit average is about .715 on liners, .235 on grounders, and .140 on fly balls. Now, we can break that down further with this data. Lefties hit for a lower average on grounders than righties by about 10-15 points. Opposite field grounders and grounders up the middle from lefties go for hits on average about 30% of the time, while pulled grounders go for hits only 15-20% of the time. Interestingly, hitting homeruns has a negative impact on pulled and total groundball average, but is one of the most significant positively correlated variables that go into opposite field average. One guess is that power hitters tend to hit weaker groundballs to the right side when they roll over their wrists. Or perhaps they pull the ball into a shift, which seems to be supplied only to power hitters due to a likely managerial bias. But when these homerun hitters do hit opposite field groundballs, however rarely, they are apparently more likely to go for hits than opposite field grounders from slash hitters.

One of the main reasons we calculated our expected average value was to examine the exaggerated infield shift more closely. In our sample, we came up with nearly 20 players who we believed to have been “overshifted,” a defensive alignment in which the shortstop plays on the second-base side of the bag and the second-baseman goes to short right field. The shift was originally introduced as a way to get Ted Williams out, and it was brought back in vogue to foil Barry Bonds. By comparing a player’s expected average with his actual average, and using several more basic methods, we were able to draw conclusions about the use of the shift. An average significantly greater than the corresponding expected average indicates that our regression model does not account for something affecting the hitter – maybe a defensive shift.

The players whose expected groundball average most exceeded actual groundball average were Barry Bonds, Rafael Palmeiro, Mark Teixeira, Adam Dunn, and Jack Cust. Their averages all fell at least 20 points below their expected averages, while Jack Cust’s came up almost 30 points short. With this information, we looked at their traditional BABIPs with men on base and nobody on base as a loose measure to determine when these batters are being shifted, and when they’re not. We should note that the average BABIP with men on is slightly higher than with nobody on, and for pull-hitting lefties, there will be an even greater difference as the first baseman will often have to hold on a runner, opening up the hole between first and second base. Bonds, Palmeiro, and Cust all gained at least 30 extra points of BABIP with men on, and Bonds had a .265 BABIP with nobody on and .338 with men on. Dunn showed little split, while we could not isolate Teixeira’s situational left-handed at-bats from his right-handed at-bats. All of these players pull their groundballs at least six times as much as they hit grounders to the opposite field, and they all have slow speed scores, making them prime candidates to be victims of the shift.

Other players who get shifted and who have averages below their expected averages include: Prince Fielder, Justin Morneau, Mike Jacobs, and Jason Giambi. Giambi’s BABIP has been an astounding 95 points higher with men on than with nobody on.

What was almost as interesting was the list of shifted players whose average exceeds their expected average – potentially meaning the shift is not effective against them. David Ortiz, Carlos Pena, and Travis Hafner all fit into this category. There was no noticeable difference between skill sets of these player and the first group, so some other factors must explain this difference. Perhaps this second group includes hitters who are better at locating their hits against the shift. Ortiz does have a split of 45 points between his BABIP with men on vs. nobody on, so we won’t discount the impact of the shift on him.

Within this group of shifted batters, there were some other noteworthy discoveries. Ryan Howard has an incredibly high pull-to-opposite-field-groundball ratio of 11.875—the largest in our sample—yet his average and expected average were about equal, as both values fell within the .200-.205 range. Given his dramatic pull/opp ratio, we have little doubt that the shift has affected him, so we dug deeper to find the answer. Looking at the MLB.com provided hitting charts, and checking the locations of his groundball outs, there is a cluster of outs in short right field over the last two years, but not prior, meaning the decision to shift him might have been recent. Indeed, in 2005-2006, Howard hit .237 on grounders, and then when the shift came into play regularly in 2007-2008, he hit only .175 on grounders. Also notable were Hafner's and Morneau’s extremely low pull/opp ratios, which were 3.98 and 2.99 respectively. According to this statistic, neither player would be an obvious candidate for the shift – yet both are shifted, and as said earlier, it would appear that the shift is detrimental to Morneau. However, the 3-4 defense applied to Hafner never made much sense, as he has rather moderate pull-to-opposite-field-groundball and groundball-to-flyball ratios.

Finally, we looked for any left-handed batters with high pull percentages, who would therefore be good candidates for the defensive shift. Nate McLouth had a pull/opp ratio of 10.208, but his speed statistic is quite high, explaining why teams probably choose not to shift him. If you’re fielding balls in short right field, you won’t get a fast player out. Nick Swisher’s pull/opp ratio 10.92 yet teams do not shift him. Russell Branyan and David Dellucci are also strong candidates for a shift, but none of these players follow the hulking power hitter profile, so managers don’t think twice about creative ways to get them out.

We ran a logistic regression using a value of one if we had evidence that the player had been shifted and zero if not. It turns out that homerun-per-flyball and groundball-to-flyball ratios have been the most significant factors in determining what players get shifted. Bonds’ expected shift score was one, meaning that he is truly the prototype of shifted players. Pull percentage and intentional walks per plate appearance were also significant at a five percent level, but we believe that opposite field groundball rate should be taken into account as well. Evacuating that side of the infield against a hitter who hits any significant amount of opposite field groundballs is simply giving away hits, no matter how many pulled grounders get taken away. There is a clear managerial bias to shift power hitters, while not taking enough into account batted ball location.

Our study is not perfect. We found no good way to quantify the shift, which would allow us to distinguish between players who receive a full shift and those who receive a partial one, or those who are shifted all the time and those for whom only some teams put on the defensive shift. Nevertheless, our study shows some interesting results. By comparing expected ground ball and actual averages, we believe that the shift had the most significant impact on Bonds, Palmeiro, and Cust, and that it had a surprisingly little impact on batters like Ortiz and Pena. In addition, we suggest that Swisher might be a good candidate to shift, and we suggest that managers make decisions based on evidence rather than player reputation. These are only basic observations, yet they shed some light on the hard-to-quantify defensive shift.

Leanne Brotsky, David Estabrook, Jeremy Greenhouse, Kimberly Miner, and Steven Smith assisted in writing this article. We would also like to thank Evan Chiachiaro and Dan Rathman, and Anthony Doina who participated in Baseball Analysis at Tufts’ research committee. Any questions can be directed to TuftsBAT@gmail.com.

Permalink | Comments (7)

Oh, no, not another projection system! Why would someone want to join the logjam of current systems? In no particular order, we have ZiPS, CHONE, Oliver, Marcel, Bill James, PECOTA and no doubt some others I haven’t stumbled across (sorry). All of these systems are designed to tell us how MLB players will perform next season, but none of them can convincingly claim to be more accurate than all the rest. When I look at any particular player’s projections in the various systems, I see a lot of similarity, which makes me suspect there must be some degree of groupthink going on. I believe there is some potential to improve performance forecasting by doing something different.

In the following paragraphs, I will outline a system for forecasting using Hit Tracker, an aerodynamic model for flying baseballs that is well-known for providing accurate home run measurements. I can guarantee that the Hit Tracker system will be different. Better? I won’t be able to say for sure until the 2009 season is over.

Background: How We Forecast Now

Why is it so difficult to forecast a player’s performance accurately? One huge reason is that every one of the current systems for performance projection starts from a set of data — the player’s prior year’s "box score stats" — that is positively riddled with statistical noise (chief among these uncontrolled noise factors are the dramatic differences in ballpark configurations and playing conditions across the 2,430 games played in 30 different parks over the course of six months).

Let’s consider another familiar form of forecasting: weather. In the 19th century, after the invention of the telegraph, weathermen began to form their predictions by first learning the weather "upwind," and then adjusting those measurements to come up with a forecast. "How hot will it be tomorrow? Well, it was 85 degrees today in the state where our weather seems to be coming from, so we’ll start with 85 and then adjust it up or down according to our experience. It’s usually a little hotter there than it gets here, so let’s say 82 degrees…" They didn’t call them "city factors" back then, but they could have.

After computers became available in the mid-20th century, weathermen became meteorologists, and the process of forecasting weather has continued to become more involved and mathematical as the years have gone by. Contemporary meteorologists now monitor a much larger array of parameters, and they feed these lower-order parameters into elaborate computer-based models to arrive at predictions for the higher-order outcomes like temperature, or winds, or precipitation. Thanks to more accurate measurements, and more detailed models, weather forecasts are dramatically more accurate today than those of even only 10 years ago.

In my opinion, baseball forecasting systems resemble the "19th century weatherman" system described above: to forecast something, measure something (well, in baseball we should say "count" something) that has happened already, then adjust this number to predict what hasn’t happened yet. So, to predict a player’s home runs, for example, the starting point is always his prior year’s total for home runs (or perhaps a weighted total from several seasons). From this starting point, various adjustments are applied to arrive at a final projection. Never mind where those home runs were hit, or how far they flew, or how much help or hindrance the weather may have provided them. Just count and adjust.

Starting from last year’s total assigns an equal value to what may in reality be very different events. For example, Jeremy Hermida hit two radically dissimilar fly balls last year, each of which cleared the home run fence: first, a windblown 321 foot homer in San Francisco on Aug. 20th, and second, a 443 foot rocket in Miami on July 19th. In a game context, they count the same, but when we are trying to measure the likelihood of future home runs, we should acknowledge that the outcome of one of those fly balls (the short one) was entirely dependent on its ballpark and weather context, while for the other fly ball, the ballpark and weather were irrelevant to the outcome. The short fly ball could only have become a home run in a park with a very shallow RF fence like AT&T Park, and only with the help of a tail wind. The long one would have been a homer in every park major league baseball has ever been played in, in any wind short of a hurricane blowing towards home plate.

Any system that cannot recognize the difference between two events such as these Hermida home runs cannot hope to consistently generate highly accurate predictions. I don’t mean this as a criticism of anyone who has created a projection system, don’t get me wrong. But I do believe that those systems have reached the limit of their capabilities, with average errors of around 60-70 points of OPS, and any further refinement of these models will probably just chase the statistical noise around in circles.

Something Different

How can we get away from the practice of predicting future outcomes by using prior outcomes? I believe that the key is to consider the lower-level processes that lead to the final result of any particular batted ball. Some of these are the landing point of the hit, how hard the ball was hit, and the physical environment that the ball was hit in. For those batted balls where the physical environment is crucial (i.e. long fly balls), we need to measure the trajectory of the ball, the fence dimensions of the park, and the weather. For the rest of the batted balls, where the physical environment isn’t very important to the final result, we don’t need to.

In Hit Tracker, I have developed a method for analyzing the trajectory of long fly balls and projecting them into each of the 30 MLB ballparks for the purpose of generating a performance forecast. It is my hope that this system will yield more accurate performance forecasts.

How It Works: Steps in the Hit Tracker Forecasting Method

• Observe all long fly balls hit by a player in the past 1-3 years.
  • A long fly ball is defined as any ball the player hit that might have approached or cleared the fence, if hit in any of the 30 MLB ballparks in any reasonable weather conditions.
  • This very liberal standard is applied to ensure that all the long fly balls are captured. Having a few not-so-deep flies in the data set won’t cause any problems, because if a particular ball turns out to be a flyout in every park, this is equivalent to not including that ball in the analysis.
• Analyze each long fly ball in its actual weather conditions, to determine its launch characteristics (Speed Off Bat, Horizontal and Vertical Launch Angles, Spin).
• Note each long fly ball’s original result (2B, 3B, HR, Flyout, etc.).
• Project each long fly ball into each of the 30 MLB ballparks, in the average weather conditions for that ballpark (calculated over a 5-year period).
• Note the hypothetical result of each projected fly ball in each ballpark.
  • Balls that fly far enough to clear the fence are judged to be home runs.
  • Balls that hit the fence more than 8 feet above field level are judged to be extra base hits.
  • All other balls are considered to be "catchable," and are analyzed further using a range model.
  • The range model uses standard assumed initial positions of outfielders, a distance vs. time model for an average outfielder, the actual landing point of the ball and the time of flight of the ball to determine if the ball would have been caught.
  • An empirical method was used on approximately 1,000 actual fly balls to determine the 50/50 likelihood boundary between outs and hits, in terms of time and distance from the closest outfielder. This boundary is then used as the evaluation criteria for catchable balls: balls inside the range circle of any outfielder for a given time of flight are flyouts, and balls outside it are extra base hits.
• For each ballpark, count the net hits and bases for the long fly ball data set:
  • For each ball that was originally a hit, but projected as an out, give a -1 for hits and –X for bases (e.g. for a ball that was originally a short home run to RF in Yankee Stadium, but which projects to be caught in Fenway Park, give -1 hit and -4 bases.)
  • For each ball that was originally an out, but projected as a hit, give +1 for hits and +X for bases (e.g. for a ball that was originally a flyout to LF at Yankee Stadium, but which projects to hit the Green Monster in Fenway Park more than 8 feet up, give +1 hit and (usually) +2 bases.)
  • For each ball that was originally a hit, but which projects to be another sort of hit, give ± X bases (e.g. for a home run to RCF in Shea Stadium that projects to be an extra base hit in Citi Field, give -2 or -1 bases, depending on the speed of the runner, the location of the hit and the time of flight.)
• Apply the net adjustments to hits and bases for all the long flies to the player’s actual stats for the season in question. Calculate OBP/SLG with the adjustments. This becomes the player’s projection for that ballpark.
• For projections based on multiple years of long fly balls, apply appropriate weighting factors (e.g. 3-2-1) to the projections for each ballpark.
• Using the MLB schedule for the season of the projection, create a projection for the player as a member of each team by multiplying their performance averages in each ballpark by a weighting factor proportional to the number of games each team plays in each park.

