Designated HitterOctober 14, 2005
Not a Prospect List
By Boyd Nation

Opening disclaimer: I love Baseball America. I've been a subscriber for years; I read it cover to cover when it comes in (OK, not really cover-to-cover, since the old media guys in the front put me to sleep, but you know what I mean); I've built a small shrine to it in my basement.

Nonetheless, Baseball America has been the source of one of the great evils of our time -- the prospect list. We all know why they do it, of course; people like lists, and they like feeling like insiders, so prospect lists move copies. There's nothing inherently wrong with that, but these lists need to be kept out of the hands of people who make actual decisions, because they're reversing the process. It's the result of what I've heard called The Halo Effect.

Let's look at a couple of players:

    Year 1   Year 2   Year 3
  League   Stats   League   Stats   League   Stats
A   California   .341/.414/.540   Southern   .252/.387/.514   PCL   .346/.433/.500
B   California   .302/.379/.527   PCL   .283/.329/.422   NL   .267/.321/.391

Now, there is an age factor here, as A was a year older than B in the years represented (although they're the same age in real life), but it's interesting how these tracks went, especially since they were both seasoned college players and not teenagers when they turned pro. A is Jon Knott, and Year 1 for him is 2002. Player B is Xavier Nady, and Year 1 for him was 2001. There is no reason in what's shown here that Nady should have been moved faster (or, since this isn't really about Nady, that Knott should have been moved slower). However, Nady was a second round draft choice who had been on every prospect list on the planet, while Knott was an undrafted free agent no one had ever heard of, so not only did Nady move faster up the ladder, he spent another year in San Diego in 2005 while Knott wandered in the wilderness of the PCL again. The Halo Effect does its damage, and prospect lists are one of the root causes of that.

All of this is a long prelude to what could, if you don't look closely, be mistaken for a prospect list. There is a difference, but feel free to laugh at my inconsistency for a moment if you wish. What follows is actually what the decision makers should be looking at, or at least a variant of it; it's a performance list. What follows is the list of the top performances by my favorite evaluation measures for college players by last year's sophomore class. The difference in this and a prospect list is that I haven't talked to anyone, much less a scout, I've never seen most of these guys, and the next time I use the word "toolsy" will be the first.

First, the hitters. These guys are ranked by AOPS (adjusted OPS), a stat of mine which takes traditional OPS and adjusts them for park factor and strength of schedule faced.

Team   Name   OBP   SLG   OPS   AOPS
Florida   Matt Laporta   .438   .698   1.136   1.257
Florida State   Shane Robinson   .532   .605   1.137   1.239
Pepperdine   Chad Tracy   .428   .609   1.037   1.239
Mississippi   Mark Wright   .407   .583   0.990   1.223
Lamar   Michael Ambort   .414   .654   1.068   1.173
Mississippi   Chris Coghlan   .430   .516   0.946   1.169
Georgia   Josh Morris   .405   .541   0.946   1.166
Texas Christian   Shelby Ford   .479   .578   1.057   1.160
Mississippi   C. J. Ketchum   .481   .457   0.938   1.159
California   Brennan Boesch   .436   .567   1.003   1.157
Arkansas   Danny Hamblin   .419   .584   1.003   1.142
Pittsburgh   Jim Negrych   .471   .694   1.165   1.142
Tulane   Mark Hamilton   .452   .599   1.051   1.130
Miami, Florida   Jon Jay   .490   .531   1.021   1.125
Cal State Fullerton   Brandon Tripp   .436   .556   0.992   1.117
Georgia Tech   Wes Hodges   .466   .566   1.032   1.115
Oregon State   Mitch Canham   .423   .531   0.954   1.114
Texas Christian   Chad Huffman   .437   .573   1.010   1.108
San Diego   Shane Buschini   .450   .538   0.988   1.096
Rice   Josh Rodriguez   .411   .555   0.966   1.092
Virginia Commonwealth   Scott Sizemore   .464   .673   1.137   1.092
Cal Poly   J. J. Owen   .398   .588   0.986   1.083
Santa Clara   Robert Perry   .427   .556   0.983   1.079
Georgia Southern   Justin Klinger   .464   .591   1.055   1.075
College of Charleston   Chris Campbell   .421   .625   1.046   1.069

Now, you heard what I said earlier about talking to scouts, right? There's a temptation here to push the word count up by trying to offer a pithy comment about each of these guys, but that's not what we're doing here. These are the guys who have performed, and no one should care if they're strapping young hunks of manhood or guys who look up to Quasimodo, or would if they could keep up with him.

