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Aha

I've been trying to figure out why the Phillies offense looks so awful, so often, when, in both overall terms and key splits (runners in scoring positionclose and late, etc), the numbers suggest it's very good.

Maybe this is it: 

Name (PA) AVG-D OBP-D SLG-D OPS-D OPS-O Difference
Burrell (125) .290 .425 .670 1.095 1.000 .095
Coste (55) .288 .327 .519 .847 .806 .041
Howard (137) .250 .348 .467 .814 .837 -.023
Utley (127) .250 .336 .448 .784 .963 -.179
Victorino (106) .310 .349 .430 .779 .748 .031
Rollins (113) .257 .330 .396 .726 .768 -.042
Jenkins (99) .223 .260 .383 .643 .680 -.037
Ruiz (75) .200 .333 .292 .626 .573 .056
Werth (68) .167 .286 .333 .619 .820 -.201
TEAM .241 .323 .402 .726 .775 -.049

"D" is daytime splits; "O" is overall. So what this tells us is that the Phillies as a team hit a hell of a lot worse when the sun is out for the whole game. Chase Utley and Jayson Werth are the worst culprits; Utley turns into, essentially, a league-average second baseman, while Werth devolves into something like T.J. Bohn. The only Phillie who hits noticeably better during the day is Pat Burrell, which offers maybe the best evidence that his carousing days are really behind him. As a team, the Phillies approximately go from Mike Jacobs overall to Jose Castillo during the day. 

The Phillies as a team are 12-19 in day games, the worst record in the NL East and fifth-worst in the majors, ahead of only the three last-place AL teams (Baltimore, Cleveland, and Seattle) and the Rockies. Here's hoping for a lot of rainy Sundays between now and September. 

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Eureka!

I think you might have something here, but I’m not sure yet.

On one hand, I generally hate fake splits data for the following reason: statistical significance entails testing whether the odds of such an extreme difference in outcomes would occur are less than 5%. In other words, 1/20 of all randomly generated splits tests will yield a false positive—and lead us to conclude that such a split is a significant difference, and we’ll go searching for causes.

So, I generally treat this type of stuff with hesitation. The cumulative data is not significant—the differences in day/night AVG and OBP (it’s harder to test SLG since it’s not a percentage) are NOT statistically significant.

However, aggregating data blurs results at times so I did look at individual players. If you check 10 regulars/starters (you skipped Feliz, but I assume you meant to), you will expect that about 0.5 of them will yield a false positive.

However, it looks like Werth does have a significantly higher AVG in the night than the day this year and a significantly higher OBP at night in his career than during the day. His OBP in 2008 and AVG in his career both narrowly missed statistical significance, but are worth nothing at least.

Utley just misses statistical significance for his career OBP, with the odds of his 34-point OBP difference happening by chance falling at about 8%. The sample sizes for 2008 are too small to look at anyway.

Feliz actually just missed statistical significance for the difference between his daytime and nighttime average (.191 day, .290 night), but his career shows basically no difference (.250 day, .255 night).

It could very well be that randomness is generating these results, but I’m not quite sure. There does seem to be some evidence that Utley and Werth probably are better night hitters than day hitters. Still, I’m not completely convinced. It’s definitely worth noting, and it might be useful when deciding on off-days for players.

by Matt Swartz on Jul 21, 2008 12:49 PM EDT reply actions  

Thanks.

The hell of it is that I took three terms of quantitative methodology in graduate school; I passed the courses; I didn’t cheat; and yet I recall pretty much none of it. It’s about as useful as my high school Spanish, in that in both cases I can sort of understand what someone else has written, but I can’t really use either myself.

In general, though, when I post stuff like this it’s more to try and explain what I’ve seen than offer a hypothesis as to causal relationships. I leave that to bigger brains such as yourself.

Oh, and skipping Feliz was a screwup… which is a shame, because it’s supportive of my point. Daytime splits (101 AB): .191/.248/.277/.524. Overall: .262/.311/.434/.745. So he’s 221 points of OPS lower during the day, making him the single worst offender on the team.

by dajafi on Jul 21, 2008 6:15 PM EDT up reply actions  

Sounds good. I’m not quite sure why hitters are worse in the day or night. I’m guessing it has to do with vision and picking up the ball as it’s pitcheed, maybe the same types of comfort that might have to do with homefield advantage.

As for the formula, it’s actually not that bad. If you’re curious (or if anybody else wants to test something), it goes like this:

Say you have {1}: X(a) sucesses in N(a) trials for group a {2}: X(b) sucesses in N(b) trials for group b

Then come up with three probabilities:
(1): p(a)= X(a) / N(a)
(2): p(b)= X(b) / N(b)
(3) p(a&b)= [X(a)+X(b)] / [N(a)+N(b)]

Then the formula is:

[p(a)-p(b)] / square root of [ (p(a&b) * (1-p(a&b)) * (1/N(a) + 1/N(b)) ]

If this number is bigger than 1.96 or smaller than -1.96, you have statistical significance For example, it works very well with batting average. p(a) and p(b) are batting averages in each spit and p(a&b) is total batting average, and N(a) and N(b) are the number of at-bats both ways.

As for whether I’m “bigger brains”, it’s a good thing you haven’t seen me try to remember my high school Spanish! I was so bad that even after taking it for 2 years of middle school and 4 years of high school, I still couldn’t pass out of it for college and needed to take a semester there. My wife is perpetually confused when she asks me what something in Spanish on TV or whatever means, and I still don’t know despite my 7 years of studying it.

by Matt Swartz on Jul 21, 2008 8:45 PM EDT reply actions  

LaRoche of the dodgers, would anyone be interested in him?

by jemagee on Jul 25, 2008 9:56 PM EDT reply actions  

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