Case Study: Manny Ramirez

To further illustrate the method, I am going to highlight some of the findings from the Hit Tracker Analysis of Manny Ramirez over the years 2006-08, and his forecast for 2009.

First and foremost, I hope Manny Ramirez re-signs with the Los Angeles Dodgers for 2009, because Dodger Stadium is an absolutely perfect place for him to hit. I am not saying it is perfect for everyone; in fact, Dodger Stadium is a difficult place to hit for average or below average hitters, because its fences are deep in the corners where lesser hitters typically place their home runs. I am saying that Dodger Stadium is perfect for Manny. Manny’s swing, particularly his phenomenal power to center and right-center field, is ideally suited for the dimensions and environmental conditions of Dodger Stadium. I described the unique layout of Dodger Stadium (deep corners, shallow alleys and center field) in detail in my article, "Hit Tracker 2008," which was published in the 2009 Hardball Times Annual earlier this off-season.

At the opposite extreme, Manny’s home from 2000 to the 2008 trade deadline, Fenway Park, has robbed him of a great number of home runs over the years, perhaps as many as 50, as well as many other extra-base hits. Fenway’s very deep right-center and right fields have turned many of Manny’s towering opposite field drives into outs, and its 37-foot high Green Monster has turned many of his blistering drives to left and left-center field into doubles (or even singles).

A popular image exists of the Green Monster adding lots of extra-base hits to a hitter’s total by turning shallow fly balls into wall-scraping doubles, but this hasn’t been the case for Manny: in the three seasons 2006-08, Manny only hit 6 doubles at Fenway that would have been outs at Dodger Stadium. Over the same period, Manny hit 23 flyouts, 5 doubles and 1 triple at Fenway that would have been home runs at Dodger Stadium.

In the first 4 months of 2008, Manny encountered a particularly bad run of luck with his deep fly balls; despite racking up 20 home runs during that time, Manny could have gotten a lot more. Here is a list of Manny’s deep fly balls for the Boston Red Sox in 2008 that were not actually home runs, but which would have been home runs on an average day in Dodger Stadium. Where the weather negatively impacted his fly ball to a significant degree, this is listed as well:

• April 2, 2008 at Oakland, 407 ft. flyout to deep CF, lost 11 ft. of distance from wind and temperature.
• April 5, 2008 at Toronto, 387 ft. double to LCF.
• April 8, 2008 at Boston, 395 ft. triple to RCF, lost 25 ft.
• April 11, 2008 at Boston, 361 ft. flyout to RF, lost 7 ft.
• April 17, 2008 at New York Yankees, 395 ft. flyout to CF, lost 3 ft.
• April 24, 2008 at Boston (7th inning), 383 ft. double to RCF
• April 24, 2008 at Boston (9th inning), 402 ft. flyout to CF
• May 5, 2008 at Detroit (2nd inning), 415 ft. double to RCF
• May 5, 2008 at Detroit (3rd inning), 416 ft. flyout to CF
• May 6, 2008 at Detroit, 404 ft. flyout to LCF
• May 7, 2008 at Detroit, 402 ft. flyout to CF
• May 18, 2008 at Boston, 368 ft. flyout to RF, lost 9 feet
• May 19, 2008 at Boston, 386 ft flyout to CF, lost 11 feet
• May 23, 2008 at Oakland, 356 ft. flyout to RF, lost 6 feet
• June 4, 2008 at Boston, 364 ft. flyout to RF, lost 18 feet
• July 9, 2008 at Boston, 429 ft double to LCF off top of Monster
• July 19, 2008 at LA Angels, 378 ft double off RF wall
• July 27, 2008 at Boston, 410 ft flyout to RCF triangle
• July 30, 2008 at Boston, 367 ft flyout to LCF, lost 11 ft

Now, to be fair we have to look at the good luck Manny encountered during that same time frame. Here’s the list of Manny’s deep fly balls for the Boston Red Sox in 2008 that were actually home runs, but which would have not have been home runs on an average day in Dodger Stadium (there are 4):

• May 12, 2008 at Minnesota, 354 ft home run to RF
• May 27, 2008 at Seattle, 361 ft home run to RF
• June 1, 2008 at Baltimore, 382 ft home run to RF, got +23 ft help
• July 8, 2008 at Boston, 384 ft home run to LF, got +32 ft help

That’s a net of 15 balls hit by Manny in the first 4 months of 2008 that had the power to fly out of Dodger Stadium, but which didn’t make it out where Manny actually hit them. Watching the video of these hits, the disbelief and disgust on Manny’s face was apparent after several of his blasts came up short due to deep fences, cold/windy weather or a combination of the two. Once he was traded to LA, those balls started making it out at a much higher rate: Manny connected for 9 home runs in only 80 at-bats in Dodger Stadium in 2008.

Forecast: Manny Ramirez 2009

Manny’s forecast for 2009 is based on analysis of all 248 long fly balls he hit during the 2006, 2007 and 2008 seasons. In 143 games in 2009, Manny should continue to perform extremely well in a Dodger uniform: the Hit Tracker forecast projects him to post the following numbers:

Los Angeles Dodgers: .430 OBP, .641 SLG, 1.071 OPS and 36 home runs (including 21 at Dodger Stadium).

As of the posting of this article, Manny is still a free agent, so here are forecasts for some other teams Manny might sign with:

San Francisco: .428 OBP, .618 SLG, 1.047 OPS, 32 home runs.

NY Mets: .417 OBP, .566 SLG, .983 OPS, 26 home runs.

More Forecasts

Here are the Hit Tracker forecasts for several other MLB players. Some of the projections are based on three years of data (2006-08), while some are based only on one year of data (2008). The three-year forecasts are expected to be more accurate.

Forecasts Based on 2006-08 Data

Jason Bay, Boston Red Sox
Boston: .368 OBP, .501 SLG, OPS .869, 27 HR’s

Adam Dunn, free agent
LA Dodgers: .394 OBP, .587 SLG, .981 OPS, 47 HR’s
Washington: .389 OBP, .555 SLG, .944 OPS, 43 HR’s
NY Mets: .382 OBP, .506 SLG, .888 OPS, 35 HR’s
Atlanta: .387 OBP, .543 SLG, .930 OPS, 41 HR’s
Boston: .392 OBP, .549 SLG, .941 OPS, 39 HR’s

Forecasts Based on 2008 Data Only

Mark Teixeira, New York Yankees
New York Yankees: .420 OBP, .588 SLG, 1.008 OPS, 32 HR’s

Matt Holliday, Oakland Athletics
Oakland: .418 OBP, .563 SLG, .981 OPS, 28 HR’s
San Francisco: .426 OBP, .593 SLG, 1.019 OPS, 32 HR’s
Boston: .420 OBP, .557 SLG, .977 OPS, 25 HR’s
New York Yankees: .422 OBP, .584 SLG, 1.006 OPS, 32 HR’s
New York Mets: .417 OBP, .546 SLG, .963 OPS, 24 HR’s

Nate McLouth, Pittsburgh Pirates
Pittsburgh: .348 OBP, .484 SLG, .833 OPS, 29 HR’s

Validation

In an attempt to validate the Hit Tracker forecasting method, I analyzed the 2007 long fly balls of three players who changed teams during the 2007-08 off-season: Torii Hunter, Aaron Rowand and Jim Edmonds. Using this data, I projected their 2008 results as a member of the teams they ended up with, and compared to their actual performances in 2008.

Torii Hunter

HT Projection as Los Angeles Angel: .325 OBP, .485 SLG, .810 OPS, 25 HR’s
Actual as Los Angeles Angel: .344 OBP, .466 SLG, .810 OPS, 21 HR’s

Slightly off on the home runs, but overall a very good projection.

Aaron Rowand

HT Projection as San Francisco Giant: .373 OBP, .507 SLG, .880 OPS, 25 HR’s
Actual as San Francisco Giant: .339 OBP, .410 SLG, .749 OPS, 13 HR’s

This is terrible, but there is an explanation: on June 6th, Rowand sustained a right quadriceps injury that hindered him the rest of the year. His actual production splits are as follows:

Through June 6th: .396 OBP, .526 SLG, .922 OPS, 23 HR’s (pro-rated for a full year)
After June 6th: .303 OBP, .338 SLG, .641 OPS, 9 HR’s (pro-rated for a full year)

The HT projection matched the pre-injury Rowand reasonably well, considering the small sample size of about 1/3 of a season. Since the forecast was based on a relatively injury-free 2007 season, this is a fair comparison to make, I think. By the way, if anyone ever comes up with a way to predict the performance of a player who plays hurt through the final 96 of his 152 games, do me a favor: a) tell me what the stock market is going to do in the next year, b) wait a couple days, c) tell the world. In a year, I’ll be rich, and you’ll be famous!

Jim Edmonds

HT Projection as SD/CHC: .346 OBP, .488 SLG, .834 OPS, 18 HR’s
Actual as SD/CHC: .343 OBP, .479 SLG, .822 OPS, 20 HR’s

This is another good projection. Edmonds hit a lot of deep fly balls to left-center field in 2007 that were caught in his home park, Busch Stadium. That tendency carried over to the following season, but it didn’t help him in San Diego, where he started the year. However, after a May trade to the Cubs, Edmonds found a place where that swing worked well. Left-center field is the most favorable spot in Wrigley Field for home runs, and Edmonds took advantage, hitting 6 of his 11 Wrigley home runs into the bleachers in front of Waveland Ave. On the road he picked his spots well also, hitting 7 of his 9 away homers to left and left-center field. A projection that either didn’t factor in Edmonds’ home park, or which couldn’t discern his tendency to hit the other way with power, would be at a disadvantage when trying to accurately forecast Jim Edmonds.

More Thoughts About Forecasting

Here are some possible adjustments I considered, but decided not to include in the Hit Tracker system:

BABIP Adjustment

Regressing a player’s numbers towards the league average BABIP is a common tactic in projection systems. Instead of leaving alone all the non-long fly balls, I considered trying to adjust these hits according to the hitter’s BABIP, e.g. taking away an appropriate number of hits from the projection if the player showed an unusually favorable BABIP during the prior season(s).

My objection to this method is that I don’t feel that I can be certain that a player’s unusually high (or low) BABIP was due to luck instead of due to some underlying real factor. I don’t want to assume that a player’s BABIP should be a certain value, and regress back towards that value, because I don’t feel confident enough that I can pinpoint what that value should be for each individual player. I definitely don’t want to regress all hitters towards a common BABIP. In any event, the use of three years of data to generate projections should minimize any possibility of a player’s wildly aberrant BABIP ruining his projection.

Age Adjustment

Adjusting a projection for a player’s age is another common tactic which has some merit when one’s objective is to be correct "on average," for a large group of players. However, I feel uncomfortable applying an aging correction factor "across the board," without any regard for a player’s particular situation. Perhaps on average hitters lose a small amount of their power each year, but I don’t feel like I can say for which hitters that is true, and for which hitters that is not true, so I have chosen to leave out an aging factor.

I freely admit that an ideal forecasting system of the future will include some method for predicting the effects of aging on future performance, and that I am leaving it out. In the future I hope to be able to incorporate predictive aging into the HT model in terms of lower-level parameters such as speed off bat, or the direction of hits, rather than a crude adjustment of the final results. Such changes in hitters’ spray patterns can readily be detected (a good example is Jim Edmonds, whose long fly balls have decreased in distance and shifted from RF towards LF for the past several seasons.)

Modeling aging in this more detailed manner should also allow for situations where a decline in raw hitting performance does not manifest in a decline in results, such as a power hitter who loses a bit of distance on his fly balls, but still clears the fence with room to spare. I don’t want to paint that hitter, or any hitter for that matter, with the broad brush of "aging means the numbers get smaller"…

Overall "Regression to the Mean"

Some systems regress all of a player’s box score stats towards a selected value, typically a mean value for a subset of the population such as the AL, NL or all of MLB. The purpose of doing so is to account for the possibility that, due to limited sample size, a player has fortuitously outperformed or underperformed their true talent level. The league mean values are used because it is believed that it is impossible to accurately pinpoint a player’s true talent level.

