BABIP and Home Field Advantage

With several recent discussions (here and here and here and here) on home team advantage (HTA) – which began with Tobias Moskowitz’s and L. Jon Wertheim’s new book Scorecasting – I decided to see if I could find any reasonable causes for the advantage. I decided to look into areas that I thought home teams may have an advantage, namely errors (not much – about 2 wins league wide) and base running (some), but the number that caught my eye was the differences in batting average on balls in play from the home and away team. Here are the differences in BABIP for the home and away teams over the last few years:

As you can see, there is an average difference of about 0.007 BABIP difference between the home and visiting team. This difference is quite substantial when looking over an entire season, working out to about 230 hits per season for the entire league. Using an average of 0.54 runs created per non-home run hit (thanks Tommy), the run difference works out to be 123 runs or about 12 wins across the entire league. This effect accounts for about 17.5% of total home field advantage.

There are many potential causes for the difference – for instance, the away pitchers may be squeezed by the home plate umpire, leading to hitters counts and more hard hit balls. Another theory is that the home team’s defenders know the park better and can make more plays on balls hit into the field which lead to more outs. To answer these questions I used Retrosheet batted ball data from 2006 to 2009 (I have not yet updated my retrosheet data with 2010 info yet) to look for possible differences:

The main difference in the percentage of batted ball data is that the home team hits more line drives versus the away team, who tend to hit more fly balls. This will explain some of the overall difference since line drives are more likely to end up as hits. By adjusting the away team’s batted ball distributions to be the same as the home team’s distribution, the visitors BABIP raises to 0.299.

I am not sure of the exact cause of the difference, but here are some questions that could be explored: Do home pitchers feel comfortable throwing pitches that will end up as fly balls knowing that the ball will stay in the park? Could it be the same as the previous reasoning with the home town hitter knowing what they can’t hit out of the park and settle for line drives or ground balls instead? Could it be that the home hitters are able to take advantage of their home park’s dimensions, or are General Mangers just specifically compiling rosters to take advantage of how their parks play?

The rest of the difference in BABIP is shown by the differences in the rate that the batted balls become hits. BABIP for both pop ups and flyballs are the same between the home and away teams. The home teams have a nine point advantage with ground balls and a five point advantage with line drives.

The reasoning behind this difference can’t be easily explained. Is it the pitcher having to throw more pitches in the heart of the plate? Do the away infielders not know the infield well enough to predict all the possible bounces a ball can take? Do away fielders have a more difficult time seeing hard hit balls leaving the bat? Is there a home town bias in scoring different batted ball data?

I feel like I am just beginning to scratch the surface, but I am working on filling in the gaps. For one, I am looking into getting the home and away defensive splits, especially for the infielders vs. outfielders. I would like to see which fielders are being labeled as responsible for these extra hits (all infielders?, 70-30 with the outfielders?). Second, I am looking at taking the single month’s worth of Hit F/x data publicly available and checking to see if there are any differences in batted ball speed and distribution. While I set out to answer a few questions about home field advantage, I feel that I have raised just as many, if not more, questions. This is a subject that simply requires more research.




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Jeff writes for FanGraphs, The Hardball Times and Royals Review, as well as his own website, Baseball Heat Maps with his brother Darrell. In tandem with Bill Petti, he won the 2013 SABR Analytics Research Award for Contemporary Analysis. Follow him on Twitter @jeffwzimmerman.


28 Responses to “BABIP and Home Field Advantage”

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  1. xdog says:

    I’d like more information on differences in error rates. If home hitters have fewer errors on balls in play, that would increase their BABIP, yes?

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    • Jeff Zimmerman says:

      Year, Team, % of Batted Balls Leading to Error Total, ROE per 80000 PA
      2010 Home 1.42% 1137
      2010 Away 1.41% 1127
      2009 Home 1.28% 1027
      2009 Away 1.36% 1086
      2008 Home 1.28% 1022
      2008 Away 1.38% 1104
      2007 Home 1.30% 1043
      2007 Away 1.37% 1096
      Average Home 1.32% 1057
      Average Away 1.38% 1103

      ROE Difference 46.2
      Runs per Error 0.47
      Runs from Errors 21.7
      Wins Gained in all games ~2
      Percent of Total difference 2.5%

      Sorry lack of ability to make tables in the comments

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    • chuckb says:

      This was my guess as well — that some of the difference may be attributed to favorable home team scoring vis-a-vis errors called hits (or vice-versa). Based on Jeff’s comment above, however, that doesn’t appear to be the reason at all. Interesting.

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  2. bill says:

    Being used to the hitting background might help hit a few more line drives (the old, “seeing the ball better”).

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  3. kp says:

    My personal theory: batters hit more line drives at home because they’re used to the center-field-area background and can pick up pitches earlier, making more solid contact.

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  4. APE says:

    Home mound vs. Away mound. That little discomfort for the visiting pitcher might translate into hitter’s making more solid contact on LD, GB and FB’s.

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  5. John DiFool says:

    There’s a pretty huge triples gap between home and away (last year it was 484 vs. 382). Combined with the fact that away teams hit MORE doubles (!) (14 more), then that’s substantial evidence that familiarity with the home park strongly affects triples rates.

