Baseball Beat March 15, 2011
Graphing the Pitchers: LOB% and BABIP

Thanks to the work of Voros McCracken and later Tom Tango, Defense Independent Pitching and Fielding Independent Pitching have become widely accepted in the baseball community as better measurements of pitching effectiveness (and predictability of future results) than earned run average (ERA). DIPS and FIP focus on strikeouts, walks, and home runs — the three primary outcomes that a pitcher controls. Except for perhaps catchers, fielders have no impact on these events.

While SO, BB, and HR play a large part in determining ERA, the latter is also a function of defensive and bullpen support, as well as performance with bases empty vs. runners in scoring position. As a result, the difference between ERA and FIP is almost entirely accounted by strand rate (LOB%*) and batting average on balls in play (BABIP). Each variable has a coefficient correlation of nearly 80 percent with the delta between ERA and FIP.

* Based on the formula, the strand rate is an estimator of LOB% rather than an actual tally.

When you put the two together (LOB% divided by BABIP), the coefficient correlation jumps to 90 percent. Accordingly, the coefficient of determination or R² is 81 percent. In other words, more than four-fifths of the difference between ERA and FIP is due to LOB% and BABIP. As such, in addition to SO, BB, and HR rates, it makes sense to study LOB% and BABIP to understand why a pitcher's ERA may be better or worse than his FIP.

The MLB averages for LOB% and BABIP have been running at almost exactly 72 percent and .300, respectively, for several years. These percentages held true once again in 2010.

Plotting LOB% on the y-axis and BABIP on the x-axis for all 147 pitchers who threw at least 100 innings in 2010, I created the following graph. As has become customary around these parts, I broke the graph into quadrants via the intersection of the LOB% and BABIP means. The pitchers in the northwest quadrant had high LOB% and low BABIP. Moving clockwise, the pitchers in the northeast quadrant had high LOB% and high BABIP, the hurlers in the southeast quadrant had low LOB% and high BABIP, and those in the southwest quadrant had low LOB% and low BABIP.

The numbers were lifted from FanGraphs in January. The BABIP data was subsequently recalculated, perhaps due to FanGraphs using an incorrect formula initially. While directionally correct, the BABIP used for this graph are generally about .005-.010 higher than those listed on the site now. The LOB% data matches exactly. You can download the spreadsheet with the applicable data here.

As usual, I have identified the outliers in all four quadrants in the graph above. In addition, as shown below, I have created lists of leaders and laggards for both LOB% and BABIP. For perspective, the ranges on LOB% and BABIP were 59.5-82.7 percent and .238-.354, respectively.

Starting with LOB%, I highlighted the six pitchers with strand rates over 80 percent and compared 2010 with their career marks. All but Madison Bumgarner (who pitched just 10 innings prior to last season) have career LOB% that are well below their results in 2010. That said, I found it interesting that the career rates were all above the MLB norm of 72 percent.

Roy Halladay, Cole Hamels, Brian Duensing, Tim Hudson, and Tommy Hunter all posted career high LOB%. Halladay had only exceeded 75 percent twice before last year.

In addition to sharing high LOB%, the common thread among these pitchers is that they fared better with RISP than with the bases empty.

There were 11 pitchers with strand rates of 65 percent or lower. Excluding John Ely (who was a rookie), all but Luke Hochevar have career LOB% that are well above their results in 2010. Nonetheless, I found it as equally interesting as the observation from the leader board that the career rates were all at or below the MLB norm of 72 percent.

Nate Robertson, Tim Wakefield, Ryan Rowland-Smith, Jeff Francis, and Paul Maholm all posted career low LOB%. Scott Feldman, Jeremy Bonderman, and Tony Pena produced the second-lowest LOB% while Jamie Moyer had the third-lowest since he broke into the majors in 1986.

In addition to sharing low LOB%, the common thread among these pitchers is that they fared worse with RISP than with the bases empty.

Turning to BABIP, I spotlighted the 14 pitchers with averages under .270 and, like LOB%, compared 2010 with their career marks. All of these starters (including Armando Galarraga who actually posted a .261 BABIP based on FanGraphs' revised calculations) have career BABIP that are above their results in 2010. Of note, the career rates were all below the MLB norm of .300.

