GB%, LD%, FB%

Batted Ball Statistics are fairly straightforward: they express the share of a batter’s balls in play are line drives, ground balls, or fly balls. This includes balls that leave the park (home runs), so the sum of a batter’s batted ball statistics should be 100%. Major leaguers have a variety of swings, resulting in different batted ball profiles. Some batters hit lots of fly balls (typically power hitters), others put lots of balls on the ground (contact hitters), and many others fall somewhere in between.

Infield pop-ups are also tracked on FanGraphs (IFFB%), and they are expressed as the percentage of pop-ups a batter hits out of their total number of fly balls. These numbers are generally small and fluctuate from year to year. They’re the worst batted ball type for batters, as they almost always lead to an out.


The statistics published on FanGraphs are drawn from data from Baseball Info Solutions (BIS) and reflect the share of a batter’s total balls in play that are of a certain type, classified as line drives, fly balls, and ground balls. Fly balls are also divided up between infield fly balls and total fly balls. To wit, the following are the formulas to calculate the percentages you can find on the site:

Line Drive Percentage (LD%) = Line Drives / Balls in Play

Fly Ball Percentage (FB%) = Fly Balls / Balls in Play

Ground Ball Percentage (GB%) = Ground Balls / Balls in Play

Infield Fly Ball Percentage (IFFB%) = Infield Fly Balls / Fly Balls

Our batted ball data goes back to 2002, but it’s important to remember that there is no perfect way to define each type of batted ball so some balls that you might consider a fly balls might get classified as line drives and vice versa. In reality, batted balls exist on a continuous distribution from rolling perfectly on the ground to being launched straight up in the air. The cut points between the three classifications are somewhat arbitrary and imprecise, so do not treat the data as infallible.

Why Batted Ball Stats:

Batted ball stats are extremely useful for determining the type of hitter at which you’re looking. There is no ideal batted ball distribution, but batters who hit a lot of line drives typically perform better than hitters who hit lots of fly balls or ground balls. Generally speaking, line drives go for hits most often, ground balls go for hits more often than fly balls, and fly balls are more productive than ground balls when they do go for hits (i.e. extra base hits). Additionally, infield fly balls are essentially strikeouts and almost never result in hits or runner advancement. Here are the numbers from 2014:

GB .239 .020 .220
LD .685 .190 .684
FB .207 .378 .335

We use these stats to tell us two things. First, we want to get a sense of a batter’s swing or style of play. A big slugger hits lots of fly balls. A weak hitter probably hits a lot of ground balls. But more than descriptive information like that, batted ball data can be an indication of a hitter’s underlying performance.

We often look at a hitter’s Batting Average on Balls in Play (BABIP) to make determinations about the sustainability of their performance and batted ball data informs that analysis in an important way. If a batter hits a lot of line drives, a high BABIP is more likely a function of his true talent than a hitter who hits a lot of fly balls, who has probably just been lucky in running that higher BABIP.

Batted ball stats are a proxy for the nature of the batter’s swing. We know outcome metrics like wOBA are a good measure of value and performance, but they don’t tell us much about process. Batted ball data tells us something about process because the data isn’t a function of the defense. The data is admittedly binned into only three categories without any sort of velocity information, but it’s useful information if used properly.

How to Use Batted Ball Stats:

Batted ball statistics, like most statistics, should be used with caution for three key reasons. First, sample size is very important for the batted ball stat you likely care most about for hitters — line drive rate. While you can get a good sense of fly ball and ground ball rate with a month or two of data, it takes more like a year and a half for line drive rate to “stabilize.” All this means is that six weeks of batted ball data shouldn’t change your opinion of a player’s talent level.

Second, batted ball classification is tricky. What’s the difference between a fly ball and a line drive? At what angle does one become the other? While BIS has a great team scouting each major league game, video data only offers only a certain level of detail. Even the most diligent stringer can’t get it right 100% of the time because they just don’t always have the proper angle to distinguish between a fly ball and line drive. When StatCast becomes fully operational, this problem should disappear because we will be able to use a simple numeric cut point.

Finally, and most importantly, not all line drives/fly balls/ground balls are created equally. A pulled fly ball traveling at 105 mph to deep left field and one that lands harmlessly in the glove of the right fielder are extremely different. A screaming line drive up the game and one that’s easily caught by the shortstop are different. This is essentially another example of the data being a continuous (in launch angle, direction, and velocity) but presented as discrete data. A ball isn’t a fly ball or a line drive, it is hit at X launch angle, Y degrees from center, at Z velocity.

