January 25, 2020

Which College World Series Teams Play Moneyball the Best?

June 12, 2014 by · Leave a Comment 

Nearly all discussion of the Moneyball/sabermetrics revolution in baseball has centered on MLB. As part of this revolution, teams such as the Boston Red Sox and Oakland A’s have enjoyed success over roughly the past decade with data-based approaches to the game that emphasize certain principles. These principles include getting on base (with walks being valued more than they used to be), treating offensive outs as precious commodities not to be given away lightly, and, as Earl Weaver, a forerunner of modern sabermetric-based management, would say, waiting for a three-run homer.

Do these same strategies work in college baseball? I could find relatively little written on the issue, this article about Kent State’s devotion to sabermetrics being a rare example. With this year’s NCAA College World Series getting underway on Saturday, now seems like a good time to examine the issue. I have thus compiled seven sabermetrics-relevant statistics for each of the eight teams participating in the CWS. (One of the teams is first-time participant Texas Tech, where I’m on the faculty, so that has heightened my interest!) Teams’ statistics can be obtained via their respective university athletic websites or their conferences’ websites (here are links for the Big 12 and SEC, which have the most teams going to Omaha).

Four of the seven statistics come from a feature on ESPN.com known as the “Beane Count,” a collection of stats developed by Rob Neyer and named after A’s general manager Billy Beane. Since 2002, the Beane Count has tracked MLB teams’ performance in the areas of own and opponents’ home runs and walks drawn. (For walks given up to opponents, most sources report this statistic per nine innings, so I used this number instead of total walks yielded.) A well-functioning sabermetric team should accumulate many homers and walks and allow few of each to its opponents.

To these four statistics, I added three: slugging percentage (a broader reflection than home runs of hitting for extra bases), bunts (which should be low, as they intentionally give away an out), and stolen-base attempts (which, at the MLB level at least, require a very high success rate to break even, so should generally be avoided). Regarding bunts, I used the statistic listed as “SH” (sacrifice hit), which appears to apply mainly to successful bunts (see the MLB rule). I would have liked to have had data on sacrifice-bunt attempts (e.g., including someone who strikes out attempting to bunt), but I couldn’t find such a measure.

The following set of graphs shows how the eight teams in the upcoming CWS fared during the season on the seven statistics (statistics are for all games up until now, not just conference games). Because the seven stats have vastly different scales of magnitude (e.g., a team could have hit 30 home runs and have a slugging percentage of .400), I have converted all of the values to z-scores. These have the advantage of putting all statistics on a common metric, on which 0 represents average performance. On the graphs, it would be considered optimal for a team to have high values for statistics shown against a white background and low values for statistics shown against a gray background.

college moneyball
Arguably, four of the eight teams approach the offensive ideal of Moneyball and sabermetrics. For context in interpreting the following numbers, each CWS team has played between 62-68 games thus far. Relative to the eight-team CWS field, Texas Tech is above average in hitting home runs (30), slugging (.409), and drawing walks (257); well below average in trying to steal (35 attempts); and below average in bunts (48).

Mississippi (Ole Miss) appears to have the best power-hitting in the CWS field (42 HR, .421 SLG) and rarely bunts (36). However, the Rebels also rarely walk (211). Virginia has some home-run power (33) and ability to draw walks (274). The Cavaliers are also a little below average in number of stealing attempts (83) and a little above average in use of the bunt (75). Louisville has some modest power (32 HR, .401 SLG) and bunts slightly less (60) than the average CWS team.

Texas coach Augie Garrido, as a five-time CWS winner (twice with the Longhorns) and proponent of a “small-ball” approach that includes drawing walks (271) and bunting (96), contradicts much of the Moneyball/sabermetric approach. Where the Longhorns really stand out, however, is in the rarity with which they give up the long ball (only six allowed all season).

Texas Christian (TCU) has below average power (13 homers and .358 slugging), but is slightly above average in drawing walks (252) and attempted steals (125). Horned Frog pitchers are among the best in the CWS field in limiting opponents’ walks (143). Vanderbilt is a hard team to figure. The Commodores are average in most of the categories examined here, except that they like to try to steal (143 attempts) and their pitchers are more prone than average to giving up walks (218).

Finally, the University of California, Irvine, is well below average in hitting for power (only a dozen dingers and .352 slugging) and in drawing walks (200). The Anteaters are, however, the only team playing in Omaha that is really strong at preventing both opponents’ homers (9) and walks (131). Some might argue that UCI’s Big West conference competition is not as strong as that encountered in the Big 12, SEC, and Pac 12, for example. Still, the Anteaters’ league schedule includes traditionally strong opponents Cal State Fullerton and Long Beach State.

One caution in comparing the eight CWS teams is that their schedules during the season were not necessarily of equal strength. The safest comparisons would appear to be between members of the same conference, such as Texas, TCU, and Texas Tech of the Big 12, and Mississippi and Vanderbilt of the SEC.

On to the College World Series, to see how these formulations turn out!

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Alan Reifman is a professor at Texas Tech University and author of the book Hot Hand: The Statistics Behind Sports’ Greatest Streaks (Potomac Books).

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