Matt Cain has never had a league-average BABIP and, in fact, has not exceeded the .278 he allowed in 2007.

Hudson and Hunter appear on the most favorable LOB% and BABIP lists. Moyer, on the other hand, was the only pitcher to appear on a leader and laggard board.

There were 16 pitchers with BABIP higher than .330. All of these pitchers have career BABIP that are below their results in 2010. In five cases, the career marks are slightly below the MLB norm of .300. The balance are all higher.

Maholm and Feldman appear on the least favorable LOB% and BABIP lists.

Here is the same graph presented with a best-fit trendline. As shown, it slopes from the northwest quadrant down and to the right through the intersection to the southeast quadrant. Generally speaking, the lower the BABIP, the higher the LOB%, and the higher BABIP, the lower the LOB%.

The outliers in the NWQ were the pitchers who benefited the most from high LOB% and low BABIP. Here are the pitchers with the highest ratios of LOB% divided by BABIP:

Six of the above pitchers ranked in the top seven in ascending order in ERA minus FIP (E-F), meaning they had better ERAs than FIPs. The other four placed 11th, 17th, 27th, and 28th (out of 147 pitchers who threw at least 100 innings in 2010).

Conversely, the outliers in the SEQ were victimized the most by low LOB% and high BABIP. Here are the pitchers with the lowest ratios:

Seven of the above pitchers ranked in the top ten in descending order in E-F, meaning they had worse ERAs than FIPs. The other four placed 17th, 19th, 21st, and 22nd.

Interestingly, the outliers in the NEQ and SWQ neither benefited nor were victimized in the aggregate as the abnormal percentages in each category basically offset one another. As an example, Moyer, a SWQ outlier, had an ERA (4.84) minus FIP (4.98) of -0.14.

There are several takeaways embedded in this study, some of which are more obvious than others:

• LOB% and BABIP explain over 80 percent of the difference between ERA and FIP.

• High LOB% and low BABIP will deflate ERAs. Low LOB% and high BABIP will inflate ERAs.

• LOB% appears to be more highly correlated with how a pitcher performs with RISP vs. the bases empty than bullpen support.

• Pitchers with extreme LOB% and BABIP will tend to regress/rebound toward their career marks the following year but not necessarily all the way to the MLB averages.

There are also a few questions: Is the discrepancy in performance between RISP and bases empty due to a pitcher's ability to work from the windup as opposed to the stretch? Do certain pitchers have an extra gear that they can employ when the going gets tough? Is there a self-fulfilling prophecy at play here, a Yogi-ism where pitchers perform well until they don't perform well? The answers to these questions could go a long way toward understanding how much skill or luck is involved in the year-to-year fluctuations in LOB%.

Courtesy of Dave Studeman of The Hardball Times, you can read more about LOB% here and here.

The correlations, nicely developed and examined here, are crystal clear. What is less clear is what is cause and what is effect. We need to beware the thought that wind comes from trees waving their branches.

How about how well a pitcher does at pitch location? That might be the key to the cause and effect. Pitchers who locate their pitches better and make a batter hit the pitcher's pitch instead of the batter's pitch will most likely be more successful or, as this pitcher put it:

"I was pitching to contact. I was trying to make the guy hit the ball. I didn't want to throw any cripples in there but I wanted the batter to hit it. Hit it right away, by all means. But you're hitting my pitch, not yours." - Bob Gibson.

Perhaps the rule of real estate applies to all of this: Location, location, location.

It would be interesting to see a graph of pitch location/BABIP and of pitch location/LOB%.

FIP is new to me (and is not exactly a centerpiece of this article), but I used the link, tried the link from there to Fangraphs and tried running some charts over time. I selected 1920-2010 (reasonable I think), and then sorted on FIP.

I got results which made no sense (Lefty Grove was ranked 63rd, Sonny Siebert 60th, Larry Jackson 51st, Maddux 3th, Koosman 36th, Fritz Peterson 34th, Nolan Ryan 5th.)

