My introductory post on the topic of luck/randomness (or stochasticity -- Ivy League education right there) in baseball focused a lot on the degree to which small changes in the positioning of the bat and the ball can produce large differences in result. Not only that, but slight changes in the positioning or movement of the fielders (like A-Rod giving one too many winks to the blonde in the third row) can also make the difference between an out and a single. The most basic tool that we can use to assess how these random events have affected a hitter’s performance is Batting Average on Balls in Play (BABIP).
BABIP, unsurprisingly, measures a player’s batting average on those at-bats in which he puts the ball in play (i.e. NOT a walk, strikeout, hit-by-pitch, or home run), putting the outcome of the at-bat up to the positioning of the fielders relative to the ball. Each player’s skill set contributes to where his BABIP will tend to fall, as faster players beat out more grounders and thus have a higher BABIP, while sluggers tend to be slower and hit more home runs, reducing their average BABIP. Over the course of a single player’s career, however, there can be pretty strong variability in the stat due to the positioning of fielders when he is at bat, as well as simple luck.
Here’s an example of the effect that BABIP can have on performance from year to year. Take Ichiro Suzuki, a guy who has been around as long as he has because of his ability to get a lot of hits with his speed. His average BABIP over his career has been .350, which is about 50 points above the league average in that span. To make this a more appropriate discussion, I’ll disregard the past two seasons, in which his age has caught up to him and his batting average dropped 50 points from his career average. From his rookie year in 2001 to 2010, Ichiro’s worst BABIP was .316, and his best was .399, representing pretty large deviations from his career numbers. These seasons also correspond to his worst and best batting-average seasons, at .303 and .372, respectively. In fact, the r2 value between Ichiro’s BABIP and batting average, or the percentage of variance in batting average that can be explained by BABIP, is 97%, meaning that almost all of Ichiro’s year-to-year changes in batting average can be explained by the weird stuff that happens once the ball hits the bat.
How can we use BABIP to our advantage? Let’s take my fantasy team, for example. The only reason I drafted Tigers catcher Alex Avila this season was because he represented a great value, but I wasn’t happy about it. Why? He hit .295 with 19 homers and 82 RBI while only playing 140 games because Victor Martinez played some catcher. This season, Martinez is hurt and they add Prince Fielder – slam dunk, right? I was skeptical. Avila’s BABIP in 2011 was .366, 90 points above what he posted in 2010, his only long stay in the majors. Regression to the mean would probably put Avila’s BABIP at more like .310, cutting his batting average by a solid 50 points, and thus bringing his run and RBI totals down as well. What has actually happened? He’s on pace to hit .225, 19 homers, and 56 RBI this season, a significant downgrade from a breakout 2011.
I would be remiss not to mention that BABIP can be just as useful for pitchers as for hitters. While skill set doesn’t really come into play with pitcher BABIP (most players’ career rates center around .290 to .310), the concepts of luck and fielder ability still apply, and perhaps more consistently than with hitters. For example, there was controversy as to whether Rays pitcher Jeremy Hellickson’s 2.95 ERA in 2011 could be maintained given the .223 BABIP against him. However, if you look deeper, his low BABIP is as much about the Rays’ team fielding prowess as it is about good fortune. Among Rays pitchers with at least 40 IP, no one had an opponents’ BABIP higher than .284.
Cubs ace Ryan Dempster had a 4.80 ERA last season, but had one of the highest starters’ BABIP in 2011 at .324. This season, his BABIP is .259, and his ERA is 1.74. Former A’s starter Trevor Cahill posted a 2.97 ERA and went 18-8 in 2010 with a shockingly low .236 BABIP. In 2011, his BABIP went back to normal (.302), and he went 12-14 with a 4.16 ERA. Granted, there are other factors at play here, but absent a dramatic change in the defense behind him or the park in which he plays, a pitcher’s performance is very much dependent on where the ball happens to fall.
Based solely on BABIP, here are some players that are overachieving that I might expect to fall back to earth relatively soon (with their BABIP and batting average or ERA, as of last night):
HITTERS: David Wright (.470, .411), Bryan LaHair (.406, .330), Paul Konerko (.406, .362)
PITCHERS: Ted Lilly (.196, 2.11), Brandon Beachy (.214, 1.33), Lance Lynn (.219, 1.81)
As for players who one might expect to bounce back from a tough start…
HITTERS: Eric Hosmer (.165, .174), Jose Bautista (.178, .207), Russell Martin (.186, .167)
PITCHERS: Max Scherzer (.403, 6.26), Josh Johnson (.385, 5.36), Ivan Nova (.380, 5.44)