It is certainly true that in any large sample of players, there will be some players that significantly outperform their true talent, some who significantly underperform, and some who perform roughly at their true talent level. In a system where box score outcomes are the only form of data, it makes sense to regress the outcomes to the mean: even though such a system might make some strange predictions (a career high 3 homers in 2009 for Juan Pierre, who has hit one ball out of the park in his last 1,097 at bats?), overall it will perform better than it could without applying such regression.

However, the Hit Tracker system accounts for variation from true talent level in a different way: by including all long flies instead of just homers, the luck factor for ballparks and weather is removed. By including multiple years of data, the sample size becomes even bigger, further decreasing the need to compensate via some form of regression to the mean. With these methods in use, I don’t feel it is appropriate to also add 75 or 80 at-bats from Gabe Gross to the reigning NL MVP’s numbers from 2008 before trying to predict how Prince Albert will do next year.

Advantages of the Hit Tracker System

• The Hit Tracker system goes a long way towards removing statistical noise from the projection. Most good or bad luck a player may have had because they hit a particular ball in a large or small park, in favorable or unfavorable weather, will be removed.
• Analyzing all long fly balls increases the sample size for evaluating power potential, which is one of the most important variables in performance projection. This method makes it possible to detect unlucky trends (Adam Dunn hit 16 balls more than 400 feet that were not home runs in 2008), or lucky trends (9 of Mark DeRosa’s 21 homers in 2008 were blown over the fence by the wind.)
• Team-specific projections are created, but without the use of the extremely blunt instrument known as Park Factors. Because park-based projections are used, the fit of a player’s spray profile to a park’s dimensions and weather is included, and is crucial. The frequency of visits to other parks is also included, capturing the importance of the unbalanced schedule and the vagaries of the interleague schedule.
• Hit Tracker projections are based entirely on what a player does, rather than what an average player does. Since the HT method is focused on making an accurate projection for a single player (and not an entire league), it does not use across the board regression to the mean. Regression to the mean compensates for variables that are missing from a model: Hit Tracker measures those variables instead.

Disadvantages

• The HT method is time-consuming. The observation data required for this method is not for sale, and the analysis can only be done by me.
• The HT method requires video of all batted balls for the player in question. If any hits are not available, the accuracy of the forecast may be reduced proportionally to the percentage of missing balls.
• Because the method depends on analysis of long fly balls, there is a limited ability to evaluate rookies.

Between now and the beginning of the 2009 season, I hope to post some more forecasts for other players, or perhaps expand some of the one-year forecasts listed above to three years. After the 2009 season we’ll have a chance to see how well this method did. I’m hoping that Hit Tracker will be able to bring the process of making projections forward to where weather forecasting was in the 1970’s: occasionally way off, more often on the money, but still far short of perfection (which is forever out of reach). Then we’ll figure out what the next step is…

Greg Rybarczyk is the creator of Hit Tracker, an aerodynamic model and method for recreating the trajectory of batted baseballs. With Hit Tracker, Greg has analyzed more than 15,000 MLB home runs over the past 3 seasons; a multitude of data on hitters, pitchers, ballparks and more can be found at hittrackeronline.com. While not tracking hits, Greg works as a reliability engineer, and he lives in the Portland, OR area with his wife and two children. Feel free to contact Greg at grybar@hittrackeronline.com.

Permalink | Comments (19)

"I'd like to think I did well. I'd like to think that, if I had a must-win game, the guys I played with would want me to have the ball. But no, I don't think I deserve to be in the Hall of Fame." – Curt Schilling, January 29 on WEEI AM 850's "The Big Show"

Last week, the always present and oft self-promoting Curt Schilling showed some rare humility over the Boston radio waves and downplayed his chances at one day ending up in baseball's Hall of Fame. Now some will believe that Schilling only understated his case in order for talking heads (and typing hands) to do what I'm doing right now: make a pitch on Schilling's behalf. Even so, because of his polarizing personality among teammates, fans and the baseball writers, Schilling — unfairly or not — may need all the help he can get.

Given the fact that he's fallen short of all those "important" Hall of Fame benchmarks (300 wins, a trophy case full of Cy Young Awards, a Baseball-Reference page listing dozens upon dozens of All-Star appearances, a Wikipedia page featuring quotes on how feared Schilling was on the mound, etc.), the forty-two year old righty looks like a marginal candidate to earn a bronze bust in Cooperstown. All that said, I'm going to state a strong case for Schilling's enshrinement. I mean, "hey man, even though I'm part of the 'younger people on the Internet,' I saw Schilling play his entire career and I always thought he was a Hall of Famer."

The easiest place to start is to look at Schilling's career performance compared to his peers:

The names listed above are arguably the top ten pitchers during Schilling's career, spanning from 1988 to 2007. There's no question the top five pitchers are no-brainer Hall of Famers (say what you will about the ongoing Roger Clemens saga, but The Rocket is as much an "inner-circle" Hall of Famer as he is a jerk.) After the first five Schilling contemporaries, the numbers start getting blurred but one thing that is clear is that Schilling was one of the best among the next group anyway you slice it. However, before we are so quick to label him "sixth or seventh or eighth best" during his career, let's look a little closer at Schilling's numbers versus the top tier.

Schilling became a full-time starter in 1992 after arriving in Philadelphia – how'd Jason Grimsley work out for ya, Houston? – and was a mainstay in the big league rotations until injuries hit in 2005, forcing him to make 20 appearances out of Boston's bullpen. Even so, he still started 66 games his last three seasons (2005-2007). If we take the top-tier hurlers from the chart above and look strictly at their numbers from 1992 to 2007, Schilling's case for the Hall becomes that much stronger:

During that stretch, Schilling was second in complete games, first in K:BB and third in K/9. Schilling betters the group's average in complete games, strikeouts, walks allowed, K:BB, K/9 and WHIP. By the way, if you didn't know, Schilling's K:BB ratio (4.38) ranks first all-time since 1900. Sure, it's just one stat off the back of a baseball card, but c'mon people…Schilling was a great pitcher, one of the very best in all of baseball for sixteen years — a period which includes at least five Hall of Famers.

One could also look at some Bill Jamesian Hall of Fame metrics, like the Black Ink test, the Gray Ink test, Hall of Fame Standards and Hall of Fame Monitor and Schilling once again stacks up favorably.

The lack of shiny hardware will be an easy thing for many to knock Schilling on, but he did have three second-place finishes in Cy Young Award voting — 2001 and 2002 in the NL and 2004 in the AL. Below are Schilling's three runner-up seasons…seasons good enough to win almost any other year:

I mean, really, is it fair to hold it against Schilling that Randy Johnson (2002) and Johan Santana (2004) were unanimous winners those years? And if awards are your bag, then don't overlook his NLCS MVP from 1993, his World Series co-MVP from 2001 and his back-to-back Pitcher of the Year awards by The Sporting News in 2001 and 2002. If feel-good stories are also your kind of thing, throw in his 1995 Lou Gehrig Memorial Award (best exemplifies character and integrity both on and off the field), his 2001 Roberto Clemente Award (selected for character and charitable contributions to his community) and his 2001 Hutch Award (best exemplifies the fighting spirit and competitive desire to win.) Fluff? Yes, but all part of the package, baby.

Finally, it'd be foolish not to touch on Schilling's postseason record. Everyone remembers Game 6 of the 2004 American League Championship Series, fewer people can recall how dominant he was in Game 7 of the 2001 World Series, and unfortunately not enough people recall how important Schilling's Game 5 start in the 1993 World Series was to the Phillies. But three amazing postseason starts does a Hall of Fame career not make. To truly appreciate Schilling's big game dominance, you have to look at his entire playoff career totals:

Need I say more?

Hmm…let's review. Lots of strikeouts to go along with very solid numbers across the board, unfairly not enough All-Star appearances or Cy Young Awards to please the over-the-hill (or is it under-the-bridge?) Baseball Writers Association of America, an outstanding postseason record, possibly abrasive personality…Geez, does that at all sound familiar? (Oh, give me a break…I'm a Lederer for cryin' out loud!)

The case is pretty clear and the statistics don't lie. So Curt, the next time you want to go on record about your unworthy-for-the-Hall career, put a sock in it, bloody or otherwise.

Joe Lederer is the Assistant General Manager of Riverwalk Golf Club in San Diego. Besides working on his PGA Class A membership, Joe spends way too much time cooking and reading Nietzsche and not enough time working on his short game. Joe gets his baseball writing chops from his mother.

Permalink | Comments (35)

It's been well documented that Jon Heyman has a prejudice against, in his words, "younger people on the Internet who never saw [Bert Blyleven] play." This bigotry in and of itself is sad, but it also is a prime example of one of the most effective logical fallacies: the Ad Hominem. Essentially, as a rebuttal to an argument, one attempts to discredit the person or group of people who present the argument, without discrediting the argument.

The power of this faulty reasoning lies in its ability to change the course of the discussion. Politicians love this fallacy because it allows them to place people who disagree with their policies into negative categories. For example, one might state that proponents of gun control are elitist or out-of-touch. "It's easy," one might argue, "to be for gun control when you live in an exclusive, gated-community and can afford a fancy alarm system." "But wait," the proponent of gun control responds, "I grew up on a farm and live in a ground level apartment in a rough area of town." At this point, they have lost the argument because the debate has changed from the possible benefits or consequences of gun control, to defending one's own character.

We have seen this happen in many of the responses to Heyman's comments: "I'm 70, I saw Blyleven and yes, I use the Internet" or "those stories [Heyman] broke are really not very interesting…" These types of responses which either defend one's own character or attack Heyman's only indulge a discussion that is completely irrelevant to the merits of Blyleven's Hall of Fame candidacy. Sadly, this fallacy is often quite successful to that end.

The Ad Hominem rears its ugly head in many forms. The Circumstantial Ad Hominem is when one argues that a person only supports something because it is in their best interest to do so. One might argue that Pitcher A thinks Blyleven belongs in the Hall only because they have similar stats to Blyleven, and thus it will help their own candidacy. Again, this does not address the underlying arguments that Pitcher A may be making. One's own personal interest is irrelevant (or circumstantial) to those arguments.

The Ad Hominem Tu Quoque discredits an argument by pointing out a person's hypocrisy. For example: "Your statement that Blyleven doesn't belong because of his winning percentage is not valid because you voted for Nolan Ryan who had a lower winning percentage." The fact that someone is a hypocrite does not make their argument invalid. In this case, attention is directed away from why winning percentage is a lousy litmus test for the Hall of Fame.

Another similar fallacy is False Dilemma, which is a distortion of the logical truth P or ~P: either P is true or it is false. With False Dilemma someone will argue P or Q, as if there is some causal link between the two. An example of this fallacy is subtly used by Heyman: people either do not think Blyleven is Hall worthy (P) or they never saw him pitch (Q). The purpose of this fallacious argument is really to stop the opposing voices: either you agree with statement A or you are [fill in any insulting, degrading characterization – in Heyman's case he uses ignorance]. Now the stage has been set so that before anyone disagreeing with Statement A speaks up, they are perceived in a negative way or thought of as sympathizers to a negative group. Often, the discussion will skip right to the insulting characterization as in the following exchange: "I disagree with gun control." "Oh, so you're a hick." Notice that the following fallacious statement is implied here, but never actually stated: either you support gun control or you are a hick. Now the argument can move to a discussion of a person's character without ever having to address the reasons why the person disagrees with gun control.

Another common fallacy used in Hall of Fame discussions is the Relativist Fallacy: stating that something is true in certain situations but not others. With Blyleven, we often hear that he isn't Hall worthy because of his low career winning percentage. When it is pointed out that he has a higher winning percentage than Nolan Ryan, the Relativist Fallacy follows: that doesn't apply to Ryan because Ryan got to 300 wins.

My point with all of this is not to further the Blyleven arguments, Rich and Sully have already done a tremendous job of that. My purpose is to point out that it is extremely difficult to engage in ANY Hall of Fame discussion without running headfirst into a logical fallacy. Take the common argument against Blyleven or for Rice: "he just didn’t feel like a Hall of Famer," or "he was one of the most feared hitters of his time." Both of these arguments are the logical fallacy Appeal to Emotion, whereby emotion is used as evidence of fact. Perhaps it really felt that way to some people at the time but feelings are not facts and often run counter to reality (as statistical analysis has shown with Jim Rice).

Consider the argument that, if Jim Rice goes into the Hall of Fame, then dozens of other similar players also have to be considered and presumably, these dozens of other players are not Hall worthy. This fallacy is known as Appeal to Consequences of a Belief. The consequences of Jim Rice going into the Hall of Fame are not evidence that he does not belong. Furthermore, let's assume that BBWAA got it wrong with Rice and he does not belong. That does not mean that the BBWAA now has to get it wrong with the dozens of similar players that do not belong.

