Batter's Box - ShockDome (February 5, 2004)
A good study (though I'd ignore the talk about individual effects... at this level, the best you can do is look at the group effect).
To summarize: the pitcher's pre Toronto years had a HR rate of 1.02 (I suppose that's per 9 IP). While you'd expect these pitchers to have a HR rate allowed of 1.18 in the skydome, in their first year there, they were 1.31. The author calls this the "shockdome factor".
Sample size issues should not be ignored (as noted in the study). As well, I would have used only the last 2 or 3 years of a pitcher's HR rate. Finally, per PA would be preferable to per IP.
All in all, a pretty good study that opens the door for some more investigation.... not only for the Skydome, but reasonably for every single park. It's possible that a pitcher gets a "shock" in pitching a first season with new fielders or new parks or new league, etc. It would be nice to also see the effect not only for the first year in the new environment, but presumably by the 2nd or 3rd year, this shock should have settled down.
--posted by TangoTiger at 09:33 AM EDT
Posted 11:04 a.m.,
February 5, 2004
(#1) -
Leigh
You are correct, sir. It would be better if it uses hr/pa and included three year rates both ways rather than career/one season. It also would have been better if I had made a composite hr effect for each pitcher based on the parks they played in before SkyDome. Further, it could have been better if I would have used the SkyDome homerun factor for the year in which the pitcher pitched there, not simply the 2003 factor for everybody. If fact, had I done it that way, the ShockDome Factor would have been more prolific, as 2003 was had a particularly high homerun rate for the Dome.
Posted 11:06 a.m.,
February 5, 2004
(#2) -
Leigh
Sorry, three typos there. That comment, like the study itself, was quick and dirty - although neither ought to be dismissed.
Posted 7:46 p.m.,
February 5, 2004
(#3) -
MGL
Yes, an interesting study that definitely requires more research. I agree that it is critical to use weighted 3 or 4 year HR rates for the pre-SD HR rates and not career HR rates (it wasn't obvious whether he used career HR rates. I don't think he specified). The whole affect, or a good portion of it, might be simply the affect of aging (Tango has HR rate peaking at age 21). One could look at a control group of pitchers of about the same age as the ones in the study.
I don't think it is critcal to use more than one year after going to the Jays, although it would increase the sample of size for the post-move HR rate. It is also not critical to park adjust the pre-HR rates, although it would also help given the small samples. Bascialy whenever you do a study with large samples, adjusting for context, or using more than one year of data is not that important. With smaller samples, it is more important.
I also don't think that you want to use anything but a multi-year (averaged over the history of the Skydome) and regressed HR factor for Skydome. I definitely don't think you want to use the actual HR factor for the year(s) in question. That is almosy never the correct thing to do, otherwise you end up essentially "regressing" all the sample HR rates, since the park factors for any given year are generated from the sample H/R splits of the home players themsleves (or at least "half" of the park factor). IOW, if all the Toronto pitchers in one year had HR rates 1.5 times their road HR rates, the park factor would be 1.50 (if you just used the home playres to generate the PF's) and yo uwould just end up dividing their home HR rates by 1.5, so no matter what the sample HR park factor was for that year, all TOPR pitchers would have a park adjusted home HR rate exactly equalk to their road rate, which makes no sense.
As I said, intersting premise and the results give one pause for thought and an impetus for more work. Good job!