I'm not saying I understand it (I don't) or that it's wrong, but any thing that says it measure pitchers effectiveness and says a guy who won 9 ERA titles isn't as good as Fritz Peterson has to be explained.

I apologize for any derail this may cause.

Eric, no stat is perfect. All have their flaws and shortcomings as well as their strengths. FIP is one of those. It is true that pitchers can not control fielding unless the ball is hit to them, they do influence greatly how a ball is put into play. Pitchers who locate well, get the batter to swing at the pitch they want the batter to swing at instead of giving the batter the pitch the batter wants to swing at, etc., are the pitchers that will have the success.

Is FIP a good stat and useful? Yes, but it is far from perfect. However, don't dismiss it because it is not perfect.

Xerac, I did not mean to suggest that anything should be dismissed.

Let me say this a bit differently:

Fritz Peterson had a careen normalized ERA of 101 (average), Lefty Grove was around 148 (about the best ever, if not the best.)

Here is a relevant quote

"•LOB% and BABIP explain over 80 percent of the difference between ERA and FIP" [I presume this could just as well say Normalized ERA as opposed to ERA].

Now, I truly think ERA is a fairly misleading stat. I think normalized ERA is much better, but also has flaws if one is not content with a broad brush.

To have Peterson achieve the 34th FIP of the modern era (last 90 years) while Grove is 63rd 'might' mean that FIP is inaccurate or that BABIP and LOB% are grossly disparate between these 2 players. I'm not suggesting either is true or that there aren't other answers. I'm just suggesting that this variance needs to be explained in light of those measures. For example, maybe Lefty was incredible at stopping rallys, but Fritz stunk.

Again, I apologize if this appears to dismiss the metrics or the article.

Eric, I see what you're driving at. There obviously has to be more to the story. I think FIP is a good stat but I also believe that pitchers have a great deal of influence on fielding. How a ball that is hit fairly is put into play is greatly influenced by the pitcher.

Yes, ERA is a greatly flawed stat. That is why ERA+, etc., are such great tools in helping evaluate pitchers better.

No stat is perfect but if you use a combination of various stats you get a complete picture.

Eric, baseball-reference has Grove's lifetime ERA at 3.06, 130th.
Meanwhile, FIP ranks him higher.

http://www.baseball-reference.com/players/g/grovele01.shtml

His "WAR for Pitchers" lifetime is ranked 7th.

so, which stats are more flawed?

Also note that he pitched against some extreme Yankee teams. That's likely a lot of Home Runs Against for him.

Maybe FIP+ would provide a better picture, seeing as every other pitcher i the league (except yankee pitchers) had to pitch against yankees.

My post was "normalized ERA", not ERA.

Grove is 4th. Excluding Mariano Rivera-reliever, Devlin- 1870's pitcher and depending on where Pero Maritinez is when his career ends, Grove would show as 1st or 2nd on most lists.

Peterson is tied with 40 others for 671st spot.

WAR has Grove at 7th and Peterson at 573rd.

So, again since both WAR and NERA are well respected tools, it does not say FIP is wrong, but says it needs more explanation. I am good with it as long as it is combines with LOB% and gives us something that resembles reality.

Does anyone think that we can't find 50 quotes saying Lefty was the best ever by people who played against him? How many will we see for Fritz? If FIP is right, (it may well be 100% correct) then something like LOB% must be the rest of the story, no?

I think a shoutout should be given to Tom Tippett for his awesome study of DIPS on the old Diamond Mind site (his studies used to be there, but my last search found it posted on some other site, probably a mirror), which showed that while DIPS applied to most pitchers, there ARE pitchers who can control their BABIP to great effect. He also went through and analyzed how certain pitchers delivered value through their pitching.

TangoTiger later said that it takes 6 full seasons worth of IP for a starter to have enough to statistically significant show that his BABIP is controllable. And Cain is basically there now, his BABIP would have to be waaay over .300 to bring his career BABIP to .300. Zito has already passed that threshold.

Great article as usual, always look forward to seeing this each year.