I wondered at the fact that Appeal to Emotion, Appeal to Consequences and Relativist Fallacy are so often considered good evidence of Hall of Fame candidacy. I then went to the Hall of Fame website and looked up the BBWAA rules for election. Any player who played for at least 10 years is eligible to be voted on. However, this is the only guidance given with regards to voting: "voting shall be based upon the player's record, playing ability, integrity, sportsmanship, character, and contributions to the team(s) on which the player played." It also goes on to state there are no automatic elections for outstanding achievements.

Essentially, there are no base standards for Hall of Fame induction. The election system itself is based on the logical fallacy Appeal to Belief: if a certain percentage of a group believe something to be true, then it must be true. Therefore, if 75% of the BBWAA believe someone is a Hall of Famer, they are a Hall of Famer. It is amazing to me that the previous sentence is both a fact and a logical fallacy.

In some ways, it's disheartening to look at the Hall of Fame in this light. It seems that, when talking about the Hall of Fame, all logical arguments reach a dead end. Lacking any concrete standards, all Hall of Fame discussions are eventually reduced to irrational arguments. Furthermore, because there is no logical basis for Hall of Fame entry, examining those who are already in the Hall offers no help. In fact, relying on the current members would also be a logical fallacy: Biased Sample, whereby conclusions are drawn from a sample that is unreliable.

So how can we change the course of the dialogue surrounding the Hall of Fame? I believe that first and foremost we need a logical basis from which to begin. It's time that we reevaluate what it actually means to be a Hall of Famer. A set of minimum, objective standards would help to mute much of the illogical cacophony out there today. While I would leave the actual standards up to someone more qualified than I; it should probably start somewhere with ERA+, OPS+ and win shares: stats that can be used across the many different eras of baseball. Certainly, the standards will be hard to agree upon in the first place and will probably be heavily criticized and even outright rejected by the BBWAA (if not completely ignored). However, without a logical foundation to the Hall, all emotional and irrational arguments will continue to be relied upon and Jon Heyman's gut feeling will have more influence than statistical analysis.

Heyman is not alone in his hostility toward a growing demand for more concrete and quantifiable measures of greatness. But his comments underscore that there has been a real shift in the way baseball is being viewed. No longer are fantastical, unquantifiable and largely indefensible beliefs (such as Derek Jeter being a Gold-Glove caliber shortstop) acceptable to a growing number of baseball fans. Whether or not this change originated with "younger people on the Internet" is irrelevant. The fact is that the current method of evaluation is based upon flawed logic and is being met with discontent. Any attempt to marginalize that discontent should consistently be met with the very thing it cannot handle: more sound, logical thinking.

Conor Gallagher is a paralegal in Chicago, IL. He is also an aspiring winemaker with dreams of moving to California this summer. His passion for baseball and baseball statistics in particular began at the age of eight or so when his father taught him how to keep box scores and they would play APBA together.

Permalink | Comments (45)

Of all the personal testimonials honoring Jim Rice, my favorite is that of the much-beloved late commissioner of baseball, Bart Giamatti, who once wrote that Rice was “the Hammer of God sent to scourge the Yankees.”[1] That alone, in the minds of many baseball fans (outside of New York), should be enough to let Rice through the gates of the game’s Valhalla, Cooperstown’s Hall of Fame.

But, alas, Jim has stuck out 14 times with the Baseball Writers Association of America, and a debate rages over whether this final time will be the charm. Of course, even if he fails – or, rather, if the writers who vote on such matters fail him – his case will be shuffled off to the Veteran’s Committee where he may yet attain immortality. However, opinion across the land seems to be that there is something slightly dodgy and even undignified about entering the Hall in this manner, as though one has come through an inadvertently unlatched back door.

A lot the debate over Rice’s fate has been carried on at the level of “I saw him hit a home run against the [fill in a team name here] when I was [fill in an age under 10 here] and it was the most awesome sight I ever witnessed. [Therefore he should go to the Hall.]” We also see fierce, dramatic but intensely subjective judgments of the stature Rice had when he played. Pitchers, it is said by some, feared him, perhaps more than any other batter in baseball at that time.

SABR members and their intellectual brethren have debated Rice’s qualifications at a somewhat more sophisticated level (mostly), examining Rice’s statistics and awards while comparing his record to those of others who have (and haven’t) had their images inscribed on Cooperstown plaques. Consider, for instance, the claim that Rice was feared by opposing pitchers. Perhaps so, but then what are we to make of the fact that he never received more than 10 intentional base on balls in any one season? By this measure of “feared hitter,” Rice falls behind not only contemporaries Dale Murphy, Garry Templeton, Dave Winfield, and Dave Parker, but also Ted Simmons and Warren Cromartie (each of whom had two or three seasons with 20 or more IBB. With 77 career IBB, Rice is tied for 179th all time, along with players such as Jerry Grote, Ken Henderson, Claudell Washington, and Rice’s one-time teammate Fred Lynn.

In 16 seasons, Rice had a batting average of .298 with 2452 hits and 382 HR – each just a little short of the lifetime statistics that (used to?) assure one a ticket to the Hall. Still, Rice was an All-Star eight times and an MVP once (and he finished 3rd in MVP voting two other times, once in his rookie year, in which he lost to fellow rookie teammate Lynn). If the basic statistics fail to provide a clear answer, one can bring in second-generation statistics to help elucidate matters. For instance, Rice’s OBP was.352 and his SLG was .502, for an OPS of .854. This is just ahead of Hall-of-Famers Eddie Collins and Billy Williams, but behind non-Hall-of-Famers such as Reggie Smith and Jack Clark. So there is nothing decisive here for Rice’s case either. He remains precariously balanced on the cusp of greatness, like a star that is visible in the night sky only if you look slightly to one side of it.

The real statheads among us indulge in even more exotic stuff, like Bill James’ quantitative estimates of similarity among players.[2] Perhaps not surprisingly, Rice scores most similar to another legendary “tough case” for the Hall: Orlando Cepeda. In 17 seasons, Cepeda had 2351 hits (101 fewer than Rice), 379 HR (3 fewer), a .297 career BA (.001 lower), and a .849 career OPS (.005 lower). He was an All-Star 7 times (one fewer), a Rookie of the Year (one more), and an MVP once (tied). Rice fans will note that their man was just slightly better in nearly every case, and that Cepeda ultimately made it into the Hall. But Cepeda hit in an era of tougher pitching (lgOPS of .724 vs. .744 in Rice’s era) and, as a result, Cepeda has a slightly higher park-adjusted league-normalized *OPS+ (133 vs. Rice 128). Again, nothing decisive here. Let us move on. James has also developed some estimates of the likelihood of players entering the Hall. Naturally, Rice is low on one (HoF Standard = 44, where the avg. HoFer scores about 50) and high on the other (HoF Monitor = 144.5, where 100 represents a likely HoFer).

And so, finally, we come to James’ most recent, most influential, and perhaps most complicated estimate of player value: win shares. I won’t go into the calculations here (you can find it on the internet if you are interested), but win shares is supposed to tell us how many additional wins a given player was responsible for with his bat, his fielding, and (if applicable) his pitching. It is well-tested and well-known. It has its quirks, to be sure, but it is generally accepted to do a good job at measuring player performance.

How many win shares did Jim Rice have over the course of his career? 282. How good is that? It is tied with Boog Powell, the one-time MVP, mostly-Oriole LF-1B of the 1960s and 1970s. Powell is not, it should be noted, in the Hall. Fred Lynn is two win shares below Rice. He is not in the Hall. Minnie Minoso and Sal Bando are one win share ahead of Rice. They are not in the Hall. Amos Otis and Toby Harrah are a little further ahead (+4 and +5, respectively). George Sisler is 10 ahead and Dale Murphy (another notoriously tough HoF case) is 12 ahead, tied with Shoeless Joe Jackson. Then Cesar Cedeno (+14), Frank Howard (+15), Home Run Baker (+19), Ken Singleton (+20), Bobby Bonds (+20), Harold Baines (+25), and finally Orlando Cepeda at 310 win shares, a full 28 ahead of Rice.[3] At last, we have some solid evidence that Rice’s career contribution was, in cold reality, just a little below that usually needed to make it into the Hall; that perhaps his presence in Boston made him more visible nationally than Cepeda, who labored mostly in San Francisco and Atlanta (where he worked in the shadows of Willie Mays and Hank Aaron), but not actually quite as good a player.

A number of people have made exactly this case in the debate currently swirling around the vote for the 2009 Hall of Fame induction class. Of course, the win shares numbers are just evidence. They do not constitute definitive “proof.” One can continue to debate, among other things, the relative weaknesses of the various measures used, the importance of “peak” years, and a variety of “intangibles” that are not captured by any of the numbers. Fair enough. But this is how this sort of debate productively proceeds – from impressions, to statistics, to comparative statistics, to better comparative statistics, and so on. For instance, on 14 December 2008, David Kaiser posted an analysis of this kind to the SABR-L list, using win shares (among various other measures) to answer a number of questions about whether Rice should be in the Hall of Fame. Kaiser concluded:

The answers to this quiz are interesting because they show Rice as an almost classic case of a player writers tend to overrate: coming up with the Red Sox in one of their glory eras, he put up some spectacular home run and RBI numbers in his first few years and had one truly fantastic season. As a result he did quite well in MVP voting and was picked for a lot of All-Star games but his actual value was only once (1978) as large as it seemed, his secondary numbers were very poor, and he faded out quickly.

But then comes along Gabriel Schechter, a Research Associate at the National Baseball Hall of Fame & Museum, who wrote in a posting to the SABR-L list on 15 December 2008:

I simply want to register a strong protest over David [Kaiser]'s use of win shares as the primary tool of his analysis…. Rice played in the 1970s and 1980s, so how is it fitting to apply a sabermetrical measure that wasn't even created until 2001? Aren't those questions supposed to reflect how the player was regarded AT THE TIME he was playing? To say that Fred Lynn or Carlton Fisk had more win shares than Rice in a given season and equate that with considering Lynn or Fisk as more highly regarded than Rice is ridiculous.

And so we come to the real point of this column, which was not, it may surprise you to learn, to contribute to the Jim Rice HoF debate but, rather, to discuss the justice of using modern statistical tools (like win shares) to decide historical questions (like whether Jim Rice was so great a ballplayer that he belongs in the Hall of Fame).

I do not know Mr. Schechter’s views of statistical analysis generally. There are some fans (and players and managers) who believe they see plainly with their eyes (and with their memories), and that statistics, with all their fussy formulas, only confuse the issue. Without further ado, I commend to them the cognitive psychological work of people such as Paul Meehl, Gerd Gigerenzer, and Nobel prize-winner Daniel Kahneman to disabuse them of their misapprehension. I will assume that Mr. Schechter, instead, is only objecting to the casting back of modern statistics into historical eras. I suspect, however, that he has confused two superficially similar, though, in point of fact, quite distinct complaints. The one, to which many object, has to do with creating leader boards and records for statistics that did not exist when a particular season was played. So, for instance, claiming that Three-Finger Brown led the NL in saves four years running, from 1908-1911 (5, 7, 7, 13), seems a little silly not just because there was no such statistic for Brown to lead the league in then, but also because the conception of the relief pitcher as a kind of “specialist” with a particular “function” (such as “saving”) was not yet in place in Brown’s time. It is a little like claiming that Hannibal had more “tanks” than the Romans on account of his use of elephants. I have some sympathy with this objection.

However, that is not what is going on when Mr. Kaiser (and others) use win shares to analyze the performance of players past. First of all, there is nothing that goes into computing win shares that would have been foreign to Rice or his cohort: hits, at bats, bases on balls, total bases, outs, etc. Mr. James has just stirred a little differently a pot of wholly familiar ingredients. Second, the point of doing this kind of analysis is not (only) to create a retrospective leader board, but rather to use quantitative methods to analyze Rice’s performance relative to his peers (and to others throughout the history of major league baseball). With a modicum of judiciousness, there is nothing in the least ridiculous about this process. Indeed, we do it all the time.

To wit, which of these historical questions are ridiculous? How many people lived in the city of Rome in 44 bc? What proportion of them were slaves? What was the average life expectancy? What were the leading causes of death? Among the land owners? Among slaves? Across genders? All of them require quantitative answers. All of them were questions that went unasked (and unanswered) by the Romans themselves. That does not make them historically illegitimate. Consider more questions of the same type: What proportion of the US population spoke English as a mother tongue in 1776? What proportion of the American population approved of Abraham’s Lincoln’s actions in 1863? Would Woodrow Wilson have won the 1912 presidential election if either William Howard Taft or Theodore Roosevelt had dropped out of the race?

The people of these eras did not have either the data or the methods (or both) to answer such questions definitively, but certainly there is nothing to prevent us from using the methods we have since developed on the data that we still have from those times to develop answers that are in some ways better than the ones people of the time in question could have generated (for instance, computers make it possible for us to manipulate huge masses of data that would have been impracticable, if not strictly impossible, prior to their invention).

