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  1. Is there no honor on the internet!

    http://www.fangraphs.com/blogs/index.php/babip-splits/

    Comment by Not Actually Dave Cameron — February 4, 2011 @ 9:33 am

  2. +1

    Comment by Albert Lyu — February 4, 2011 @ 9:46 am

  3. 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?

    Comment by xdog — February 4, 2011 @ 9:57 am

  4. Aw, that’s cold — that article’s a year old. Statute of limitations and such. Besides, this extends the work a fair deal.

    Comment by skipperxc — February 4, 2011 @ 10:02 am

  5. That said — well played.

    Comment by skipperxc — February 4, 2011 @ 10:03 am

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

    Comment by bill — February 4, 2011 @ 10:16 am

  7. 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.

    Comment by kp — February 4, 2011 @ 10:27 am

  8. dang. 9 minutes too late.

    Comment by kp — February 4, 2011 @ 10:29 am

  9. 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

    Comment by Jeff Zimmerman — February 4, 2011 @ 10:31 am

  10. 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.

    Comment by APE — February 4, 2011 @ 10:35 am

  11. 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.

    Comment by John DiFool — February 4, 2011 @ 11:03 am

  12. 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.

    Comment by Nate — February 4, 2011 @ 11:07 am

  13. 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.

    Comment by chuckb — February 4, 2011 @ 11:16 am

  14. 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.

    Comment by Steve Phillips — February 4, 2011 @ 11:49 am

  15. 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?

    Comment by Linuxit — February 4, 2011 @ 12:17 pm

  16. 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?

    Comment by Steve Phillips — February 4, 2011 @ 12:49 pm

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  19. 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.

    Comment by Ratwar — February 4, 2011 @ 6:07 pm

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

    Comment by AJS — February 4, 2011 @ 6:23 pm

  21. I blame the Pirates for the disparity:)

    Comment by neuter_your_dogma — February 4, 2011 @ 10:02 pm

  22. 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?

    Comment by lex logan — February 5, 2011 @ 8:55 am

  23. 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

    Comment by Linuxit — February 5, 2011 @ 12:27 pm

  24. 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.

    Comment by Nathaniel Dawson — February 5, 2011 @ 1:31 pm

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

    Comment by Dan — February 5, 2011 @ 9:35 pm

  26. 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.)

    Comment by lex logan — February 5, 2011 @ 10:54 pm

  27. 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.

    Comment by Steve Phillips — February 7, 2011 @ 10:19 am

  28. “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.

    Comment by jacob — February 7, 2011 @ 11:03 am

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