clock menu more-arrow no yes mobile

Filed under:

The luck factor: How to maintain your BABIP and become a “gem”

The primer on how to create your own luck.

MLB: Chicago White Sox at Arizona Diamondbacks Mark J. Rebilas-USA TODAY Sports

Batting average on balls in play is one of the simplest sabermetric statistics, yet it’s also one of the most useful. BABIP measures how often a ball in play — defined generally as any batted ball that did not clear the outfield fence — goes for a hit.

BABIP is often used to determine which hitters are “lucky” versus “unlucky.” Generally speaking, about 30 percent of balls in play go for hits, making the league-average BABIP around .300, with a point or two fluctuation possible in either direction. (In 2017, the league-average BABIP was actually .300, but I would have used that as the general benchmark anyway.)

BABIP often tells us whether sample size is helping or hurting a player. If Player X is hitting .350/.450/.550 in the first two months of the season, but his BABIP is north of .400, we can expect him to regress at some point during the rest of the season. Still, depending on how long luck is going in Player X’s favor, he may still be in the midst of a career year. It works in the opposite direction, too, with underperforming players and low BABIPs, but that should be pretty self-explanatory.

The thing I’ve always wondered about BABIP is what factors help a player “control” it. Many of the best hitters in baseball are able to maintain relatively high BABIPs, and in this article, I hope to break down the factors that I believe lead to these out-of-the-ordinary BABIPs, as well as predict who is likely to maintain a high BABIP going forward.

I used the 25 highest BABIPs in the league from 2017 to try to find the factors that create high BABIPs. I will admit, 25 is fairly an arbitrary number, but I felt it gave me a large enough of a sample (around the top 17 percent of qualified hitters) to figure out these factors, which I’ll lay out below.

What makes this the most interesting, though, is that many of these hitters used different “tactics” to keep their BABIPs high. Some benefited mainly from luck, but most, if not all of them, had some special skill that did contribute to their abnormally high BABIP.

Through the article, I will refer to my 25 hitters as “BABIP gems,” for lack of a better term.

If you would like to see the full Google spreadsheet, please click here.

Hard contact

The league-average hard hit rate is 31.8 percent, but I would expect many of these BABIP gems to be roughly within the top-20 percent of the league in hard-hit rate.

Of the BABIP gems, eight out of my 25 found themselves within in the top-20 percent of batters in the Majors in hard-hit rate. Aaron Judge and Paul Goldschmidt, ranked No. 2 and No. 3 in the league in hard-hit rate, are members of the BABIP gems.

Here are all eight:

BABIP hard-hit gems

Name Hard% Hard% rank BABIP BABIP rank
Name Hard% Hard% rank BABIP BABIP rank
Aaron Judge 45.3% 2 0.357 8
Paul Goldschmidt 44.3% 3 0.343 20
Corey Seager 44.0% 4 0.352 12
Justin Upton 41.0% 13 0.341 23
Domingo Santana 39.7% 19 0.363 6
Marcell Ozuna 39.1% 23 0.355 9
Tim Beckham 39.1% 23 0.365 5
Charlie Blackmon 39.0% 25 0.371 2

There seems to be a pretty strong correlation between having an excellent hard-hit rate and a good BABIP, but it does not mean everything. Of the top 29 players across the league (approximately the top 20 percent of the league) in hard hit rate, 17 had BABIPs above the league-average mark of .300. For the other 12, does this mean that they were unlucky? It’s quite possible, but hard-hit rate isn’t the only thing that leads to a good BABIP.

Fly balls

In the age of “elevate and celebrate,” I thought that hitters with a high fly ball rate might also have high BABIPs. I was wrong, and it conceptually makes sense why.

For the purpose of BABIP, home runs are not considered batted balls, since they leave the yard. So every time a batter celebrates a four-bagger, they aren’t helping their BABIP. And that also makes sense, too. There’s no chance for a fielder to make a play on a home run, so hitters should not get credit toward their BABIP for putting a ball into orbit.

Just two BABIP gems — Justin Upton and Aaron Judge — had fly ball rates that ranked within the top-20 percent of the league. In fact, 17 of the BABIP gems, or 68 percent, had fly ball rates below the league average of 35.5 percent. If you want to elevate and celebrate, be prepared to have a low BABIP.

This also could explain the hard-hit rate. Batters like Joey Gallo, who hit the ball very hard, also are those that hit a lot of fly balls and home runs, and that could be why the correlation between hard-hit rate and BABIP isn’t as strong as I would have originally thought.

Line drives

According to FanGraphs, batters hit .689 on line drives last season, so it would make the most sense that prominent line-drive hitters would have the highest BABIPs in the league. That idea holds pretty true with the numbers, as 10 BABIP gems ranked within the top 20 percent of the league in line drive rate.