Far from being illegitimate, a statistic like win shares is precisely the kind of evidence to which members of the BBWAA should attend more fully when deciding questions like whether Jim Rice was as good a player as the others who are now in the Hall. It allows us to separate dispassionate consideration of the merits of the case from contentious but ultimately irrelevant stories of who thrilled us when we were young. Isn’t that exactly why the BBWAA waits five years after a player retires before considering his case for entering the Hall – to let passions cool and allow the facts to rise to the surface?

-----

Notes:

[1] Giamatti, A. Bartlett (1998). "The Green Fields of the Mind." In A Great and Glorious Game: Baseball Writings of A. Bartlett Giamatti. Algonquin. Available on-line at: http://mason.gmu.edu/~rmatz/giamatti.html.

[2] The source I used was baseball-reference.com.

[3] I have only picked a few familiar names between Rice and Cepeda. In fact there were 56 players separating the two on the all-time win shares list, as of 2002. (Players like Frank Thomas have since passed Cepeda. Others have, no doubt, crept between them from below Rice in the intervening years.)

Christopher D. Green teaches statistics in the Department of Psychology at York University in Toronto. His academic research is mostly concerned with the history of psychology.

Permalink | Comments (18)

Free agents are just waiting for that first shoe to drop. Once one mega-contract is signed, others will surely follow. Or at least, that's the optimistic tone agents are trying to set, amidst all sorts of negative indicators.

The New York Times ran a piece last week that noted how slowly the free agent market was moving, relative to the past five offseasons. The obvious assumption is that the economy is forcing teams to be more cautious, and that the players could be in for a rough winter.

I touched on this a bit on Squawking Baseball on Monday. The Times' data, in itself, isn't overly convincing; the sample sizes are too small to have any real meaning, and these types of dead periods happen at some point in every offseason. But with that said, this is the behavior we would expect in this type of economic atmosphere.

To see how this dynamic plays out, it's important to consider how teams value players to begin with. If you remember back to Econ 101, companies will hire employees up until the point when marginal revenue equals marginal cost. So if the A's project that Rafael Furcal will bring them $15 million in additional revenue next season, they should be willing to pay him up to $15 million. This number is his marginal revenue product (MRP).

Sounds simple enough, but a player's MRP is tied to many different factors. The most obvious, of course, is the player's production. In our hypothetical, the A's could project that Furcal is worth five additional wins, and each of those wins is worth $3 million, making his MRP $15 million.

But what if the A's, worried about the economic climate, decided to do a whole new set of revenue forecasts for 2009, and found that ticket sales were likely to take a huge hit? Or that demand for playoff tickets (should the team get that far) would be much lighter than normal, resulting in lower prices? All of a sudden, the rewards of winning 5 more games and possibly reaching the playoffs are much smaller. This, in turn, means that Furcal's marginal value to the team is much less, so his MRP (or the salary the team would have been willing to pay him) goes down as well.

It's unlikely that MLB, as a whole, will see a decline in revenue next year (I've actually been very bullish on this front). But there is obviously a tremendous amount of uncertainty, which generally (and rightfully) should lead individual teams to set very conservative revenue projections, and therefore very conservative budgets.

Bud Selig has gone out of his way to make sure the owners and general managers realize all of this. During the last recession, which began in 2001, baseball revenues stagnated. The teams, used to double-digit growth, kept adding on expenses accordingly. The result was almost disastrous, with the Devil Rays and Tigers reportedly almost missing payroll.

Scott Boras has a different take, of course, citing teams' record profits and large cash positions. "I always look at baseball revenues, and in the last seven years they have gone from $3 billion to $6.5 billion," he said. "If baseball revenues drop off, that's something we'll look at, but if there is a drop-off, it is not going to be dramatic."

He continues, ""You can't say just because one sector is bad, all others are as well. Baseball is doing very, very well."

In a lot of ways, he's right. But it's also his job to be optimistic, and he's not taking into account the most fundamental aspect of the market: budgets are set based on next year's projections, not last year's performance. And there will be a tremendous amount of uncertainty, if not overt negativity, priced into teams' budgets.

That uncertainty lies in several areas of each team's operations. Taking a closer look, we can break it down by the major sources of revenue. Depending on the team's market, competitiveness, and brand loyalty, certain factors will be more pressing than others (i.e. the Pirates should be very concerned about almost all of them, while the Yankees just need to sell their last luxury suite):

1) Season ticket sales. This should be a pretty tough market for season tickets, relative to years past. The financial crisis hit in mid-September, and the economic news isn't likely to get better before Opening Day. That means teams will be facing constant headwinds, as consumers will be less likely to spend on expensive, discretionary goods such as season ticket packages. Teams will probably have to rely more on corporations, which will be much harder in certain places than others (think Detroit).

2) Individual game tickets / gameday-related sales (concessions, parking, etc.). These are linked, obviously, since the more tickets a team sells, the more concessions they will sell, as well. Teams often have a tipping point during the season, where fans either come in droves because the team is competitive, or stay away because the team is out of the race. In a good economy, a bad team may still be able to draw fans in August and September, since consumers have cash to spend. But in this current atmosphere, bad teams could set multi-year lows in attendance.

3) Luxury suite sales. Most of these should be sold by now. For those still left, it will no doubt be a tough atmosphere. But the supply is so small, teams should still be able to sell out, even if they have to lower prices a bit. This won't be a tremendous hit for a team's overall revenue intake.

4) Corporate sponsorships. Corporate sales vary tremendously, team to team. Some may have most of their inventory locked up in long term deals. Others may have several partners up for renewal, which isn't the best situation to be in right now (especially if one of those partners is General Motors). For those that have inventory available, most new deals are closed between January and Opening Day. There may have to be discounts in order, but, much like with luxury suites, most teams shouldn't see a huge year-over-year decline.

5) National media contracts. These are fixed for next season.

6) Local media contracts. Like the national media contracts, most (if not all) teams are already set with their local media contracts. Teams that own their RSN, or sell their own radio advertising, may see some declines. But cable, especially, is a pretty good place to be right now, since the networks are paid subscriber fees by the operators.

7) Merchandise. This is squarely in the consumer realm, so that's not good. If there's any way to efficiently boost merchandise sales in 2009, it's to do it virally through MLB.com. I've often advocated taking down MLB.com's pay-walls, opening up the video vault that sits in downtown Manhattan, and building an incredible online content collection. This would make MLB.com an even better destination site than it is today, and in the process create tons of new advertising inventory that MLB could either sell, or use to push its own products.

8) Revenue sharing. Imagine trying to set a budget for next year, when much of your income relies on the performance of others. For a big market team, this means possibly writing a larger check, even in the face of declining revenues. For a small market team, it means having no control over a huge chunk of earnings. Of all the unknowns going into 2009, this may be the biggest one.

Given all that, it's no wonder general managers are being cautious. In the past, when they could count on year-over-year growth, long-term contracts weren't quite as risky. Derek Lowe's four-year, $36 million deal seemed terribly expensive in January of '05. But after four years of massive industry-wide expansion, it looks downright cheap. (Don't think Paul DePodesta thought about that back then?)

On the flipside, long-term contracts that were signed in the late '90s and early '00s were considered albatrosses by 2003. When Alex Rodriguez was traded to the Yankees, few could have imagined that he would even consider opting out (let alone get an even bigger deal) just four years later.

In good times, multi-year deals are calculated risks. In bad times, they're fireable offenses. No GM wants to be stuck with bad contracts and a shrinking budget.

So what are the likely results? The teams with some breathing room, like the Yankees and Red Sox, will keep taking calculated risks. The top tier of players (CC Sabathia, Mark Teixeira) should get very nice deals. But the great majority of the small- and mid-market teams will be extremely conservative, and that will bring down overall demand (and salaries) for the rest of the players on the market.

In particular, look for long-term deals to be shorter than most people are expecting. No GM wants to be collared with bad contracts in this environment, and the smart ones (of which there are more now than ever before) will be extremely careful.

In all, not such a rosy outlook. But it's really more of a call for conservatism by Selig (and Paul Volcker, apparently), reminding teams of the legitimate pain many of them went through during the previous downturn. Given the magnitude of this recession compared to the last one, expect the teams to heed the advice.

Shawn Hoffman writes about business and baseball at Squawking Baseball. In real life, he is a principal in web startup Veritocracy.

Permalink | Comments (3)

Manuel Aristides Ramirez was all of 15 months old on Aug. 23, 1973, when Jan Erik Olsson walked into Kreditbanken, a Stockholm bank on Normalmstorg square, shot a member of the Swedish police and took four people hostage.

The hostage crisis continued for five days as Olsson and his alleged accomplice, Clark Olofsson, negotiated with police and even the Swedish prime minister. During the ordeal, the four hostages were said to express more fear of the police than their captors. A criminologist working with police noted the attitude and coined a phrase that provided Olsson and Olofsson some measure of infamy long after the robbery was forgotten: “Stockholm syndrome.”

The aforementioned Ramirez left the Boston Red Sox – all but forced his departure, if reports are to be believed – at the end of July, nearly four months ago. Yet stories continue to leak about the tumultuous final month between Ramirez and the team that paid him handsomely for nearly eight years, and none of them portrays the clearly mercurial slugger as the nice guy.

On the field, the situation seems to have turned out as well for everyone as could be expected: the Red Sox received a left fielder that essentially replaced Ramirez’s pre-trade production, the Los Angeles Dodgers got an otherworldly performance from Ramirez that pushed them into the playoffs, and Ramirez and his agent, Scott Boras, will make a killing in free agency.

Everyone wins but me.

I don’t need your pity – at least not anymore. As a Red Sox fan, I’ve seen two world championships and witnessed more playoff appearances since 2002 than in the previous 13 years combined. Dealing with the drama of Manny Ramirez was easily worth those rings.

But it’s becoming clearer that for much of the seven-plus years Ramirez was in Boston, we as fans were Manny’s hostages. He pouted, lied to the press (and consequently to us), showed up late – or not at all – to All-Star Games and managerial meetings alike, refused to pinch hit when asked or even refused to play.

He did this before the current ownership bought the team in 2001. He did it during the 2002 transition year before Theo Epstein was named general manager. And he did it nearly every season since Epstein took the reins in 2003. The incidents all became part of “Manny being Manny.”

And while the Red Sox made some efforts to rid themselves of his shtick – placing him on waivers and nearly engineering his trade to the baseball wilderness of Texas being the most notorious – we as fans never seemed to fully believe the import of these stories.

Moreso than even David Ortiz, Manny Ramirez was the face of the Red Sox, and we were happy with this scenario. At least I certainly was. Heck, there’s an orange-and-white feline with an attitude that stalks my house and answers – when he feels like it – to “Manny.”

How did we let this man fool us so?

The evidence was there, even before 2008, that Ramirez cared little for the Red Sox and their fans, none at all for Boston and its culture. When John Henry met Ramirez in 2002, the first thing he heard was a trade request. When Grady Little, a man whose surname speaks to his accomplishments in a Red Sox uniform, benched Ramirez for refusing to pinch hit during a ninth-inning rally in 2003, Henry and Larry Lucchino were approached a second time about a trade.

It all happened again in 2005, and it seemed the fans had enough. Ramirez was booed at the plate that July, as his trade demands and lollygagging to first reached team-distraction proportions. But when the trade deadline expired – a three-team deal having fallen through – Ramirez seemed to renew himself to Boston, receiving a standing ovation in his first at-bat back and telling anyone who would listen that he wanted to win another World Series with the Red Sox.

Frustration turned to rejoicing, and we took Ramirez at his word. When he sat the final month of the lost 2006 season and stories began to crop up alleging he had quit on the team, I rejected these rumors. No proof, I said. No evidence.

Things seemed rosier than ever after the second championship in 2007. Ramirez began talking to the press again after his tremendous ALDS walk-off home run off Francisco Rodriguez, he began reading “The Secret,” he told the sportswriters he wanted to stay in Boston, and he expressed ambivalence about when or whether the Sox picked up his two options after the season.

With Ramirez still productive, his $20 million options no longer seemed excessive. It seemed impossible to imagine a future without the suddenly happy, suddenly affordable Manny Ramirez. He still had his moments, but there were those other moments, too – the mid-double-play high-five with a fan, the trips into the Green Monster. They were goofy. They weren’t always appreciated, but they were the kind of antics that make the game fun, that make you believe some guys aren’t out there thinking only about the money.

Perhaps that was why it was so easy for some of us to accept the mythos of Manny being Manny. The talented hitter who wanted to do nothing more than hit. Not an idiot – I always rejected that slur – but simply happy and secure in his own world. One could understand why he didn’t like the microscope of Boston, and his brilliance with the bat couldn’t help but smooth over the rough patches over the years.

Then he hired Scott Boras.

