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November 23, 2009

Checking the Numbers

Fielding Distrust

by Eric Seidman


The increased relevance of defensive metrics in recent years has led to a bevy of cost-cutting activity across the league, as teams are beginning to exhibit a greater understanding of the value of saving runs with the glove. Solid defense is tantamount to success, but it does not translate to deeper bank accounts like the mighty whopping stick. Even amongst some statistically savvy fans, offense garners more value than defense for reasons like the perceived irrefutability of batting data in comparison to fielding subjectivity, how the goals of fielding metrics seem to be more abstract than the what-you-see-is-what-you-get numbers on offense, and how advanced defensive statistics are still fairly new additions to the baseball vernacular. Subjectivity creates doubt, which leads to distrust and skepticism, making it difficult for some to wrap their heads around how a relatively mid-pack player Mike Cameron (4.8 WARP1) could actually have been more valuable than a masher like Jason Bay—4.4 WARP1.

The basic reason for this ranking reversal is that most of Cameron’s value is tied up in his value on defense. The doubt surrounding how valuable that is, however, leads to "yeah, but…" statements issued with the intention of knocking his performance down a few pegs. Admittedly, statistics like UZR, FRAA, and Plus/Minus should not be treated as gospels, but their different, rigorous methodologies paint fairly accurate portraits of player value, and are worthy of acceptance as evidence. Changing everyone's mind on the subject will not be achieved overnight, however, so to expedite the process, it's worth exploring the reasons for doubt as well as why the data can clash with personal opinions of fielding prowess on occasion, because in the end subjective evaluations seem to comprise the leading source skepticism thrown in the way of advanced fielding metrics.

Comparative Confusion

The aforementioned statistics are not natural analogs for commonly used numbers like batting average or home runs. The outcomes are not binary, but they are much more straightforward and easy to comprehend. The defensive equivalent in this regard is fielding percentage: the play was made cleanly, or an error resulted, with no gray area in between. [Ed. note: In the official scorer's opinion.] We know that fielding percentage is practically worthless as an evaluative metric because errors are not always bad—perhaps a shortstop records an error on a ball that half the league wouldn't even reach—and due to several other factors looming large in the nuts-and-bolts foundation of what constitutes a solid fielder, that gray area matters more than anything else. Other factors interfere as well, specifically involving the exclusion of baselines.

For instance, a .280/.380/.540 slash line looks fantastic, and it will be treated as such regardless of whether or not the league average was .260/.360/.515; evidence of this phenomenon can be found in Marc Normandin’s fantasy articles involving first basemen, where the replacement level for the position is so high that hitters deemed superb in a vacuum do not rate all that highly once they're evaluated within the appropriate context. Certain statistics normalize data for these situations, but not everyone measures performance from a relative standpoint. Even if they did, it is much easier to conjure up an image of an average or replacement-level hitter than to qualitatively figure out what an average fielder looks like, making difficult the task of pinning down what we even want to measure and how to structure the results.

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