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    • Nate says:

      Yes, triples rate has always been the most obvious home advantage, almost certainly due the home outfielders being very familiar with what the wall will due to a given gapper.

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  6. Steve Phillips says:

    How much does the asymmetric nature of 9th inning affect this? Looks like this was pointed out (but not evaluated) before: http://www.fangraphs.com/blogs/index.php/babip-splits/#comment-64037

    Y’all should read the comments in DC’s article–lots of interesting ideas and possibilities for further reading.

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  7. Linuxit says:

    Another thing to factor in is the game situation and sample size. The home team doesn’t even bat in the 9th inning if they already have the lead, which prevents them from facing the away team’s closer in a save situation. The 9th inning pitcher had a .290 BABIP average in 2010. The BABIP for a closer in a save situation is probably even lower than that, but I don’t know where that number can be found. Anyways, this could decrease the BABIP for the away team. How much I don’t know. Also since the home team didn’t bat, their BABIP would have a smaller sample size in where they didn’t face a closer in a save situation, this would help the BABIP for the home team somewhat.

    Where can I find relief pitching splits for save and non-save situations?

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    • Steve Phillips says:

      Hmm…interesting…Has anyone checked to see if there are systematic lineup differences between home and away games? Do players on aggregate show the same splits, or is this partially due to the quality of players that the manager sends out there for H/A games? Likewise, is the manager more likely to “give up” on a game when on the road, subbing in earlier or with lesser players?

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    • AJS says:

      Why should closers have a significantly lower BABIP than the the average pitcher? Does this trend hold across all seasons?

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    • Linuxit says:

      I found the BABIP stats that I was searching for.
      http://www.baseball-reference.com/leagues/split.cgi?t=p&lg=MLB&year=2010#outco

      saves: .229 BABIP
      save situations: .292 BABIP
      non save situations: .300 BABIP

      Another thing that is huge is winning vs losing
      The winner has a .251 BABIP
      The loser has a .352 BABIP
      A no decision has a .297 BABIP

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      • Steve Phillips says:

        LOVE pages like that.

        Interesting: 9th inning has the lowest BABIP of any inning.

        I wonder how much of the game-situation splits are due to sampling bias. For example, we see that non-save BABIP > save BABIP. But skilled teams are going to have more save situations than less-skilled teams (I think), so that’s going to skew the BABIP numbers. Same with the ahead/behind splits (where pitchers pitching with the lead have a .005 advantage in BABIP). I’d love to say that splits like this point to a “teams try harder when they’re at home/leading/etc,” but I’m afraid that most of the differences in these splits (at least the game-situation ones) is due to sampling bias.

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  10. Ratwar says:

    Unless you eliminated inter-league data, that may be inducing some of the difference. In AL parks, NL teams need to use a pinch hitter as a DH, who is probably worse than his equivalent on the AL team so he’d hit less line drives. By the same measure, in NL parks, some AL teams try to start their regular DH in the field and sacrifice some defensive ability (especially at first base). I don’t think this would account for all of the difference in the BABIP, but it might account for some.

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  11. neuter_your_dogma says:

    I blame the Pirates for the disparity:)

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  12. lex logan says:

    No one has mentioned the crowd. I’m quite certain the crowd explains virtually all the home court advantage for basketball, and I expect it has the biggest effect in baseball, football, and other team sports. I recall hearing of a study on home court advantage in basketball, 20 or 30 years ago. Anecdotally, the University of Kentucky has always enjoyed a home court advantage in their once-a-year game in Freedom Hall (Louisville, away from Rupp Arena in Lexington, not counting games against the University of Louisville.) More telling, the Wildcats had one of the highest home court advantages in Southeast Conference play at Rupp Arena until a period in the late 80′s – early 90′s where, for various reasons, student attendance slumped and all student tickets were moved to the upper arena. I attended games in person both in the late 70′s when Rupp would explode in deafening noise and in the 90s when it was so quiet you could hear the sneakers squeak. The Cat’s home record slumped; they played better on the road some years. Then, the University moved some student seating back to the lower arena, the noise level returned to deafening (the students would fire up the entire crowd of 23,000) and the Cats resumed being a tough place for a visiting team to win (measured by conference games, which controls for quality of opponent.)

    So, did the A’s of the low attendance Charlie Finley years have a home field advantage?

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  13. Nathaniel Dawson says:

    Am I reading something wrong?

    The main difference in the percentage of batted ball data is that the home team hits more line drives versus the away team, who tend to hit more fly balls.

    Looking at the table, it shows the same percentage of FB for both home and road. Away teams seem to hit more groundballs than the home team.

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  14. Dan says:

    Is .007 really a significant difference in BABIP, even given the large sample size?

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    • lex logan says:

      Do you mean “practical significance” or “statistical significance” ? JZim discusses the practical significance in the second paragraph, BABIP accounting for about 17.5% of home field advantage. As for statistical significance, I might faint if anyone on Fangraphs bothered to compute a confidence interval or p-value, but I estimate the total sample size to be around 160,000 with an estimated margin of error of .0025 (for a 95% confidence interval), so yeah, .007 looks like it is statistically significant (i.e., unlikely to occur simply by chance.)

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  15. jacob says:

    “or are General Mangers just specifically compiling rosters to take advantage of how their parks play?”

    i think this point hits the nail on the head.

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