Here’s how they break down:

BABIP line drive gems

Name Line Drive% Line Drive% rank BABIP BABIP rank
Name Line Drive% Line Drive% rank BABIP BABIP rank
Daniel Murphy 27.6% 1 0.341 23
Domingo Santana 27.4% 2 0.363 6
Joe Mauer 24.9% 6 0.349 16
Chase Headley 24.9% 7 0.341 23
Corey Seager 24.8% 8 0.352 12
DJ LeMahieu 24.7% 9 0.351 14
Buster Posey 23.3% 19 0.347 17
Dee Gordon 22.8% 25 0.354 10
Chris Taylor 22.6% 27 0.361 7
Cesar Hernandez 22.6% 27 0.353 11

I’m fascinated by the fact that six of the top 25 hitters in BABIP ranked within the top 10 hitters in the league in line drive percentage. And of the top 29 batters in line drive rate (again, the approximately top 20 percent of the league), just four had BABIPs below .300, giving a high line drive rate a stronger correlation with a high BABIP than hard-hit rate.

The four hitters in the latter group that couldn’t eclipse the .300-BABIP mark — Miguel Cabrera (.292), Alex Gordon (.261), Freddy Galvis (.292) and Dansby Swanson (.292) — could be in line for an improved year in 2018 as their luck seemingly evens out.

If you want a high BABIP, hit line drives. More simply, just be Daniel Murphy.

Speed (perhaps paired with ground balls)

Another aspect that could lead to high BABIPs is speed. Faster runners could be able to run out more ground balls for hits, stretching their luck by the virtue of having a fruitful skill. In addition, these hitters might benefit from having a high ground ball rate.

It’s not advantageous, for example, if Dee Gordon tried to put the ball in the air. It wouldn’t make sense — like Willie Mays Hayes in Major League, Gordon doesn’t have a lot of power, so he won’t hit a lot of homers. But, if he can stretch more infield hits out with his speed, he’ll be better off.

Six batters who had sprint speeds within the top 20 percent of the league were BABIP gems:

BABIP speed gems

Name Sprint Speed Sprint Speed rank Ground Ball% Ground Ball rank BABIP BABIP rank
Name Sprint Speed Sprint Speed rank Ground Ball% Ground Ball rank BABIP BABIP rank
Dee Gordon 29.7 4 57.6% 1 0.354 10
Tommy Pham 28.7 37 51.7% 12 0.368 4
Cesar Hernandez 28.7 37 52.8% 9 0.353 11
Chris Taylor 28.6 43 41.5% 86 0.361 7
Javier Baez 28.3 71 48.6% 25 0.345 18
Marcell Ozuna 28.2 80 47.1% 35 0.355 9

Interestingly, Gordon, Pham, Hernandez and Baez all had ground-ball rates that also ranked within the top 20 percent of baseball. And given their skill sets, that might just be okay.

The hitters who could maintain their BABIP

Here are all the hitters I have deemed to have a special skill that should be able to maintain their BABIP in the future. If they made one of the three lists (I omitted fly ball rate), then they’re listed here:

BABIP gems

Name Hard Hit Line Drive Speed
Name Hard Hit Line Drive Speed
Aaron Judge X
Paul Goldschmidt X
Corey Seager X X
Justin Upton X
Domingo Santana X X
Marcell Ozuna X X
Tim Beckham X
Charlie Blackmon X
Daniel Murphy X
Joe Mauer X
Chase Headley X
DJ LeMahieu X
Buster Posey X
Dee Gordon X X
Chris Taylor X X
Cesar Hernandez X X
Tommy Pham X
Javier Baez X

There were 18 hitters to show up on at least one list, which is 72 percent of the overall pool that I started with. This probably means that the qualifications I chose were fairly solid ones.

Six hitters, including Corey Seager, Dee Gordon, Cesar Hernandez, Chris Taylor, Marcell Ozuna and Domingo Santana, showed up on multiple lists. If I had to predict which batters I’d expect to be near the top of the league in BABIP again, I’d start with this list of six.

What’s also interesting is that many of the speedsters (Gordon, Hernandez and Taylor) also were very good at hitting line drives. They know how to get on base, and as a result, these should be the guys near or at the top of your order, assuming that they know how to walk, too.

Here are the seven hitters to not make any list:

BABIP lemons

Avisail Garcia 0.392 1
Jose Altuve 0.370 3
Trey Mancini 0.352 13
Eric Hosmer 0.351 14
Odubel Herrera 0.345 19
Marwin Gonzalez 0.343 20
Mark Reynolds 0.343 20

There are some interesting names on this list, too. My favorite overrated player, Eric Hosmer, found himself on this list; if you’re a team interested in signing him, then that could be something to think about going forward. He probably had a lucky season in 2017. Avisail Garcia, too, had a great year in 2017, but I wouldn’t expect him to repeat it to the same level going forward.

Why does it matter?

It’s a skill to be able to maintain a high BABIP. Most of these players, by having high BABIPs, had above-average offensive outputs across the board. In my pool of 25, only four hitters had a wRC+ of 100 or below.

Having a high BABIP isn’t the only way to be a successful Major League hitter, but it can certainly help you get there.

It’s always good to have a little luck on your side. And there’s no better luck than the luck that you create on your own.

Devan Fink is a Featured Writer for Beyond The Box Score. You can follow him on Twitter @DevanFink.