Derek Carty, a colleague of mine, wrote an article not too long ago revolving around BABIP and the DIPS theory from the pitcher’s point of view. My goal in this article is to analyze the BABIP statistic from the point of view of the batter. To read Derek’s article, click here.

BABIP stands for Batting Average of Balls In Play. The statistic can be calculated with the following formula:

BABIP = (H – HR) / (AB – K – HR + SF)
The statistic measures the percentage of balls in play that fall in for hits. Since home runs are considered to be a pitcher-dependent statistic, BABIP removes them from qualifying. Strikeouts are also considered to be pitcher-dependent and so this statistic primarily measures the amount of times a batter gets a hit out of the amount of times he hit the ball. For an example we will look at the 2007 season of Philadelphia Phillies left-fielder Pat Burrell. Burrell had a BA (Batting Average) of .256 while going 121-472 in 155 games. Burrell hit 30 home runs, struck out 120 times, and had 8 sacrifice flies. Plugging him into the BABIP formula:

Burrell BABIP
= (121 – 30) / (472 – 120 – 30 + 8)
= (91) / (330)
= .276

In 2007, Burrell had a batting average of .256 but a batting average of balls in play of .276. This tells us that Burrell’s average took a big hit (almost 20 points) due to his high strikeout count. Essentially, since the stat removes home runs from each side, BABIP tells us what a player’s batting average would be if he never struck out. The reason this statistic can be useful deals with the context in which it is used. We should not, by any means, replace BA with BABIP. Players do strikeout and so using BABIP as a barometer would not be a fruitful way of analyzing talent. What BABIP can tell us is which players would be good or bad fantasy picks.

The key, above all else, is consistency.

Make no mistake, if a player posts consistent BABIP regardless of his BA, then we are dealing with luck and factors seemingly out of his control. These types of players are the ones we should be looking into drafting. Of course, this really does not apply for the early rounds when we all know which batters are going to be drafted, but rather for the later rounds, when we are deciding between the Felipe Lopez’s and Ryan Church’s of the world. Those who show extreme fluctuations in BABIP are the ones who get drafted higher the next year and then usually are used as trade bait or deemed busts when they do not match their previous year’s success. The problem here is not that the player was a “bust” but rather that the owner that drafted him did not do his homework and was instead WOW’ed by flashy numbers.

Again, let’s look at Pat Burrell, this time analyzing his seasonal BABIP since his MLB debut in 2000:


This table tells us that Pat Burrell, other than one awful season, has consistently had very respectable BABIP numbers. Though he appears to be on the decline since 2005, you can see that his BABIP has been pretty consistent despite the fluctuations in his batting average. These are the types of guys that are good bets for fantasy picks due to the consistency in their percentages of balls in play that drop in for hits.

I’m not telling you to draft Pat Burrell, or draft him high, or anything along those lines. What I am saying, though, is that when it gets down to the final few rounds of a draft and you need to fill out your team, incorporate BABIP into the equation. If you’re having trouble deciding between a Juan Pierre or Dave Roberts, guys that will rack up steals, go with whoever has had a more consistent BABIP throughout the recent years.

BABIP will also progress or regress, usually towards a .300 range. This can be seen in Burrell’s table. In 2000 and 2005 his BABIP were abnormally high, however his very low 2003 makes up for it.

The entire point of this article, in suggesting you apply BABIP to your fantasy evaluation arsenal, is to be wary of breakout seasons and incredibly “down” seasons. Most would shy away from a player like Burrell following the 2003 and 2004 seasons due to his terrible 2003, however he was essentially the same type of player in 2004 as he was in 2001 and 2002. Before getting very high on players who come out of nowhere to lead the league in BA or very low on those who have significant dropoffs, do yourself a favor and investigate their BABIP – it will tell you whether or not this was a fluke or something to look out for.