I don’t know whether Boras put Ramirez up to the things he did once the 2008 season began. For that matter, I don’t even know what exactly Ramirez did and what he’s merely suspected of doing. All I know is what’s been said, but that it fits closely with what we know has actually occurred.

We know Ramirez shoved traveling secretary Jack McCormick. We know he got into an in-game dugout scuffle with fan- and organization-favorite Kevin Youkilis. We know he suddenly demanded the Red Sox pick up his first option, and that he considered any sign of caution or prudence on Boston’s part to be disrespectful.

I watched these goings-on with dismay. What happened? Ramirez was having the as-expected rebound season from his subpar 2007. It shouldn’t have surprised me that he changed his mind, but it did nonetheless. For some reason, I kept hoping that this time he meant it. This time would be different. This time Ramirez cared. Turns out it wasn’t. Turns out he didn’t.

July was the worst yet. He sat in back-to-back games against the Yankees, complaining of a sore knee. When the Red Sox sent him to get an MRI, he couldn’t remember which one was sore. When he pinch-hit against Mariano Rivera on what was supposed to be a day off, he never swung the bat in taking three straight strikes.

It might have been the most controversial single plate appearance of 2008 in Red Sox Nation. Was Ramirez fooled by three devastating cutters from a Hall-of-Fame pitcher – two of which were borderline strikes? Or was he making a statement about his intentions if the Red Sox failed to trade him by the July 31 deadline? The maddening thing is we’ll never know. Again, I found myself defending Ramirez.

But the end was coming. Apparently, the Red Sox threatened a suspension – a threat made more believable by Boras’ inability to deny it. He made comments too ridiculous to laugh off, alleging the Red Sox lied to their players, telling the press he was “tired” of the team. He wanted out. He was clearly doing everything possible to ensure that would happen.

At the time, I wrote:

I may be tired of him. I may not love him anymore. I don't think I even particularly like him after the events of this weekend. But he's still our Manny. For better or worse, he's wearing the laundry, and that means we root for him. Just like we'd root for Barry Bonds or Alex Rodriguez if they wound up in red and white.

No matter how tired Ramirez is of the Red Sox, or the Sox of him, they need each other if they want to play baseball this October. And that means we need him, too.

That was three days before Ramirez was sent to LA in a three-way trade with the Pirates for Jason Bay. The Red Sox turned around their flatlining season and played baseball in October after all. Ramirez got what he wanted. The Red Sox, after their seemingly annual attempts to be rid of him, finally got what they wanted.

So why do I feel so unhappy?

Much ink has been spilled, many megabytes filled about the Manny Ramirez saga – his time in Boston, the trade that sent him west, his resurgence at Chavez Ravine. I have no interest in further repeating the many words said on the matter, many by his own teammates. I can only offer one fan’s perspective – one that renders me incapable of seeing things in the stark rhetoric many have employed to vilify Ramirez or, alternately, the Red Sox organization.

It seems clear that Ramirez through his actions was the aggressor here, for reasons perhaps only he knows. Yet it’s difficult to harbor resentment for what certainly appears to be a clear case of a player attempting to hold a team hostage – and receiving all that he demanded.

He gave us so much, after all. Ask any group of Red Sox fans for their favorite Manny moments, and you’re not likely to leave any time soon. There’s the simple magnitude of the numbers he posted – statistics that likely will ensure his induction into the Hall of Fame with a “B” on his cap. There’s the two rings, the World Series MVP, his place as half the greatest 3/4 combination of our generation.

Others may be able to push all that aside and demonize the slugger, dismiss his time in Boston and turn away without glancing back as he heads toward mega dollars this offseason. I cannot. He was our Manny. We were his hostages.

Paul Anthony is a native Connecticutian transplanted to Texas, where he covers politics for a daily newspaper. His (unpaid) night job is as a co-blogger at YFSF, which has provided a peaceful coexistence for Red Sox and Yankee fans since 2003. While there, he has compiled a list of the Top 50 individual Red Sox seasons of all time.

Permalink | Comments (12)

I'm Rob McMillin, author of the Dodgers and Angels blog 6-4-2, and a long-time reader of Rich's The Baseball Analysts through several homes. Patrick Sullivan asked me to do a review of the Dodgers and Cubs in preparation for their upcoming National League Division Series, and so here I am.

The long-term regular-season matchup for the Dodgers versus the Cubs is remarkably even — as of the end of 2007, it was 1,009 wins and 1,007 losses for the Dodgers. But change that to the Los Angeles era, and it becomes much more lopsided, as the Dodgers won the all-time series 343-281. The 84-win 2008 Dodgers are 2-5 against the Cubs this year, but that record may prove fairly useless for predictive purposes when it comes down to the postseason.

While the main reason for this is the Dodgers' acquisition of Manny Ramirez, there are other mitigating factors in play. Along with David Mick of Another Cubs Blog, we'll take a look at both teams head-to-head and review the teams position-by-position. As always, rate stats are indicated as AVG/OBP/SLG (batting average/on-base percentage/slugging average).

SCHEDULE

Game 1: Wed., Oct. 1, 6:30 PM ET on TBS - LAD (Derek Lowe) @ CHC (Ryan Dempster)
Game 2: Thu., Oct. 2, 9:30 PM ET on TBS - LAD (Chad Billingsley) @ CHC (Carlos Zambrano)
Game 3: Sat., Oct. 4, 10 PM ET on TBS - CHC (Rich Harden) @ LAD (Hiroki Kuroda)
Game 4*: Sun., Oct. 5, TBD on TBS - CHC (Ted Lilly) @ LAD (TBD)
Game 5*: Tue., Oct 7, TBD on TBS - LAD (TBD) @ CHC (Ryan Dempster)

* if necessary

RECORDS

         HOME      ROAD     TOTAL
LAD     48-33     36-45     84-78     
CHC     55-26     42-38     97-64
Head-to-head results: CHC, 5-2

OFFENSE

        RUNS   AVG   OBP   SLG   OPS   OPS+  
LAD     700   .264  .333  .399  .732    95     
CHC     855   .278  .354  .443  .797   109 

PITCHING AND DEFENSE

        RUNS   AVG   OBP   SLG   OPS   ERA+  
LAD     648   .251  .315  .376  .691   120 
CHC     671   .242  .316  .395  .711   117

Position-By-Position Breakdown

Catcher
Russell Martin's (.280/.385/.396, 650 PA, 13 HR) numbers have descended considerably from his astonishing 2007 campaign (.293/.374/.469); perhaps not coincidentally, some of this is due to his league-leading 149 games caught, a figure he shares with Jason Kendall of the Brewers. Breaking it down by innings caught, Kendall takes the lead outright with 1,328.1, while Martin is almost a hundred outs behind him at 1,238. Defensively, Martin has slipped some, as his throwing mechanics seem to have gone haywire, recording 11 errors. It's not at Gary Bennett levels, but it's something to pay attention to. Having watched both fairly extensively, they're both capable of calling good games, and in neither case should their inability to throw out base-stealers (both are hovering around the 25% mark) be held against them.

Geovany Soto (.285/.364/.504, 563 PA, 23 HR) won the 2008 job behind the plate with his stellar performance in September of 2007. He's among the best catchers offensively and he's above average defensively. He missed the last few games the Cubs played because of a hand injury, which is something that has been recurring to Soto in 2008. The Cubs say he's ready to go for Game 1. Soto is most likely going to win Rookie of the Year in the NL, but what's more impressive is that among Cubs position players, nobody has been more productive.

Rob says: Soto has the edge mainly because of his offensive game.

David says: Edge goes to the Cubs.

First Base
A lot of James Loney's (.280/.385/.396, 651 PA, 13 HR) value is tied up in his high batting average, and as he was unable to keep up his insane batting average on balls in play from 2007 (when he hit .350), and sure enough as it fell to .284, so did his average, and more ominously, his slugging percentage. Loney's weakness is his inability to hit lefties consistently, with a .249/.303/.361 line that has led to a late-season experiment using Nomar Garciaparra in a platoon role at first. This will only arise as an issue with the only lefty Cubs starter, Ted Lilly, but the difference — a small-sample-sized .339/.424/.643 — makes him a potent force.

Derrek Lee (.291/.361/.462, 698 PA, 20 HR) got off to a great start in April. He had a horrid May and the rest of the months were disappointing for Lee, the Cubs and their fans. He's essentially been a .750ish OPS hitter since April. Overall his numbers were still solid, but his defense is overrated (+1.1 runs) and his offensive skills are in decline. Lee's still capable of getting hot and if he could get hot like he was in April for these playoffs, an already outstanding offense becomes that much better.

Rob says: Cubs have the edge thanks to Lee's sizeable offensive prowess. It should be noted, however, that Lee hit eight home runs in April and hasn't hit more than two in a single month since May.

Dave says: Dodgers. Lee is a better offensive player than Loney, but Loney is about 13 runs better on defense. (ed note, nice call, Dave!)

Second Base
"What," Cubs fans might be asking, "is Blake DeWitt (.264/.344/.383, 421 PA, 9 HR) doing at second?" Well, they could be pardoned for their confusion; earlier in the year, he was the Dodgers' starting third baseman, but as the season progressed and his hitting didn't, he eventually earned a return trip to AAA Las Vegas. Nevertheless, he still finished 2008 atop the Dodgers' leaderboard for innings at third, but once the Dodgers traded for Casey Blake and realized that Jeff Kent is too fragile to stay on the field anymore, they moved DeWitt to second and recalled him to play there in the Show.

Mike Fontenot (305/.395/.514, 284 PA, 9 HR) was probably the best role player in all of baseball this season. He's limited in that he can only play 2nd base, but he's had a very good defensive year and his offense has helped the Cubs when they need extra production the most. Fontenot won't play much against lefties (only 21 ABs in 2008), but the Dodgers have four righties starting in the series. His .398 wOBA was the highest on a team that led the league in runs scored.

Rob says: This is a clear win for the Cubs with the caveat that this matchup really shows the limitation of position-by-position analysis.

Dave says: Edge to the Cubs here.

Third Base
There is no doubt that Casey Blake (.251/.313/.460, 233 PA, 10 HR w/ Dodgers) marks an offensive improvement over DeWitt (at least at this point in their respective careers), but whether it was worth giving up catching prospect Carlos Santana for a two-month rental remains to be seen. The further away from July he's gotten, the worse his offense has become (.220/.297/.415 in September).

Aramis Ramirez (.289/.380/.518, 645 PA, 27 HR) has more big hits since he joined the Cubs in 2003 than I can remember. On top of that, over the last 5 years he's been one of the best 3rd basemen year in and year out. In 2008 he improved his plate discipline and set a career high OBP of .380. The defense is above average as well. If the game is on the line, the Cubs want Aramis Ramirez at the plate.

Rob says: Another win for the Cubs, one which ends up quite large once you consider the gap between recent performance (Ramirez is hitting .342/.386/.566 in September).

Dave says: Cubs

Shortstop
This is probably the most perplexing move the Dodgers have made to date; Rafael Furcal (.357/.439/.573, 164 PA, 5 HR) returned to service very late from a lower back injury that knocked him out most of the season (his last regular season game was May 5). With only days to go in the regular season, no rehab stint in the minors available to tune him up, there's no reason to believe he'll be effective against live pitching. He was insanely hot to start the season, as his 2008 numbers suggest, but he's the Dodgers' biggest question mark. It will be interesting to see what Joe Torre does with him if he can't hit, especially considering the Dodgers' options most of the year have been the not-ready-for-prime-time Chin-Lung Hu and Royals castoff Angel Berroa.

Ryan Theriot (.307/.387/.359, 661 PA, 1 HR) is playing out of position. He's one of the worst defensive shortstops in the game (-9.7 runs). Lou still isn't asking for my advice so he's stuck at the position. Theriot did hit .300 this season and much more importantly, he posted an OBP of .387. Much like last year, Theriot faded down the stretch (.686 OPS in August, .660 OPS in September). Despite that, Theriot enters the NLDS 11 for his last 19 with 6 walks in that span.

Rob says: If Furcal is healthy, a huge if, he provides the Dodgers a win, but we won't know what Furcal we're getting until the postseason opens.

Ryan says: Dodgers. If Furcal doesn't play much then the edge goes to the Cubs.

Left Field
The Cubs have a very good offensive left fielder in Soriano who nevertheless is still far behind Manny Ramirez (.396/.489/.743, 229 PA, 17 HR); Manny has been simply otherworldly with the Dodgers. While nobody thinks Manny will continue this hot (almost half his home runs have been hit in the two months since coming to LA), it's more than enough to make up for his defensive lapses in left, something both players are prone to.

Alfonso Soriano (.280/.344/.532, 503 PA, 29 HR) had had a disappointing year defensively. He had been so very good since he moved to LF in 2006, but the combination of age and leg injuries seems to have caught up with him. Soriano led the team in home runs despite missing about 50 games. I think he's the one offensive player the Cubs have who is capable of carrying the rest of the team. If Soriano doesn't hit in the postseason (and let's be honest, he hasn't done much of that in his career), the starters will have to be at the top of their game.

