FanGraphs takes a hack at BABIP

By this point in the baseball season, you've probably heard about batting average on balls in play, or BABIP. We're almost four months in, so how could you not? It's seemingly the new vogue stat of the season, used somewhat loosely to quantify luck.

The basic idea, if you're not familiar with it, is that a hitter whose BABIP is trending much higher than his career rate or the typical range (around .300) is due for a fall; it means he's getting more balls to fall in for hits than usual, and that will eventually stop. Likewise, a pitcher whose BABIP is extraordinarily high is getting burned either by bad luck or a defense that doesn't have the range to turn would-be hits into outs.

There's one problem with the stat, though; it treats all hits the same. So in that sense, if you think batting average is a flawed stat, you have to treat BABIP with the same skepticism. That's what this FanGraphs post suggests, anyway. Definitely worth a read, especially for the Crash Davis philosophizing.

I use BABIP plenty; heck, I used it this morning in a post about Matt Capps and the Nationals' bullpen. And while there's something to be said for Capps converting saves even in the face of a high BABIP, he isn't just sweating out saves because of bad luck. He's also giving up a homer on 11.1 percent of his fly balls, which is much closer to his 2009 rate (13.8%) than it is from his best years in Pittsburgh (4.4% in 2007 and 6.8% in 2008). The point is, not every hit is equal, and players' skills and tendencies have to be factored in.

So is there a better stat out there? The FanGraphs post suggests using something like expected batting average, and phrasing it in terms of a range. That has its drawbacks, too, especially if you're opposed to batting average as a whole. And I'm not suggesting that BABIP doesn't have its merits. But the article caught my eye, and got me thinking about taking a closer look at some of these statistics, so I just thought I'd pass it along.

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Comments

I wonder about baseball statistics that are calculated out to 3 or 4 significant figures. I'd feel a bit more comfortable talking about % than 3 or 4 figure decimals when looking at an estimate of future performance.

As for BABIP, I think at least one of the comments (and other sources) say that it is more predictive for pitcher performances than hitters. Hitters can sustain above .300 or below .300 BABIP for a career because of factors like speed, strength, contact skills, mix of GBs and FBs. You would expect Ryan Zimmmeran to have worse luck on ground balls than Nyjer, for instance. With respect to pitchers, I believe that it has been shown that certain types of pitchers can sustain BABIPs above or below average. Long term closers and lefty groundball pitchers I think are two.
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I think you're probably right about it being more valuable for pitchers than hitters, JCA, and an interesting point about closers and lefty groundball pitchers. That's probably because both of those types of pitchers excel at generating weak contact with their pitches. It was one of the things people were discussing with John Lannan - did his low BABIP figures indicate a regression was coming, or is he that good at generating weak contact? I don't know that we've completely got the answer to that question yet; I don't believe his struggles this year are thorough evidence of a regression. But it'll be interesting to watch.

Ben

Interesting. Statistics like BABIP basically theorize that whether a batted ball falls in for a hit is total luck.