Our categorization is helpful, but it is far from perfect. For example, in 2014, Brandon Crawford and Anthony Rizzo had very similar batted ball statistics, but Rizzo was clearly the better hitter overall as the quality of his contact within those categories was much better than Crawford’s.

Essentially, use batted ball stats as a guide, not an anchor.


Please note that the following chart is meant as an estimate, and that league-average batted ball rates varies slightly on a year-by-year basis. To see the league-average batted ball breakdown for every year from 2002 to the present, check the FanGraphs leaderboards.

 Type League Average
LD 21%
GB 44%
FB 35%
IFFB 11%

Power hitters will generally have higher fly ball rates (~44%), while contact hitters normally have high ground ball rates (50+%). And all hitters will hit their share of infield flies and they generally do not correlate that strongly from year to year.

Things to Remember:

● A line drive produces 1.26 runs per out, while fly balls produce 0.13 runs per out and ground balls produce 0.05 runs per out. In other words, batters want to hit lots of line drives and fly balls, while pitchers generally want to cause batters to hit ground balls.

● Players that don’t hit many balls in the air (higher GB% with lower FB% and LD%) generally have higher BABIPs and batting averages, but have limited power.

● This data is tracked by Baseball Info. Solutions (BIS), which is why it’s only available for players back until 2002.

● GB/LD/FB% are calculated per ball in play.

● IFFB% is per fly ball.

Links for Further Reading:

BABIP: Slicing and Dicing Ground Ball Out Rates – Baseball Analysts

Ground Balls and You – FanGraphs

How Batted Ball Distance Ages – Hardball Times

Redefining Batted Balls to Predict BABIP – Hardball Times

Exploring Batted Ball Run Values and Spray – Hardball Times

Steve is the editor-in-chief of DRaysBay and the keeper of the FanGraphs Library. You can follow him on Twitter at @steveslow.

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danielschwartz.rotobanterLukeEnricoPalatzzoDmanelDeuce of Spades Recent comment authors
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Is there anywhere I could find results splits for batted ball types for individual batters (for example, what percentage of Albert Pujols’ line drives resulted in HR; what percentage of Josh Hamilton’s fly balls resulted in 2B)?

Deuce of Spades
Deuce of Spades

Hi, I had a question about line drive %. I was under the impression that it correlated fairly strongly with BA, but it seems there are some guys like Bartlett and Pennington who have pretty high LD % and still don’t hit for much of an average. Can anyone explain why that is?


Am I missing something obvious, or is there a big difference between the production numbers cited here, and the ones in the linked Baseball Analyst article? ( Fangraphs: “- A line drive produces 1.26 runs/out, while fly balls produce .13 R/O and groundballs produce .05 R/O. In other words, batters want to hit lots of line drives and fly balls, while pitchers want to make batters hit groundballs.” Baseball Analyst: “However, when it comes to production, flyballs are more valuable than groundballs. To wit, including home runs, line drives produced .40 runs in 2007 and .39 in 2008, while the… Read more »


Sorry, the difference is obviously R/O vs. R/PA. I missed that.


While all line drives could be called “well-hit”, the ground balls and fly balls cannot be distinguished as such. Some ground balls dribble to the pitcher while others burn down the 3rd base line. Fly balls are similar. Is there a stat available here where you can see the amount of balls hit from say, -5 degrees to +40 degrees with the horizontal, and with a minimum velocity? Call it the GW%, for Good Wood %.


So what percentage of flyballs in play go for hits? groundballs? line drives? i know they even out to about 30% but im just curious what the league average is even though it may vary by hitter


Luke, A while back (definitely not 2011 or 2012) i know the following: LD GB FB % turned into an out 26% 72% 79% % turned into a hit 74.00% 28.00% 21.00% I want to find this data for 2012 so that i can make my 2013 projections. As mentioned above, FB may cost more outs overall, but they are more valuable because naturally FB will lead to HR.


FYI i think this data was from 2004 (via THT):



Does anyone have the data or can steer me toward the data for the following:
What is the percentage of LD/GB/FB that became hits in 2012. In short, I am trying to project how many overall hits a player is expected to have based on this which will lead me to an expected average (versus trying to associated it to BABIP or other strategies). This can also help me with projecting HR totals obviously if I project/assume a HR/FB ratio.