For example, to find out Ryan Church's lifetime stats vs. Tim Hudson, and vice versa.
Sportsline used to have them, but I don't see it on their site anymore. I checked mlb.com but you can only search by a specific year and the links don't always work.
Bwanna's add-on stuff used to do that, but mine doesn't any more. Might be worth digging his Yahoo scripts thread up and having a look. (His stuff rocks)
AussieDodger
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Yeah. I use Yahoo for splits and individual pitching matchups too.
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Steve-o
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FWIW, most studies show that this match-up information is pretty useless for predicting how batters will do the next time they face a pitcher. Use at your own risk.
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GotowarMissAgnes wrote:FWIW, most studies show that this match-up information is pretty useless for predicting how batters will do the next time they face a pitcher. Use at your own risk.
Thanks for a point I wasn't aware of. But I guess I shouldn't be suprised. After all, unless you are named Dusty Baker there are tons of obvious baseball things that were disproven by math.
Although I understand the overall concepts, I'm not a SABR expert. I would assume that in this case, one of the main issues is around sample sizes. A batter just doesn't face a pitcher enough to know if his success/failure is indicative of a true trend or just short term results that will regress to the mean.
Do you know more about those studies GotowarMissAgnes and anything in the results as to why it is not predictive data? Is it sample size or are there other factors in play?
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GotowarMissAgnes wrote:FWIW, most studies show that this match-up information is pretty useless for predicting how batters will do the next time they face a pitcher. Use at your own risk.
Yeah. That kind of information is a last, last resort for me.
I do create a lefty/right cheat sheet from the Yahoo stats that I check everday for every league I am in. It's quite a bit of work, but I believe the results are worth it.
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Steve-o
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Yeah, I don't take these batter/pitcher match-ups as gospel, I just use them as guidance on deciding between fringe players when the sample sizes are big enough to try to get a semi-accurate forecast.