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I recently read an article where the author cited a hitter’s .278 BABIP in 2014 comparable to the MLB-average .300 BABIP and concluded the player was “unlucky” and would see a more prosperous 2015. This reminded me of mistakes I made when I first began playing fantasy baseball. Making conclusions about a player’s “luck factor” based solely on his BABIP comparable to the league-average is a common fantasy baseball mistake, but it is one that is easily correctable by digging deeper into the numbers. For purposes of this article, we’re discussing BABIP ONLY as it pertains to hitters, not to pitchers.

By looking at the type of hitter a player is, the speed of that player, and that player’s spray chart, we can more accurately identify when a player has been luckier or unluckier than normal.

For a brief summary, BABIP stands for “Batting Average on Balls In Play.” The exact formula is here: In it’s simplest concept, BABIP measures the batting average of a hitter when we remove his Home Runs and strikeouts from the equation.

BABIP Factor 1: Hitter Profile

The first step to accurately utilize a hitter’s BABIP is to look at their hitter profile. In other words, what TYPE of hitter is that player? Generally, guys who hit lots of groundballs and/or flyballs will generally have a lower BABIP. On the flipside, batters who are line-drive hitters generally tend to have higher-than-average BABIPs. Line Drives are generally harder-hit balls than groundballs and flyballs, so line drives generally have a greater likelihood of dropping in for base hits. Joey Votto is Exhibit A for this. On the surface, Votto’s .355 career BABIP looks insanely lucky. But when 1 out of every 4 ABs ends in a line drive, the odds of the ball dropping in for a hit skyrocket.

In this same vein of thought, it is more important to look at a hitter’s single-season BABIP RELATIVE TO HIS OWN CAREER BABIP than it is to look at that single-season BABIP relative to the league-average BABIP for that same season. In other words, Votto’s .360 BABIP in 2013 may look extremely lucky, but when compared to his .355 career BABIP, it suggests no such “luck” on Votto’s part. In comparison, J.J. Hardy is a career .278 BABIP hitter because he’s much more of a flyball-groundball hitter. Therefore, seeing Hardy post a .270 BABIP in a single season in no way suggests bad luck on his part because that’s the type of hitter he is.

BABIP Factor 2: Speed

Again, this is something that should be factored in on a case-by-case basis, but as a general rule, faster hitters are going to have a higher BABIP than slower hitters. Why? The explanation is quite simple–a faster player is more likely to turn infield groundballs into hits than slower players. Billy Hamilton, for example, has a far greater probability of beating out a groundball to the shortstop than Victor Martinez does. In 2014, Billy Hamilton had an 11.2 Infield Hit% (in other words, the percentage of groundballs that became infield hits). For Victor Martinez, that number was 4.2%. Taking into consideration that the two had a fairly similar overall Groundball % (41.5% for Hamilton; 40.6% for Martinez), this strongly suggests that Hamilton’s speed will allow him to squeeze a few extra hits out of what would be groundball outs for the average player, while Martinez’s lack of speed may cost him what would be a few hits on tough diving plays against the average player.

BABIP Factor 3: Spray Charts

Lastly, in order to better recognize when a hitter has been “lucky” or “unlucky,” we also need to look at WHERE the hitter is hitting the ball, especially in this day and age of the defensive shift. Many extreme-pull left-handed hitters face the shift. David Ortiz, Mark Teixeira, Ryan Howard, and Eric Hosmer are just a few of the names that come to mind, and there are a few right-handed hitters that face it too. The use of spray charts is generally more effective in DISPROVING a claim of a hitter’s BAD LUCK than it is in PROVING a claim of a hitter’s GOOD LUCK. This is because extreme-pull hitters who commonly face (and hit into) the shift are more likely to have a lower BABIP than other players because they’re more likely to “give away outs” by hitting the ball at a fielder.

For purposes of this example, let’s focus on Hosmer, a player who has seen drastic fluctuation in his BABIP. Check out Hosmer’s spray charts from 2012 to 2014:

In 2012, Hosmer had a .255 BABIP, horrid if you use an oversimplified analysis of how to utilize BABIP. However, if you look at Hosmer’s 2012 spray chart, you see two things that stand out: 1) a MASSIVE concentration of groundballs to the right side of the infield; and 2) an overwhelming concentration of flyballs and line drives to the opposite field. 2012 saw Hosmer’s highest career GB %, a whopping 53.6%. In other words, Hosmer was pounding the ball into the ground more than ever, and most of those played right into the hands of the shifts that teams began to employ against him.

Now compare Hosmer’s 2013 and 2014 spray charts. Hosmer had a .335 BABIP, which on its face appears abnormally high. But looking at the spray chart, Hosmer hit fewer groundballs into the shift, as well as hitting fewer groundballs overall, and drove the ball to all fields. In other words, it appears that Hosmer adjusted to the shifts by using all fields and pulling the ball less frequently. Hosmer’s 2014 BABIP was a solid .312, but his spray chart actually suggests he made even further adjustments, as his line drives and flyballs show an even greater balance.

This information bodes well for the possibilities of Hosmer to continue to have a BABIP well over .300, despite the fact that he’s a predominant groundball hitter with subpar line drive rates. But the point of this example is not to make a prediction on Hosmer. Rather, it’s to show you that, it doesn’t matter how hard a batter hits the ball. if he hits it right at a fielder, it’s likely going to result in an out.


As you can see, there are many considerations that need to be used when evaluating a hitter’s BABIP. It is a dangerous oversimplification to compare a hitter’s single-season BABIP to the MLB-average BABIP for that same season. However, as with many statistics, you should never rely on a single factor in analyzing BABIP. In my opinion, it is extremely important to look at 1) the type of hitter a player is (and in conjunction with that, what that player’s career BABIP is); 2) the speed of that player (or their ability to “leg out” extra hits); and 3) a player’s spray charts (to determine if he’s truly unlucky, or if he’s just hitting right into the shift). By combining these 3 factors, you can more effectively identify whether a player is likely to experience regression from the previous season, or whether he was unlucky and is a bounceback candidate.

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