Understanding Statistics- BABIP

This is the first of series analyzing statistics that are commonly used, and misused, by statistically inclined baseball fans. Last weekend I posted an article criticizing the misuses of BABIP (Batting Average on Balls in Play) so I will start there.

Formula: (H-HR)/(AB-(HR+SO)+SF) (hits-home runs)/(at bats-(home runs+ strike outs)+sacrifice flies)

Explanation: The idea of BABIP is to measure how often a ball hit in the field of play turns into a hit. It is used to analyze pitchers, batters and occasionally team fielding.

Statistical Artifacts: All other things being equal, the more a player strikes out the higher their BABIP will be. Likewise, the more of a player's hits come from home runs, the lower their BABIP will be. These are what I call "statistical artifacts", how the act of measurement used effects the results. Whether there is any real difference between hitting the ball off the Green Monster or over it, one will improve a player's BABIP, the other won't.

Why we should care: Whether a batter makes a hit or an out is a combination of a lot of different factors, including some beyond the control of the pitcher or hitter. Like the outliers in any statistical measure, players with an extremely high or low BABIP are unlikely to sustain it from season to season.

Why we shouldn't care: The distinction between home runs and other hits is highly questionable. The idea is that fielders can't catch a home run (and it is therefore not "in play") while the performance of the fielder can turn a hit into an out or vice versa.

But this is really using a double standard. We have all seen hitters robbed of home runs by a leaping fielder. The home runs are the ones the fielder didn't reach. Of course, no fielder can jump 30 feet into the air on some home runs, its only the close ones that are really in play. But the same can be said of many hits. They were 15 feet over the head of the outfielder or shots through the infield. No fielder would have got to them. The adage "hit 'em where they ain't" has been part of baseball for a long time. The outfield bleachers are just one case of a place "they ain't".

How its used or misused: The most common use of BABIP and its major misuse is as a measurement of "luck". Like any baseball statistic, luck does effect the results. A single season of baseball is simply not enough to remove all meaningful random variations. Ted Williams was lucky to hit have hit .400. But there is a reason no one has done it since. The typical major league hitter, much less the Drew Butera's of the world, is not going to ever hit .400, lucky or not. Likewise, the typical player isn't going to have a BABIP of .400.

At the extremes we can be fairly confident what general effect luck had on the results. But, as with most baseball statistics, there is a lot of overlap where two players have the same BABIP but one was lucky and one was unlucky. That may be reflected in their BABIP relative to their previous career numbers. But you won't know that from the raw numbers from one season.

Like other statistics, the player's career trajectory needs to be taken into account. Improvement in a young player's BABIP over their previous career may result from real improvement in performance, while an older player's low BABIP may be a reflection of declining skills rather than bad luck.

In the case of pitchers, BABIP has been abused in the extreme. The suggestion has been made that pitchers have "little or no control" over whether a ball in play goes for a hit. This is not supported at all by the data. While good pitchers do have bad years when measured by BABIP, the career numbers of pitchers reflect a wide range of skills. With the best pitchers ending up with career numbers that are above average. As with hitters, all other things being equal, the more strike outs a pitcher has the higher their career BABIP will be. But even among high strike out pitchers, most good pitchers keep their BABIP below the league average of .300. To put this in perspective, there is not a single pitcher in the HOF whose BABIP is above that .300 mark.

This is not really surprising. Even among great strike out pitchers, two thirds of their outs come on balls in play. If you aren't getting anyone out the rest of the time, its going to be very difficult to make up for it with strike outs.

The use of BABIP for fielding is based in part on the claim about pitchers having no control over the results. If that were true, aside from luck, you might assume the biggest factor effecting BABIP is the team's fielding with the other big impact from park effects. Unfortunately, since pitching remains the biggest factor, BABIP is no more a measure of a team's fielding ability than any other measurement of results.

Conclusion: BABIP isn't really very useful in evaluating hitters or pitchers other than recognizing outliers. Its usefulness in evaluating teams fielding is based on a false premise. Its only really useful for winning arguments.