So, on to the pitchers. These guys are ranked by another creation of mine that I call RBOA (Runs Below Opponent Average), which is exactly what it sounds like. Because RBOA is a counting stat, it is affected by playing time issues, so sophomores who make their way into the rotation at midseason will suffer in this list. On the other hand, the college season is short enough that a pitcher who's only been in the rotation for half a season hasn't really provided enough of a sample size to be judged, so I think I'm OK with that.

Team   Name   RBOA
Texas   Kyle McCulloch   56.63
Missouri   Max Scherzer   53.76
Nebraska   Joba Chamberlain   48.61
Oregon State   Jonah Nickerson   44.41
Winthrop   Heath Rollins   42.10
Florida State   Bryan Henry   41.65
Southeastern Louisiana   Bernard Robert   41.44
Texas   Randy Boone   41.20
Middle Tennessee State   Matt Scott   40.13
North Carolina   Robert Woodard   39.79
South Alabama   P. J. Walters   38.37
Oregon State   Dallas Buck   38.33
UC Irvine   Justin Cassel   37.80
Washington   Tim Lincecum   37.26
Clemson   Stephen Faris   36.84
Wichita State   Noah Booth   35.15
Miami, Ohio   Keith Weiser   33.50
Georgia Tech   Blake Wood   32.48
San Diego State   Bruce Billings   32.00
Baylor   Cory Vanallen   31.70
Central Florida   Tim Bascom   31.55
Arizona   Mark Melancon   31.54
Army   Nick Hill   31.05
North Carolina   Andrew Miller   30.69
Baylor   Jeff Mandel   29.36

These, therefore, are the guys you want to start your watch list for next year with, although in this case there is a caveat. College pitchers often carry a tremendous workload, especially when measured with pitch counts. If that's something that concerns you, either professionally through your organization's stance or personally through your fantasy philosophy, do your homework on that front as well.

See, two perfectly good lists of players to watch, and I didn't use the word "gamer" once.

Boyd Nation is chief cook and bottlewasher at Boyd's World, a college baseball stats and analysis site, and provides college baseball data consulting to an undisclosed number of major league teams. In real life, he's an information security guy with a beautiful wife and three great kids in Birmingham, Alabama.


Those are two good lists indeed. For my money, I would want to create such lists by position, scout the top ten or twenty at each spot with more attention in terms of numbers and time paid to SS and CF than, say, 3B/1B or LF. In other words, combine the best of performance analysis and scouting when evaluating the pros and cons of prospects.

I would also take a disproportionately large number of pitchers while balancing my total picks between college and high school players so as to diversify one's portfolio by age, experience, upside and downside.

But, no matter what, I would want to start with lists like the ones you've developed so as not to completely waste my time beating the bushes looking for players who you might hope will perform some day.

But, no matter what, I would want to start with lists like the ones you've developed so as not to completely waste my time beating the bushes looking for players who you might hope will perform some day.

The implication that teams that don't use stat-based lists instead just "beat the bushes" looking for players is both ridiculous and insulting. Teams have been scouting the college ranks successfully without using stats for years.

No wonder you signed your name Anonymous you little prick, the implication is that teams that don't look at bottom-line performance as represented by statistical analysis, in deference instead to "potential" or "skills" or "makeup," end up looking at players whom "you might hope will perform some day."

Teams have been scouting the college ranks unsuccessfully by not using stats for years.

Even the first round of the free agent entry draft for years has been filled by potential-skills-makeup guys whose careers went nowhere because no one thought to value their actual (lack of) performance.