Batting Average On Balls In Play & How to Use It

Jim Rogash

The VEB Knowledge Nest is a recurring feature that discusses baseball terms and stats that are regularly used on the site. Today's topic: Batting Average on Balls In Play (BABIP).

The stat Batting Average on Balls In Play (BABIP) is a relatively new one. But the idea behind it is as old as baseball itself. For generations, fans have implored their favorite team's batters to "Hit it where they ain't!" and bemoaned "seeing-eye singles" off the bat of the opposing team.

In Bull Durham, which was released two decades before BABIP existed, Crash Davis delivers a sermon that may as well have been on the stat:

Know what the difference between hitting .250 and .300 is? It's 25 hits. 25 hits in 500 at bats is 50 points, okay? There's six months in a season, that's about 25 weeks. That means if you get just one extra flare a week, just one, a gorp...you get a groundball, you get a groundball with eyes...you get a dying quail, just one more dying quail a week...and you're in Yankee Stadium.

The idea behind BABIP was a baseball truth we all knew in our guts long before someone sliced up a player's batting average in a way that created the stat. Now we have that traditional notion in a black-and-white stat. It's a stat that has become ubiquitous when discussing batters and pitchers alike. Unfortunately, abuse often follows ubiquity. That's why it's important to recognize and remember what BABIP measures and the peripherals that are necessary to give the stat proper context.

BABIP Has a Narrow Focus

We know that there are many ways to look at a batter's accomplishments. For the broad view, there are plate appearances (PA). If we want to focus in on a batter's ability to make contact and reach base safely on a hit, there are at bats (AB). But the most narrowly tailored measure of a batter's offensive profile is balls in play (BIP), which are a component part of a batter's ABs and PAs.

As its name indicates, BABIP is based only on those balls a batter raps into the field of play. BABIP excludes walks, strikeouts, foul balls, and homers. It is calculated based on flyouts, groundouts, singles, doubles, triples, fielder's choices, errors, and sacrifices. Compared to BA, OBP, SLG, OPS, and wOBA, BABIP includes the least amount of batter outcomes.

PAvsABvsBIP title=

BABIP Impacts Individual Batters Differently

Despite being made up of the smallest sliver of batting events, BABIP has a ripple effect that is felt across a hitter's slash line. BABIP impacts a batter's BA most severely. This means that BABIP necessarily has an effect on a batter's SLG, a stat also calculated using ABs as the denominator. BABIP affects a player's OBP by way of BA.

Singles hitters feel the ups and downs of BABIP fortune more severely than batters who hit for a lot of home runs. A home run is not included in a batter's BIP total, so it is not a part of his BABIP calculation. But a dinger does count toward his BA, OBP, SLG, OPS, and wOBA. The more homers a batter clubs, the less he'll feel the impact of a dipping BABIP. This isn't to say there is no impact, just that it is less for home-run hitters. Their homers simply insulate them more against the vagaries of BABIP.

Batters who draw a lot of walks also have a built-in cushion against BABIP's ebbs and flows. BABIP only includes BIP. Therefore, it only impact a player's OBP by way of his BA. Players who walk a lot generate a larger share of their OBP via PAs outside of their BA. The larger the share of a batter's OBP he generates without putting the ball in play, the less of an impact his BABIP has on his OBP.

A Player's Batted-Ball Profile Must Be Considered When Evaluating His BABIP

Typically, the MLB average BABIP is around .300. Between 2004 and 2013, the MLB-wide BABIP has fluctuated between .295 and .303. Most recently, in 2013, it was .297. The rule of thumb that has flowed from this is that a player's BABIP is likely to regress, up or down, to the league average of about .300. But this can be misleading because BABIP reflects both skill and luck.

2014

All balls put into play are not equal, but BABIP standing alone treats them as such. The harder a ball is hit, the more likely it is to result in a hit for the batter. Line drives are the best kinds of BIP, because they're most likely to result in a hit. Line drives are head and shoulders above the other batted-ball types. Second-best are grounders. The type of batted ball least likely to result in a hit is a flyball.

Now consider the following graph, which shows the various batted-ball rates for MLB as a whole over the last decade.

MLB LD%, GB%, & FB% (2004-2013)

This chart tells us what the average MLB batted-ball profile looks like. The league-wide GB% stays pretty constant at right around 44%. But there's more fluctuation between GB% and LD%. Note that when LD% goes up, there's a corresponding dip in FB% and vice versa. LD% has ranged from 18% to 21% over the last decade. The MLB FB% has fallen between 34% and 38%.

It's important to look at the batted-ball profile that has led to the league-wide BABIP just as it's important to look at an individual player's batted-ball profile when assessing his BABIP. In 2013, the league average LD% was 21.2%, the collective GB% was 44.5%, and the MLB overall BABIP was .297. So it's safe to say that a player with a 23% liner rate who hit grounders on 50% of his BIP and had a .290 BABIP was unlucky. It's also safe to say that a player with a 17% liner rate, 43% grounder rate, and .307 BABIP was a bit lucky. The determination of whether a batter's BABIP was lucky is dependent on examining his batted-ball profile, not just glancing at his BABIP and seeing where it falls in relation to .300.

Expected BABIP (xBABIP)

Just as all BIP are not created equal, the hits that make up an individual batted-ball category aren't the same either. Some liners are struck harder than others. The same goes for grounders and flyballs. The harder a ball is hit, the more likely it is to result in a batter reaching base safely.

MLB clubs have Hit F/X data, which measures the trajectory of a batted ball as well as as its exit speed off the bat. Using Hit F/X, they are able to accurately value how well hit every batted was. Unfortunately, this information is not available to the public.

Absent Hit F/X, folks have developed Expected BABIP (xBABIP) calculators. Instead of using Hit F/X data, these xBABIP calculators attempt to use other stats as proxies for the factors that can cause a player's BABIP to be higher or lower than it would be all batted-ball types are treated equally. They still rely on a player's batted-ball profile, but they also use other stats as proxies for the skills that impact a player's BABIP. VEB community member Paulspike developed such a mousetrap. His formula is based on the following factors:

  • LD%
  • GB%
  • IFH%
  • Fangraphs Speed
  • Contact %
  • Isolated Power (ISO)

Fangraphs Speed and IFH% are proxies for the batter's ability to turn balls hit on the infield into hits with his legs. LD% and GB% indicate the quality of contact he has made. So does ISO. The thinking is that batters who notch more extra-base hits and therefore have a higher ISO tend to hit the ball harder overall than players who tend to hit a lot of singles. Contact% is a proxy for the batter's ability to make contact. Using these inputs gives us a more accurate picture of whether a batter was lucky or unlucky on batted balls over a period of time, because they incorporate stats that reflect individual skills.

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Context is very important when evaluating a player's BABIP. A player's skill set can lead to a higher or lower BABIP and can also impact how much his batting line is impacted by his batted-ball fortunes. BABIP is an informative stat so long as it isn't misused.

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