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Sunday, December 18, 2011
Latos and park factors
Too much is made of matchup stats (i.e., how batter X does against pitcher Y after 20-40 plate appearances, while ignoring each player’s career 2000 plate appearances).
At the same time, is too little made of individual player-park factors? If you have 3000 plate appearances of Barry Bonds at 3Com and away from 3Com (is that what it was called then? I can’t keep up with corporate names), and he hits as many HR at home as he does on the road, do we really care that the average LHH hits two-thirds as many HR at 3Com than away? I say: NO! Barry Bonds has very little in common with those hitters, other than handedness, but (traditional) park factors DEMAND that we treat Bonds as being tightly coupled with that group.
This is Mat Latos’s career Petco / non-Petco slash line (BA, OBP, SLG):
.229 .287 .348
.224 .286 .351
I won’t even bother to tell you which is Petco and which is not, since it’s the same thing! The question is: did he simply have made luck at Petco and good luck away from Petco? Or, is his talent level such that it’s an important parameter when looking at the park factors of the rest of the players? That is, with Bonds, he hits HR so far, that it doesn’t matter that 3Com suppresses HR.
Similarly, is Petco such that Latos can’t benefit from its pitcher-friendliness? I DON’T KNOW. But, these are the kinds of valid questions that are out there.
Latos’ strikeout rate per PA is 23.7% at home and 23.4% on the road. His walk rate is 6.9% at home, 7.9% on the road. His HR rate is the same 2.2% at home and on the road. His BABIP is .283 at home and .276 on the road.
Therefore, we need to do just like we do with handedness splits: personalize them. In The Book, we showed that you take the observed handedness splits and regress them toward the league mean (by adding 1000 PA for LHH and 2200 for RHH, to the number of their PA against LHP). We need to come up with the same thing for parks.
The problem is that you may have to come up with a different regression amount for each park AND for each quality of player. It makes it a tougher job.
So, we can’t presume that Latos was either:
a. completely unaffected by Petco (as evidenced by his splits)
b. extremely unlucky at Petco (as evidenced by all MLB players at Petco)
The truth is somewhere in the middle.
My guess is that it is much closer to b. I doubt that pitchers as a whole have much in the way of unique park factors.
One easy way to test this is to take all the pitchers with no or reverse park splits in one year and look at them the next year. Do this for several years of course in order to have a large sample. My guess is that these pitchers will regress almost 100% toward the normal splits for those parks. You can do the same thing for pitchers with extreme park splits (in the “normal” direction for that park).
E.g., split all 30 parks into 2 groups - pitchers and hitters parks (you can leave out the neutral parks if you want). For the hitters parks, look at all pitchers with better (or the same) stats in those parks, adjusted for H/R of course. Do the same for the pitcher’s parks - compile a list of pitchers who performed worse in those parks. Then look at each group the next year.
Again, my guess is that they will regress most of the way towards the normal park splits.
I actually suspect much the same for hitters, although perhaps not to quite the same extent as the pitchers. I reject Tango’s theory about Bonds (that we can completely ignore the normal LHH park splits at Pac Bell in favor of Bonds’ own splits).