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# A primer on BABIP

While there's intrinsic value in many of the statistical advances in baseball from the past two decades, the misinterpretation of those statistics is an ever-present danger. That's especially true at times when such statistics become mainstream.

BABIP is an excellent example of a now-mainstream statistic that is all too often misused.

Those of you who are familiar with our Fantasy Baseball Draft Kit probably recall our "BABIP Primer" column of a year ago, which introduced the statistic to those unfamiliar with the concept, as well as explain its purpose to even the most experienced fantasy owner.

Well, it's a new year, and considering BABIP is now a statistic often cited on these pages, as well as discussed by a large number of fantasy owners, what better time than to provide a refresher course on the proper use of the stat? Welcome to the 2011 version of Understanding BABIP, designed to provide you with everything from a beginner's to an advanced owner's knowledge of its use.

What, precisely, is BABIP?

Developed more than 10 years ago and widely attributed to Voros McCracken, BABIP, or batting average on balls in play, measures both a hitter's ability to produce hits and a pitcher's ability to prevent them on balls in play. It's essentially a calculation of a hitter's batting average -- or a pitcher's batting average allowed -- solely on batted balls put into the field of play. Walks and strikeouts do not count in the calculation; no balls are put into play. Home runs also do not count; those do not land within the field of play.

The formula: Hits minus home runs, divided by at-bats minus home runs minus strikeouts plus sacrifice flies (H - HR)/(AB - HR - K + SF).

What purpose does BABIP serve?

This is the most common pitfall of the BABIP statistic; there's a prevailing assumption that the category measures a player's luck, and that those who deviated greatly from the major league average in the category were either especially lucky (a hitter with a high BABIP or pitcher with a low one) or unlucky (a hitter with a low BABIP or a pitcher with a high one). While it's true that BABIP can represent to a certain degree a player's fortunes, it should never be taken as the authority on the matter, or a one-size-fits-all measure of luck.

Before we get to the reason for that, let's first address another important question: What is the major league average for BABIP?

In 2010, the major league average BABIP was .297, down two points from 2009's .299. At times during the past decade-plus, it has ranged as high as .300, and sometimes a few points higher. In the distant past, it often dipped beneath .290. For example, 25 years ago, in 1986, the league-average BABIP was .286.

It's widely assumed that a typical league-average BABIP is around .300, but that can range by as many as five points (occasionally more) in either direction.

Why can't we assume, then, that a hitter with a .360 BABIP was extraordinarily lucky, while the one with a .240 BABIP was especially unlucky, and in the case of a pitcher, that the opposite is true?

The reason is that doing so dismisses the differing skill sets, abilities and team/ballpark situations of each individual player. It treats them as "one size fits all" when, truth is, there isn't a person out there who is going to tell you that Albert Pujols and Cesar Izturis are the same kind of hitter, or that Felix Hernandez and Zach Duke are the same kind of pitcher.

Here's a different way of putting it: Jered Weaver had a .277 BABIP in 2010 and Dave Bush's was .299, but that doesn't necessarily mean that Weaver was a much luckier pitcher than Bush. In fact, it's probably the opposite. Weaver generated fly balls (48.5 percent) at a higher rate than anyone else in baseball but Ted Lilly (51.2), and line drives second-least frequently (13.8) among pitchers who qualified for the ERA title. (Those numbers per Baseball-Reference.com.) Fly balls -- at least the ones kept in the field of play -- are the most likely kind to be converted into outs, so Weaver's BABIP should have been beneath the major league average. In fact, considering his low line-drive rate, it probably should've been even lower than .277. Bush, meanwhile, surrendered the second-highest line-drive rate of any qualified starter (22.5 percent) and had ground-ball and fly-ball rates near the league averages, meaning his BABIP probably should've been noticeably higher than .299.

Are there league averages available broken down by batted-ball type?

Absolutely. Here are the 2010 major league averages for each:

Overall BABIP: .29703
Ground balls (43.5 percent of all balls in play last season): .23490
Fly balls (35.4 percent): .13716
Line drives (18.8 percent): .71578
Bunts (2.2 percent): .38828

One thing to remember: While fly balls obviously have the greatest probability of being converted into outs, remember that the benefit is often outweighed by increased risk of home runs and extra-base hits. What you're looking for are pitchers at either extreme: It's the pitchers with absurdly high ground-ball or fly-ball rates that you want, and not the ones with high line-drive rates.

