22 11 2009

The revolution of statistical analysis in baseball has completely changed the way that I’ve followed the sport. I was introduced to sabermetrics initially after reading Moneyball by Michael Lewis. Although it gave me a newfound interest in GM Billy Beane [who’s name I’ve exhausted amongst all of my friends], there was no added outside interest in baseball statistics. Besides occasionally rooting for the Oakland A’s I still followed baseball in relatively the same way. Everything changed in the summer of 2008 when I was introduced to The site, run by Parks and Recreation creator Michael Schur, took bad baseball journalism and hilariously critiqued them [I adopted their method for my posts regarding Scott Soshnick]. It was there that I learned about sabermetrics and the importance of statistics in baseball. From there I learned about Bill James and the Baseball Prospectus team. I’m going to try and give the short version of the common misconceptions of baseball statistics. I’m certainly no genius when it comes to this subject [or on any subject really], but I’ll make sure to point you in the right direction for places that define it better. When I talk about this subject, I tend to harp on the side of absolutism. That’s what gets me into trouble when I try and convince my friends that they’re misinformed [it never really goes well.]

Here are two common misconceptions about baseball statistics.

1. Batting average is not a good measurement of a players value. Guys like Juan Pierre and Ichiro can have very high batting averages, but they’re not as good as people think because they just hit a lot of singles. Simple stats like OPS are a far better indicator of a batter’s value.

2. Striking out isn’t the worst thing in the world. People think guys like Adam Dunn and Mark Reynolds are bad because strike out at very high rates. But a strike out is just another out. As long as they are hitting a crap load of home runs [which these two guys do] then it doesn’t matter that they strike out. Read this Fire Joe Morgan post to help you understand what I’m talking about.

My new favorite site for baseball statistics information is They specialize in win probability and have in game updates on the percentages that each team has to win the game.

Here are two glossarys that I would recommend that help explain the complicated statistics that are the best evaluations of a players value:

On Fangraph’s glossary make sure to check out the definitions for Cluth, FIP and WPA.

On Baseball prospectus’s glossary make sure to check out the definitions for VORP, WARP, and EqA,



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