If there were some antecedent reason to expect the middle games to be different, then I’d be more inclined to think it was ‘real’. ]]>

Seriously, I’d be inclined to accept the middle games being the product of chance, if 1,2, and 6 didn’t all have a much higher winning percentage than 3,4, and 5.

]]>I do think the total number of WS games played is large enough to support the conclusion that the home field advantage overall is a real one. Here’s one way to quantify this judgment.

The null hypothesis is that there is no home field advantage at all, that knowing which team is the home team in some future game will give you no information about who will win. Our alternative is that there is a home field advantage (it does not include that there is a disadvantage — it’s obviously reasonable to use a ‘single-winged’ test). The data in William’s table support rejection of the null hypothesis with significance at the .005 level. That means if you just modeled the games by a coin flip, the chance of getting a result as skewed toward the home teams as the historical results are is tiny — a half of a percent. It’s extremely unlikely that the results are just due to noise.

(The confidence interval here is .513 to .591. That is to say, we can be 95% confident that the real advantage to the home team is somewhere in there — the best guess is that it’s the 55.2% that we actually saw, but it wouldn’t be hugely surprising if the true advantage were as small as a little over a percent or as large as 9 percent.)

But the sample size for the middle games doesn’t support any interesting conclusions about those games. If we just take the simple hypothesis that in every single game being the home team gives you a 55% chance of winning, we should not be at all surprised to see that in a historical data set there are some spurious patterns, patterns like the loss of the advantage in middle games. My bet is that’s what’s going on in the data.

]]>I think there are two legit approaches: (1) develop a saber-type formula to normalize differences and come out with a rating; or (2) have some fun with it and attach to the ASG, which does have way of representing which league is better.

]]>i am definitely not a fan of the random approach.

but there is really no good reason why home field cannot go to the actual team with the best record.

the nba has more teams in the playoffs and thus more potential sights for where the finals ends up being so the logistics argument is crap to me.

the cards got home field this year because their current biggest rival’s chubby 1b hit a home run in the asg – i don’t see how the cards had anything to do with that :}

]]>[2] Perhaps, but the uptick really isn’t that big. Having larger crowds could explain the difference (although that could also incorporate umpire bias). It would be nice to do a study comparing HF based on attendance figures, but don’t know of a database that has such information.

]]>i have never liked the idea that the asg is tied to homefield and have become even more opposed to it over time.

a team with a slightly better than middling record like the cards should not have homefield advantage.

[2] that seems to make a lot of sense.

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