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)
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