Consider that 21 qualified pitchers allowed more fly balls than ground balls in 2010, and 19 had BABIPs beneath the league average, while 13 had BABIPs more than five percent beneath it. Meanwhile, 19 pitchers generated ground balls on more than 50 percent of their balls in play last season, 15 of those had a BABIP beneath the league average and seven had a BABIP more than five percent beneath it.

Extremes, apparently, are good.

It's also not only the type of hitter or pitcher a player is that factors into BABIP. What are some other things that have an impact?

A hitter's speed: It's a no-brainer, but the faster the runner, the more likely he'll leg out ground balls in the infield for hits, boosting his BABIP. Of the 27 players to amass at least 20 infield hits in 2010, only two had a BABIP beneath the major league average: Juan Pierre (26 infield hits, .294 BABIP) and Denard Span (24, .294), neither of whom missed by much. Breaking down BABIPs into numbers on ground balls, 18 of the top 25 qualified hitters in terms of ground-ball BABIP stole double-digit bases. Drew Stubbs (.362 GB BABIP, 30 SB), Rajai Davis (.349, 50), Colby Rasmus (.340, 12), Austin Jackson (.329, 27) and Carl Crawford (.318, 47) comprised the top five in that category, and Crawford is an excellent example of the benefits of speed in boosting ground-ball BABIP. He has registered a ground-ball BABIP higher than the league average in every one of his full seasons (in other words, excluding his rookie year of 2002 and injury-plagued 2008), and five times he has managed a .300 number or better in the category.

Conversely, slower players suffer in terms of BABIP. Of the 25 worst qualified hitters in ground-ball BABIP, 18 finished with five or fewer stolen bases. That included each of the bottom five: Carlos Pena (.137 GB BABIP, 5 SB), Jose Lopez (.143, 3), Aaron Hill (.154, 2), Mike Napoli (.161, 4) and Kevin Kouzmanoff (.162, 2). Pena, incidentally, didn't have a ground-ball BABIP higher than .196 in any of his four seasons with the Tampa Bay Rays, not to mention a .114 mark in 2009.

Quality of contact: Another no-brainer, but the more effectively a batter hits the ball, the greater his likelihood of a successful outcome. Thanks to Inside Edge, with help from Mark Simon in ESPN Stats & Information, the major league BABIP on "well hit" baseballs was .589 in 2010, while the BABIP on every other ball put into play was just .203.

Higher line-drive rates also result in higher BABIPs, naturally, since the numbers above show that such plays resulted in hits more than 70 percent of the time last season. Of the top 25 qualified hitters in terms of line-drive rate, only five had a BABIP beneath the major league average: Skip Schumaker (.294 BABIP, 22.5-percent line drive rate), Alcides Escobar (.264, 22.1), Yadier Molina (.281, 21.9), Cliff Pennington (.296, 21.5) and Chase Utley (.288, 21.5). In the cases of Schumaker and Molina, a greater-than-50-percent ground-ball rate was probably responsible, but the other three might indeed have suffered some bad luck.

Now, applying that to pitchers, only one of the 35 ERA qualifiers who had a line-drive rate beneath 18 percent had a BABIP higher than the league average, and his was only barely above: Francisco Liriano's was .29748.

A pitcher's defensive support: This is another of the pitfalls of investing too much in BABIP as a predictive tool, because the category actually does as much to demonstrate the quality of a team's defense as it might an individual pitcher's luck. The reasons for that are obvious: A poor defense is going to afford more seeing-eye singles to sneak through the infield or bloops to drop in for outfield hits, while a Web Gem-caliber defense will gobble up screaming liners, well-placed grounders and deep fly balls that might drop in for hits against almost anyone else.

To illustrate that point, seven of the top 10 teams in terms of pitching BABIP also ranked among the top 10 in Fangraphs' Ultimate Zone Rating, which measures a team's defensive quality. Meanwhile, six of the 10 worst teams in pitching BABIP also ranked among the 10 worst in UZR. And on an individual basis, 36 qualified pitchers made at least one appearance for one of those top-10 teams in UZR, 24 of them had a BABIP beneath the league average (66.7 percent) and the collective group had a .28653 BABIP. Conversely, 27 pitchers made at least one appearance for one of the bottom-10 teams in UZR, only 14 of them had a BABIP beneath the league average (51.9 percent) and the collective group had a .29719 BABIP. Clearly, quality defense does a lot to help bring down a pitcher's BABIP, so don't be so hasty to discard a low number as a product of luck.

