A primer on BABIP
How to use this effective but misunderstood stat to analyze player performance
Editor's note: This story was originally published in the 2010 ESPN Fantasy Baseball Draft Kit. It is being republished unaltered here for your convenience.
Though it has been 11 years since Voros McCracken first introduced it to the sabermetric community, BABIP is a concept that, apparently, even the most experienced baseball minds might not fully grasp.
If that's a term that's either completely foreign or somewhat new to you -- or even if you're familiar but not quite certain that you've mastered its use -- then this column is for you. Being the beginning of fantasy baseball draft season, what better time for a primer: Understanding BABIP.
Let's address the obvious question first: What, precisely, is BABIP?
BABIP, or batting average on balls in play, was originally designed to measure a pitcher's ability to prevent hits on balls in play. Today it's widely used to evaluate both pitchers and hitters, and it's a calculation of a hitter's batting average -- or pitcher's batting average allowed -- on batted balls put into the field of play. That means walks and strikeouts don't count; those aren't batted balls. Nor do home runs; those don't 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?
Fantasy owners familiar with the concept will quickly answer that it's a way to determine a hitter or pitcher's luck. That's true, as variances in a player's BABIP from the major league average could represent a certain degree of luck, either good or bad. But the common mistake many owners make is to assume that BABIP is the authority on luck in the game of baseball, and that the farther that a player's number was from that aforementioned major league average, the more or less lucky he had to have been.
That's simply not true.
Before we get to the reason, let's address another important question: Exactly what is the major league average for BABIP?
It varies from season to season, but in 2009, the major league average BABIP was .299. Generally speaking, it's about .300. It can, however, range by as many as five points (occasionally more) in either direction from that.
So, then, why can't it be assumed that a hitter with a .360 BABIP was extraordinarily lucky, while one with a .240 BABIP was especially unlucky, and in the case of a pitcher, that the opposite is true?
Making such an assumption also presumes that every baseball player is identical; that there is no such thing as a strikeout artist or command specialist, ground-ball or fly-ball pitcher, contact or power hitter. There are so many different types of baseball players nowadays, and every type of play has a varying degree of success.
An excellent way of putting it: Joel Pineiro had a .295 BABIP in 2009 and Andy Pettitte had a .297 BABIP, but does that necessarily mean that Pineiro was any luckier than Pettitte? No -- Pineiro generated ground balls on a higher percentage of balls in play than any pitcher in the game (59.0 percent) and line drives at the fourth-lowest rate (15.9 percent). Since a ground ball has a much greater chance of being converted into an out than a line drive, and a fly ball greater than a ground ball, Pineiro's BABIP should have been beneath the major league average. Pettitte, by comparison, allowed the 12th-highest line-drive rate (21.3 percent) and served up ground balls 41.7 percent of the time. His BABIP, actually, might have been a bit driven by good fortune.
It's also not only what type of hitter or pitcher a player is that factors into BABIP. What are some other things that have an impact?
Speed (applies to hitters): Naturally, the quicker the runner, the more likely he'll leg out infield grounders for hits, thereby helping his BABIP. Of the 25 players to amass at least 25 infield hits in 2009, only two had a BABIP beneath the major league average: Kazuo Matsui (28 infield hits, .285 BABIP) and Willy Taveras (28, .277). In addition, of the 14 players to attempt steals on at least 20 percent of their opportunities (data per Baseball-Reference.com), only one had a BABIP beneath the MLB average: Josh Anderson (25.6 percent steals rate, .280 BABIP).
Quality of contact (applies to both): The better wood a hitter gets on the ball, the more likely he's going to "hit 'em where they ain't," as Wee Willie Keeler once said. A high line-drive rate is one way to ensure a high BABIP, and to that end, of the 17 players who hit line drives on at least 22.5 percent of all balls in play, only Josh Willingham (.289) had a BABIP beneath the major league average. In fact, the other 16 all had BABIPs greater than .325. But here's another interesting fact: Inside Edge provides a statistic called "Well Hit Average," which measures the percentage of at-bats in which a hitter made solid contact. Of the top 25 hitters in that stat who also qualified for the batting title, 18 managed better-than-average BABIPs.
Now applying that to pitchers (working primarily with those who qualified for the ERA title in 2009), of the top 25 in "Well Hit Average" allowed, 14 surrendered BABIPs beneath the major league average. In addition, of the 25 pitchers to allow a line-drive rate of 18.0 percent or less, 17 managed beneath-league-average BABIPs.