Rob says: The Dodgers win handily here.

Dave says: Dodgers. It's not even close. As good as Soriano is, he isn't Manny.

Center Field
Matt Kemp's (.290/.340/.459, 657 PA, 18 HR) conversion to center was belated but necessary thanks to the acquisition of noodle-armed Juan Pierre and the collapsing Andruw Jones. Kemp logged much of his time in right prior to his conversion, but his bat (so far) plays better in center field. Kemp isn't a dancing bear defensively, but neither is he among the league's elite.

Jim Edmonds (.235/.343/.479, 298 PA, 19 HR) was picked up in May after an awful start with the Padres. As a longtime Cardinal, no Cubs fan wanted to root for Edmonds, but he made it remarkably easy to. It's as if he reverted back to the prime of his career. His .394 wOBA is 2nd on the team and his .568 slugging was the highest. My biggest concern at the time of the signing was his defense. Nobody could have predicted the offense and it turns out nobody could have predicted how well he'd play CF either. His .931 RZR was the highest since before 2004. His 45 OOZ were equal to 2005 in nearly 530 fewer innings.

Rob says: This is a slight edge to the Dodgers who don't have to give up average to get power, especially since the Dodgers won't be sending a lefty to the mound in the series.

Dave says: Cubs

Right Field
Andre Ethier (.305/.375/.510, 596 PA, 20 HR) has become a solid presence in the Dodger outfield this year, hitting for decent power and average, especially so in August (.292/.346/.615) and September (.462/.557/.692). Opinions differ wildly over whether Ethier has taken a step forward on a permanent basis, but he's been hitting out of his mind lately. Even before that, Ethier emerged as one of the team's top two hitters all year.

Mark DeRosa (.285/.376/.481, 593 PA, 21 HR) had a career year in 2008. He took over RF for the struggling Fukudome in early September with Fontenot moving to 2nd against righties. DeRosa isn't your typical RF. He's an infielder by trade, but in his big league career he's proven he can play just about anywhere. He adds above average defense in RF as well. He posted a .382 wOBA in 2008 and like so many of the other Cubs, his OBP was very good (.376).

Rob says: This represents a substantial win for the Dodgers, whether Piniella starts DeRosa or Fukudome.

Dave says: Cubs. Like 1st base, defense is the deciding factor here. Ethier and DeRosa have had similar years offensively (.382 wOBA for DeRosa, .385 wOBA for Ehtier), but DeRosa is 15.8 runs better defensively. Just after I finished writing this, I noticed that DeRosa's left calf may still be too sore for him to play RF, which means Fukudome would play RF with either DeRosa or Fontenot at 2nd. If that's the case, edge to the Dodgers.

Bench

After a futile dalliance with Gary Bennett earlier in the season, the Dodgers settled on Danny Ardoin as their reserve catcher.

Angel Berroa may get a start at short if Rafael Furcal doesn't feel up to it or is showing he's obviously not ready to play. Nomar Garciaparra and Jeff Kent will provide right-handed power off the bench unless Ted Lilly is starting. Pablo Ozuna will almost certainly be relegated to the role of late-innings defensive replacement for Casey Blake, and the od pinch-running job.

Both teams are carrying only one reserve outfielder. In the Dodgers' case, Juan Pierre is likely to be a designated pinch-runner; his starting days were all but over in the regular season, and it's hard to imagine Joe Torre using him for anything else. Felix Pie doesn't seem likely to get much playing time after he played himself out of the outfield. This is a wash, not that it much matters.

Reed Johnson has been the other half of the CF platoon and since the Dodgers are throwing righties at the Cubs, he won't get much playing time. Like Edmonds, he was picked up after his former team released him and the 2 of them have combined to put together a very good season for the Cubs in CF. Johnson can hit lefties rather well, doesn't field as well as some may think, but has had a real good season for the Cubs.

Kosuke Fukudome lost his starting job sometime in late August or early September after months of struggling to hit the ball. He won't be asked to do that much in the playoffs and he'll get a chance to be a defensive replacement. His defense is matched by only a few in all of baseball. He is spectacular on with the glove. Just can't hit.

Others: Ronny Cedeno (INF), Henry Blanco (C). Felix Pie (CF), Daryle Ward (1B/RF)

Rob says: Too close to call.

Dave says: I'll call it even because in that few plate appearances, literally anything is possible.

Starting Rotation

Derek Lowe 14-11, 3.24 ERA, 211 IP, 136 ERA+
Chad Billingsley 16-10, 3.14 ERA, 200.2 IP, 141 ERA+
Hiroki Kuroda 9-10, 3.73 ERA, 183.1 IP, 119 ERA+

Derek Lowe had early trouble but has come on strong in the second half with a 2.38 ERA. His key is getting outs on the ground with his heavy sinker; if he's giving up line drives, something's wrong with his game. Chad Billingsley is the staff's real ace, and many expect this NLDS will be his coming-out party; he hasn't attracted a lot of national attention because of a fairly slow start. He's whiffing about a batter an inning, while walking less than half that (201/80 K/BB). Like Forrest Gump's box of chocolates, you never know what you'll get from Hiroki Kuroda, seven scoreless innings or seven runs in the first. That overstates things, though, as Kuroda has been about what the Dodgers had expected despite some injury problems in midseason.

Ryan Dempster 17-6, 2.96 ERA, 206.2 IP, 152 ERA+
Carlos Zambrano 14-6, 3.91 ERA, 206.2 IP, 115 ERA+
Rich Harden 5-1, 1.77 ERA, 71 IP, 254 ERA+
Ted Lilly 17-9, 4.09 ERA, 204.2 IP, 110 ERA+

Ryan Dempster was closing games for the Cubs the last 3 years and now he's starting Game 1 in the playoffs. He's earned it. In only one start this year did Dempster allow more than 4 earned runs. He allowed 4 in only 5 starts. 22 times he's allowed 2 or fewer runs. He posted a 2.96 ERA this year, which stunned just about everybody. He's been the best starter the Cubs have had from start to finish.

Carlos Zambrano has had a couple of injuries in the 2nd half. They say neither is serious, but you never know. His first half was tremendous and he appeared to be more consistent than I had ever seen him. Then the 2nd half started and he was also consistent. Consistently not very good. Despite the no-hitter, Zambrano could just never get settled back down after coming back from injury.

Rich Harden has been unbelievable as a Cub. In 71 innings, he's allowed only 4.94 hits per 9 and has struck out 11.28 per 9. His ERA is 1.77. I'm still getting familiarized by Rich Harden, but from what I can gather, if he can take the mound, odds are your team is going to win the ballgame. In 9 of his 12 starts with the Cubs he allowed 1 or 0 runs. He allowed 2 runs twice and in the other start he allowed 4 runs.

Ted Lilly is coming off 4 consecutive wins giving him a career high 17. Lilly got off to a terrible start posting a 6.46 ERA in April. He posted a 3.33 ERA after the break and held hitters to a .223 batting average. Ted has had severe reverse splits in 2008. From 2005-2007 righties posted a .756 OPS and lefties a .712 OPS against Lilly. That's typical. But in 2008, lefties have hit him for a .928 OPS and righties only a .673 OPS. He's developed a cutter this year that he uses on right handed hitters and it has worked very well. He's not throwing the big over the top hook as often so that may be why the lefties are hitting him better. Maybe it's just sample size.

Rob says: Despite a formidable rotation on both sides, the Cubs have a slight advantage because Dempster and Harden are perhaps a bit better than Lowe and Kuroda, and also because they won't be asking their starters to work a three-man rotation.

Dave says: Dodgers. They have the advantage in Games 1, 2 and 5 if necessary. I don't think it's a huge edge by any means. I think Lowe and Dempster are quite similar and their numbers are comparable. Billingsley has a big advantage over Zambrano, Harden has a big advantage over Kuroda, Lilly has a good advantage over Maddux and then we're back to the Game 1 starters for Game 5. Fairly close, but overall edge to the Dodgers.

Bullpen

Joe Beimel 5-1, 2.02 ERA, 49 IP, 219 ERA+
Jonathan Broxton 3-5, 3.13 ERA, 69 IP, 141 ERA+
Clayton Kershaw 5-5, 4.26 ERA, 107.2 IP, 104 ERA+
Greg Maddux 2-4 5.09 ERA, 40.2 IP, 87 ERA+
James McDonald 0-0, 0.00 ERA, 6 IP
Chan-Ho Park 4-4, 3.40 ERA, 95.1 IP, 130 ERA+
Scott Proctor 2-0, 6.05 ERA, 38.7 IP, 73 ERA+ Takashi Saito 4-4, 2.49 ERA, 47 IP, 178 ERA+
Cory Wade 2-1, 2.27 ERA, 71.1 IP, 195 ERA+

The Dodgers have a far superior bullpen to the Cubs in general, but there are holes on both sides that are likely somewhat illusory. The Dodgers won't see Jason Marquis or Bobby Howry except in a blowout, and similarly, the Cubs won't see Greg Maddux or Scott Proctor, and possibly Chan-Ho Park. The two teams are actually closer than you might think, because Takashi Saito, the Dodgers' former closer, hasn't been quite the same since returning from a midseason injury that forced the Dodgers to give an extended look to Jonathan Broxton in the ninth. Neither team's closer is a sure thing, as their ERAs attest, but they have been good all year.

The Dodgers use Park in middle relief, though he has been decreasingly effective as the season has worn on. Despite underwhelming stuff, Cory Wade has quietly assembled an excellent season, and will likely see substantial work. The Dodgers' late decision to add James McDonald to the postseason roster could mean they intend to use him anywhere, but I include him here; like Wade, he doesn't have the best stuff, but the late callup from AA has managed to suppress offense in small samples. The Dodgers will likely call on Joe Beimel to face lefties, where he has generally been very useful.

Neal Cotts 0-2, 4.29 ERA, 35.2 IP, 105 ERA+
Bobby Howry 7-5, 5.35 ERA, 70.2 IP, 84 ERA+
Carlos Marmol 2-4, 2.68 ERA, 87.1 IP, 168 ERA+
Jason Marquis 11-9, 4.53 ERA, 167 IP, 100 ERA+
Sean Marshall 3-5, 3.86 ERA, 65.1 IP, 117 ERA+
Jeff Samardzija 1-0, 2.28 ERA, 27.2 IP, 198 ERA+
Kerry Wood 5-4, 3.26 ERA, 66.1 IP, 139 ERA+

Kerry Wood took over for Ryan Dempster as the team's closer this year. He's done a pretty good job. He's been spotty at times. 3.31 ERA, 6 blown saves, but he's allowed a measly .638 OPS. He's converted 10 of his last 11 saves.

Carlos Marmol is good at sports. That's something we'll occasionally say around my parts after Marmol has just made a few hitters look silly. He's allowed a .135 batting average against. A .507 OPS. He's allowed 4.12 hits per 9. He walks his fair share of batters and is prone to giving up the long ball. He went through a really tough stretch in June that saw his ERA balloon from 1.75 up to 3.61 prior to the All-Star break. Since then it's been only 1.29.

Bob Howry has had a pretty bad season after several stellar years as a closer and a set-up man. To give you an idea how bad it's been for Howry this year, the month of September was his most promising month. He only made 9 appearances as Lou was kind of afraid to keep giving him the ball, but 7 of those were scoreless ones in a row. Unfortunately, they were bookended by an outing on September 2nd in which he didn't record an out and allowed 4 earned runs. On the final day the season he gave up a couple runs. So in Bob's most consistent month he still managed to have an ERA of 8.10.

Neal Cotts is the Cubs LOOGY. Lefties have hit .269/.329/.522 against him this year in 67 at-bats. This has been an issue lately for the Cubs and it likely will be one at some point in the NLDS.

OTHERS: Jeff Samardzija (7th inning, groundballs, wide receiver), Sean Marshall (long/middle relief, LOOGY), Jason Marquis (long/middle relief)

Rob says: The Dodgers have a far superior bullpen to the Cubs in general, but there are holes on both sides that are likely somewhat illusory. The Dodgers won't see Jason Marquis or Bobby Howry except in a blowout, and similarly, the Cubs won't see Greg Maddux or Scott Proctor, and possibly Chan-Ho Park. The two teams are actually closer than you might think, because Takashi Saito, the Dodgers' former closer, hasn't been quite the same since returning from a midseason injury that forced the Dodgers to give an extended look to Jonathan Broxton in the ninth. Neither team's closer is a sure thing.

Dave says: Dodgers. They beat the Cubs at pretty much every spot in the bullpen.

Prediction

Rob says: (ed note: He abstained.)

