BABIP: Great stat, poorly executed 

August, 26, 2010

Today's winners in Stats & Analytics:

Joe Mauer, Albert Pujols

Today's losers:

Aaron Hill, Josh Hamilton, Trevor Hoffman

Smart baseball fans know about batting average on balls in play, or BABIP. Smarter fans should forget everything they've ever learned about it -- and I'm going to tell you why.

One of modern sabermetrics' fundamental discoveries is that pitchers have much less control over balls put into the field of play than they do over strikeouts, walks and home runs allowed. This has led to a whole new way of looking at pitchers, beginning with defense-independent pitching statistics. It has also led many pseudo-sophisticated analysts to mistakenly assume that any batter with a BABIP higher than league average must be lucky and therefore likely to decline. And that, in turn, has added to the mainstream backlash against using advanced stats at all.

Last month, for instance, Mets announcer Gary Cohen, normally an astute observer of the game, said, "David [Wright] has struck out a ton this year. Struck out 91 times. And yet he's hitting well over .300. Now, one of the stats that the sabermetrics people like to throw at you is batting average on balls in play. And if you have a particularly high batting average on balls in play, they like to think that … it shouldn't be that high, which means you're having a fortunate year and you'll come back down again. … To me that doesn't make any sense. Certain guys hit the ball harder than other guys hit it. Certain pitchers induce more ground balls or more weakly hit balls than others. That's part of what you're trying to do." Ron Darling, another smart guy, agreed with Cohen: "I think that for the average hitter, to have a high average putting balls in play, it's probably because they do have some lucky hits. But certain hitters, like Wright, hit the ball hard almost all the time." (Hat-tip: Dan Lewis at Amazin' Avenue, who posted the exchange as part of his excellent essay, "It's Time To Stop Using BABIP.")

Of course, Cohen and Darling were wrong to dismiss regression to the mean (and randomness in general) -- a huge factor in any hitter's batting average that BABIP helps illuminate. But it would also be wrong to assume that there's no skill at all in generating a high BABIP. To take an obvious example, Ichiro is batting .348 on balls in play this season. Are his 37 infield hits the product of luck? Or James Loney -- should we expect him to take a step back in 2011 just because he has an above-average .309 BABIP this year? Thing is, Loney has a career BABIP of .313. Ultimately, the relationship that's most revealing is not a hitter's BABIP to the league average but a hitter's BABIP to his expected norm.