Defense (applies to pitchers): The quality of a pitcher's defense might have a greater impact on BABIP than any other factor. The reasons are obvious: A shoddy defense means more batted balls drop in for singles, while an elite defense might steal a few plays that might otherwise have dropped in for hits. To illustrate that point, of the 10 pitchers with the lowest BABIP among those who also qualified for the ERA title in 2009, seven played for teams that ranked among the top 10 in the game in terms of Ultimate Zone Rating (UZR), according to FanGraphs. Four of the nine pitchers with the highest BABIP, by comparison, played for teams that ranked in the bottom 10 in UZR.
Does BABIP carry greater importance for either hitters or pitchers, or is it about as relevant a statistic for each?
It's actually a bit more relevant for pitchers than it is for hitters, and it's mainly because pitchers have inherently less control over the outcomes of individual plays than hitters. Once the ball leaves a pitcher's hand, its fate rests in the hands of the hitter, the defense, the weather, the ballpark, etc. A hitter, meanwhile, can use skill to help guide the ball, to a degree, to a specific spot, slightly increasing his chances of success. Look at BABIPs and you'll see the difference -- the highest recorded by a qualified pitcher in 2009 was .335 and the lowest was .254. Turning to hitters, 35 who qualified for the batting title managed a BABIP greater than .335, with David Wright's .394 tops. Three hitters had a lower BABIP than .254, with Ian Kinsler's .241 representing the worst in the game.
OK, so Kinsler is fast, yet he had a miserable BABIP. That means he's bound to hit for a higher average this year, right?
It's a distinct possibility, but that's another frequent mistake in evaluating BABIP numbers. They provide no guarantee of anything; rather they offer a way of identifying batting averages that might have been unrealistically high or low in the season in question. Kinsler's .241 BABIP means bad luck might have been largely responsible for his career-worst .253 batting average, but go back two years before that and he had a .282 BABIP yet batted only 10 points higher. Who's to say that bad luck can't strike him again in 2010, or that his potential for improvement is all that significant? Kinsler might simply be a .270 hitter at his best.
Always remember that any insights you draw from BABIP are guidelines, specifically designed to help you understand the meaning behind things like batting average, ERA and WHIP. They keep you from pitfalls like misinterpreting Kinsler's low batting average as eroding skills, or Wright's ability to maintain a .300-plus batting average if he continues to hit 10 homers and strike out 140 times a year.
What, then, are the fairest conclusions we can draw from BABIP numbers?
The final big gaffe people make -- even people most familiar with BABIP -- is failing to put a player's numbers into perspective. Individual players, over time, build established track records in the category that tend to remain somewhat consistent. Comparing a player's number in the category to those of past seasons might identify outliers -- seasons that vary enough from his career or recent-years' BABIP numbers to indicate the possible presence of good or bad luck.
The other thing fantasy owners can and should do: Break down the player's BABIP by batted ball type. Baseball-Reference.com is an excellent source for this, providing statistics for all players broken down by ground balls, fly balls, line drives and bunts, including BABIPs. Assuming enough of a sample size for a player in any of those groupings, any extreme variance from the major league averages might indicate luck at play. (That is, if there's not another obvious explanation, such as an especially good or bad defense or a spacious or bandbox ballpark.)
Here are those 2009 average BABIPs, but this time broken down by batted ball type:
Ground balls: .237
Fly balls: .138
Line drives: .724
Break down BABIPs? Why do I have to do all that work?
Good news: You don't. Didn't think I'd leave you merely with a primer, but no in-depth analysis of 2009 statistics, did you? Here's where you can see a full breakdown of last season's BABIP numbers, including players who were seemingly the luckiest or unluckiest in the category.
In order to help fantasy owners better identify such candidates, I've introduced the concept of expected BABIP to the analysis. It's no new concept, 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 arbitrary to me -- 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 .237, plus fly balls times .138, plus line drives times .724, plus bunts times .376 (GB X .237) + (FB X .138) + (LD X .724) + (BUNT X .376).
That's another handy tool you might consider for reference while mining your way through the challenging task of BABIP analysis.
Before we close, however, remember one important rule: BABIP can never, and should never, be regarded as the driving force behind your draft-day preparations. It's one of many tools that can help you be successful, but it's not the perfect tool, much the way you should never draft a fantasy team solely off a list of contract-year players, pitchers who throw 100 mph or players aged exactly 27 years. These are all factors for your consideration -- not sole decision-makers.
But a valuable, underrated (and too-often misused) factor, that's what BABIP is.
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.
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