Dave says: I feel that based on what I've written above I should say I think this will go down to the 5th game. But I don't think it will. I think the Cubs win this series in no more than 4 games. I'll go with Cubs in 4 because Bill James' log5 method gives the Cubs the highest odds of winning it in 4 at 22.5%. I think the Dodgers offense is improved with Manny, but it's still not equal to the Cubs lineup. The Cubs have a rather large edge offensively, as well as defensively, that I think the Cubs advance to the NLCS.

Permalink | Comments (5)

As Angels fans across Southern California settle in for a long and exciting playoff run, they’re justifiably hopeful that this year will match their success of 2002 when they won a World Championship. The Halos won 100 games this season, have the best record in baseball, and enjoy home field advantage throughout the playoffs. They acquired Torii Hunter and Mark Teixeira to augment an already potent lineup featuring Vlad Guerrero. Their starting rotation is arguably the best among the playoff participants, while their bullpen sports the all-time single season saves leader in Frankie Rodriguez. The Angels should be the favorites to at least make it to the World Series. Unfortunately, the odds are not in their favor. My opinion is not based on injuries, pitching matchups, rally monkeys, curses, or anything of that nature. It’s based on cold, hard historical data. Reviewing the playoff and World Series results since the current wildcard format began in 1995 reveals some surprising results that would make Gene Autry roll over in his grave.

Consider these facts:

• The team with the better record has won only 49% of all playoff series since 1995 (43 of 88).
• In 2001, Lou Piniella’s Seattle Mariners won 116 games and failed to reach the World Series.
• 12 other teams have won 100 games since 1995 and failed to play in the Fall Classic, including the Braves four times.
• 5 more 100-win teams played in the World Series and 4 of them lost.
• From 1995-2007, only the 1998 Yankees became World Series champs with the best record in baseball (Boston tied for the best record last year).
• A wildcard team has made it to the World Series 9 times in the last 13 years, claiming 4 world championships including 3 of the last 6.
• In 2006, the Cardinals won the World Series with only 83 regular season wins.

Basically, it appears that anything can happen in the postseason…and usually does. So, let’s break down the Angels’ chances one series at a time. Admittedly, some of the sample sizes used below are not very large, but the data reinforces just how unpredictable baseball has been in the wildcard era.

Division Series – Angels vs. Red Sox

"X - reached first on catcher's interference"

The line above has often been used in baseball box scores to denote one of baseball's orphaned statistics: catcher's interference. It is an event that happens just infrequently enough for people not to care about it, but important enough that the official scorer has to report all instances of it in the totals of a game. The play doesn't count as an at bat for the batter, but the batter doesn't get credited in his on-base percentage for reaching base safely. But a batter who came up just once in a game and reached base on catcher's interference would keep a hitting streak going. A batter reaching base on catcher's interference who comes around to score is an unearned run, but batters who reach after him are usually earned runs.

For reasons I've never figured out, I felt that it was one of my missions in life to keep track of this play on my blog, The Griddle. I note the last instance of it on the sidebar and ask people to let me know when the play occurs, which invariably happens when I'm away from a computer, out of town, or busy with some other mundane task, like eating.

The baseball rule that spells out catcher's interference is Rule 6.08(c):

The batter becomes a runner and is entitled to first base without liability to be put out (provided he advances to and touches first base) when:

The catcher or any fielder interferes with him. If a play follows the interference, the manager of the offense may advise the plate umpire that he elects to decline the interference penalty and accept the play. Such election shall be made immediately at the end of the play. However, if the batter reaches first base on a hit, an error, a base on balls, a hit batsman, or otherwise, and all other runners advance at least one base, the play proceeds without reference to the interference.

All that boils down to is that if the catcher's mitt touches the batter's bat before he completes his swing, catcher's interference is called. And when it happens, nobody, except for the batter, catcher, and umpire really knew what is happening. The umpire calls time and the batter is told to go down to first and everyone sort of scratches their head for a while trying to figure out what happened. Eventually "Error 2" will flash on the scoreboard and then everyone will be puzzled and look around. On TV, the announcers will look at replays and try to figure out what happened. And, after a few minutes, the befuddlement ends and the game goes on. (In theory, any fielder could interfere with the batter's swing and get called for interference, but such an instance hasn't turned up.)

Why does the play happen? I've never gotten a good answer from watching it happen, but I think (and this is highly speculative) that most catcher's interference plays happen on breaking balls. And they often happen when the batter makes a very late swing or the pitch comes in to a location that the catcher isn't expecting. So you end up with the combination of a weird swing and the catcher trying to grab a pitch in an unexpected location. This puts the bat and glove on a collision course of sorts.

Pitchers, who tend to have very poor swings at the plate, seem to get a disproportionate number of catcher's interference calls. Baseball-reference.com lists 64 instances of a pitcher getting on base via catcher's interference since 1956. Chris Short accounted for 11 of them and he was also the last AL pitcher to reach base on catcher's interference, back when he was playing for the Brewers in 1973.

According to David Nemec's book "The Rules of Baseball," catcher's interference wasn't put in the rulebook until 1899. Prior to that time, catchers would occasionally try to disrupt a batter's swing by tipping the bat with his glove. Connie Mack claimed that he pioneered this strategy, but that's likely because he lived a long time and nobody was going to argue with him. However, it didn't happen too often because catchers tended to stand well behind (anywhere from 10 to 25 feet) behind the batter because they didn't have much protective equipment and valued keeping their hands, heads, and ... um ... manhood ... intact. Catchers would only move in closer if there were runners on (to prevent stolen bases) or there were two strikes on the batter (catching the third strike cleanly is one of baseball's oldest rules.)

I asked Phil Birnbaum to go through Retrosheet's data to find out how often catcher's interference had been called in the years that data is available (1956-2007). And Phil even made a graph. And after studying the graph, I believe that you really can't tell much about it.

The number of instances of catcher's interference has gone up in recent years, which I think can be attributed to the increase in the number of games and better protective equipment for catchers that let them set up closer to the batter, even if it's by a couple of inches. However, the number of occurrences isn't exactly staggering, although it does happen more frequently than a complete game shutout now.

Baseball's all-time catcher's interference king is Pete Rose, who reached on catcher's interference 29 times in his career. His first one came on August 8, 1963 when Clay Dalrymple of the Phillies was nailed for it. Rose's final catcher's interference came over 22 years later on September 19, 1985 when Larry Owen of the Braves was called for it during a 9-run ninth inning by the Reds.

The single season record is held by Roberto Kelly, who got eight catcher's interference calls while playing for the Yankees in 1992. Kelly's knack for reaching first on catcher's interference earned him a trip to Cincinnati the next season in a trade that netted the Yankees Paul O'Neill.

Dale Berra of the Pirates holds the National League record for catcher’s interferences in 1983 with seven. Berra never had another CI call the rest of his career. Although Retrosheet doesn't have complete data on Dale's dad, Yogi, it appears likely that the gene for reaching on catcher's interference wasn't passed down from father to son, as Yogi has none in his stats.

Five times a player has reached on catcher's interference twice in one game. Pat Corrales did it twice for the Reds in 1965 (August 15 and September 29). The others were Ben Geraghty of the Phillies back on April 26, 1936 and also two Mariners: Dan Meyer on May 3, 1977 and Bob Stinson on July 24, 1979.

Catcher's interference has turned up in the postseason seven times, five times in the World Series. Roger Peckinpaugh of Washington was the first player to get one and it happened in the first inning of Game 7 and Peckinpaugh picked up an RBI as the bases were loaded. Rose had one in Game 1 of the 1970 World Series. George Hendrick had the last one in the World Series in Game 3 of the 1982 World Series. Richie Hebner of the Pirates (Game 3 in 1974) and Mike Scioscia of the Dodgers (Game 5 in 1985) have the only LCS catcher's interferences.

The leader among active players in catcher's interference calls is Darin Erstad of the Astros with 13. Craig Counsell of the Brewers is engaged in a neck and neck battle with Erstad with 12 CI calls. Erstad is the only player I've ever seen reach on CI in person, back on July 19, 1998 when Chris Hoiles of the Orioles knicked Erstad's bat. Or at least that's what I believe happened as I recall also that I had to stare into the sun most of the game, so pretty much anything that happened at home plate was just a rumor to me.

Edwin Encarnacion of the Reds could be the next big thing in the world of catcher's interference, picking up eight early in his career. However, Encarnacion hasn't had a single call this year and he could be losing momentum in his quest to go after Rose's record.

In Boston, since the Curse of the Bambino has been lifted, it's now time to talk about the Curse of Darren Lewis. Lewis reached first on catcher's interference back on September 13, 1998 courtesy of Tigers catcher Paul Bako. And no Red Sox player has reached on catcher's interference since then, the longest current drought for any franchise in the majors. How much longer will the people of Boston have to suffer? (My book proposal about this has gone nowhere which shows that there is a limit in the publishing world to the number of Red Sox-themed books there can be.)

There have been just nine catcher's interference calls so far in 2008. Three of them have come from Lyle Overbay who had never had one prior to this year. Carl Crawford has had two. Other players who have had one haven't fared well. Claudio Vargas of the Mets found himself taken off the Mets 40-man roster and is now playing in AAA New Orleans. Travis Hafner has been hurt most of the year. Guillermo Quiroz of the Orioles has hit .202 as a backup catcher. Milton Bradley has had a solid year, although he seemed to be getting more and more mysterious injuries after his catcher's interference on June 28.

For many players, they can have long careers and never once have a catcher's interference. Hank Aaron, Willie Mays, Cal Ripken, and Brooks Robinson are four notable players with long careers who never had an entry in the catcher's interference column on their ledger.

Frank Robinson received one catcher's interference in his long career and that came back on April 27, 1963 in Houston. John Bateman of the Colts interfered with Robinson in the seventh inning. Robinson must have been a little upset as he went and stole second and scored on an RBI single from John Edwards for the only run of the game.

There is only one documented case I know of when a game ended on catcher's interference. That was back on August 1, 1971 when the Dodgers were hosting the Reds. In the 11th inning of a 4-4 tie the Dodgers had the bases loaded with two outs and Willie Crawford up against Cincinnati reliever Joe Gibbon.

Manny Mota was on third for the Dodgers and either thinking that Gibbon wasn't paying attention to him or Crawford had no chance to get a hit against Gibbon, Mota tried a steal of home. Reds catcher Johnny Bench jumped out from behind the plate and stood in the base path to tag Mota.

This brought into play the seldom used Rule 7.07, to wit:

If, with a runner on third base and trying to score by means of a squeeze play or a steal, the catcher or any other fielder steps on, or in front of home base without possession of the ball, or touches the batter or his bat, the pitcher shall be charged with a balk, the batter shall be awarded first base on the interference and the ball is dead.

Home plate umpire Harry Wendelstedt called catcher's interference on Bench and a balk on Gibbon and Mota came home with the winning run. Rule 7.07 is peculiar because it imposes two different penalties for one act: catcher's interference, which allows the batter to reach first and the runners move up if forced, and a balk, which allows all the runners to move up one base. So how did Mota score? Did he score on catcher's interference or on a balk?

I discussed the play with Dave Smith of Retrosheet two years ago at the SABR Convention in St. Louis. And we agreed that the play had to be catcher's interference first because Crawford was awarded an RBI on the play, which he wouldn't have received for a balk.

So what have all these words taught people about catcher's interference? Likely very little. Catcher's interference is just a small freak play in the larger scheme of baseball. But it happens and you have to count it to make your box score balance. It's a loose end that you have to watch out for. You can take solace that I'm paying attention so you don't have to.

Bob Timmermann is a librarian who lives in South Pasadena, CA. He is a member of the Society for American Baseball Research. He writes about variety of baseball-themed topics at The Griddle. Some of them are even important.

Permalink | Comments (10)

Tom Petty has a song that proclaims “The waiting is the hardest part.” I think it is beyond safe to say the Tampa Bay Rays know the saying and perhaps the song quite well.

The long wait on Major League Baseball to grant the area a team, then the first season, then for the aging slugger obsession to fade out. Then for a rebuilding process that never really happened, and then finally waiting for a change in ownership. The latter happened in November 2005, but, until this year, it was more waiting, although this was different; this was reshuffling assets, this had direction and purpose.

Mainstays like Aubrey Huff, Julio Lugo, Danys Baez and Toby Hall were shipped out within a season without big-named replacements, leaving some fans wondering how much this new regime actually cared about winning. Sure, the days of Brian Meadows closing and Tomas Perez playing shortstop are terrifying in their realness, but all along the prophecy of B.J. Upton and Delmon Young soon taking over helped to soothe our qualms.

They took chances on players who others were tired of waiting on. Greg Norton, Ty Wigginton, Carlos Pena, Hee Seop Choi, Al Reyes, and the list goes on of former top prospects or useful parts that were casted aside from bigger organizations. Not too many players were willing to play in Tampa at any costs, and especially not at the price the Rays offered.

Although winning is finally here, the residuals from the waiting game are stamped all over this team with 18 of the 25 players currently on the active roster (no Carl Crawford or