Three-true outcome players: This might seem odd, but the players most likely to conclude their at-bats in either a home run, walk or strikeout are actually most fit to succeed in terms of BABIP. Part of that is probably their tendency to swing for the fences, meaning the majority of batted balls they put into play they do so with authority. Of the 22 players who most fit the "three-true outcome" definition in 2010, 16 had a BABIP more than 5 percent greater than the league average, and 11 of them had a line-drive percentage greater than 20 percent.

Does BABIP carry greater importance for either hitters or pitchers, or is it about as relevant a statistic for each?

BABIP is a more valuable evaluation tool for pitchers than it is for hitters, primarily because pitchers have less control over the outcomes of individual plays, at least the ones that end in a batted ball being placed into the field of play, than hitters. Once the ball leaves a pitcher's hand, its fate rests in the hands of the type of hitter, the quality of the defense, the weather conditions, ballpark factors, etc. A hitter, meanwhile, can help guide the ball with his swing, no matter by how small a degree, slightly increasing his chances for success.

These numbers help illustrate the difference: The highest recorded BABIP by a qualified hitter in 2010 was .396 (Austin Jackson), and nine hitters managed a BABIP of .350 or greater. The lowest hitter BABIP was .196 -- Aaron Hill's number, which was actually one of the lowest in history -- and seven finished beneath .250.

The highest recorded BABIP by a qualified pitcher, however, was a mere .341 (James Shields). The lowest was .236 (Trevor Cahill), and only four finished with a BABIP less than .250.

So what are the fairest conclusions we can draw from BABIP?

The final pitfall we face with BABIP -- and this is a trap that can catch even the most seasoned fantasy owners -- is failing to put a player's numbers in the category into perspective. Over time, individual players build established track records in the category that usually remain consistent, especially on the hitting side. Pitchers, meanwhile, tend to regress to the mean in terms of BABIP, meaning a pitcher whose number in the category was unusually high or low will probably settle closer to the league average the more innings he throws.

One thing you should do before taking any individual BABIP at face value is to look at the player's past numbers in the category. Was his number an outlier, completely out of character with his past performances despite little to no shifting in his batted-ball rates? Matt Kemp is such an example; he had a .295 BABIP in 2010, down 50 points from 2009 (.345), despite only negligible changes in his line-drive, ground-ball or fly-ball rates. Heck, he put only 33 fewer balls in play last season than the one before it. If you're looking for any example of unexpected, inexplicable shifting in BABIP performance, Kemp is it.

Also consider breaking down a player's BABIP by batted ball type, comparing the number to the averages listed above. (Baseball-Reference.com is an excellent resource for this.) Using the Kemp example, his ground-ball BABIP dropped from .284 in 2009 to .176 in 2010, particularly odd for a speedy runner who has a .289 career number in the category. That's further evidence that he was particularly unfortunate, and a probable bounce-back candidate in 2011.

In order to help fantasy owners better identify such candidates, consider calculating a player's expected BABIP, then comparing it to his actual number. This is no new concept -- it was even discussed in this space last year -- but is one that helps put the player's actual number in the category into perspective. Opinions on the proper formula for expected BABIP vary -- some argue you can just add 10 percent to a player's line-drive rate, which seems awfully arbitrary -- but I've found that the best ones calculate the major league average BABIPs by batted ball type, multiplied by the player's batted-ball percentages.

For example: Ground balls times .235, plus fly balls times .137, plus line drives times .716, plus bunts times .388, or (GB * .235) + (FB * .137) + (LD * .716) + (BUNT * .388).

Before we close, I'll reiterate one important rule, one made in this space a year ago: BABIP can never, and should never, be regarded as the driving force behind your draft-day preparations. As with many peripheral statistics, it's merely another tool designed to help unearth hidden value, but it's not the perfect tool, much the way you should never draft a fantasy team solely off a list of players in contract years, players aged exactly 27 years old, players in their third major league season or players who like oatmeal. These are all factors for your consideration, but should not be the sole decision-makers.

BABIP is a valuable, underrated and often misunderstood tool. Hopefully, with this column's help, you've now just about mastered it.

Tristan H. Cockcroft is a fantasy baseball analyst for ESPN.com and a two-time champion of the League of Alternative Baseball Reality (LABR) experts league. You can e-mail him here, or follow him on Twitter @SultanofStat.