DIPS bookmarks (September 13, 2003)
James Fraser's bookmarks of all things DIPS.
--posted by TangoTiger at 10:45 PM EDT
Posted 12:56 a.m.,
September 14, 2003
(#1) -
Michael
Anyone know a site that tracks season to date DIPS numbers?
Posted 9:43 a.m.,
September 14, 2003
(#2) -
studes
(homepage)
DIPS is just way to complicated for me, and, as Tango has pointed out, FIP works just as well. (and it's a lot easier to calculate and understand). Here's the link: http://www.geocities.com/tmasc/drspectrum.html
But I don't know anyplace that keeps DIPS and FIP up-to-date by player (I have team FIP calculations in my graphs).
Posted 10:10 a.m.,
September 14, 2003
(#3) -
Patriot
This is a pretty cool resource James is putting together over there. I used to visit his site almost daily back when he was updating it a couple years ago, and now I think I'll have to start again. I see that he's working on organizing some of the old FanHome discussions into some workable format, which is a great effort.
Posted 8:28 p.m.,
September 14, 2003
(#4) -
Charles Saeger(e-mail)
Say, Tom, has someone ever looked at the randomness of pitcher/batter matchups to see how much of this explains year-to-year $H variations? Say, facing Tony Gwynn 8 times one year and 1 time the next and 7 other average yahoos would be about .42 hits over the course of the year, using Gwynn's career average $H.
Posted 10:07 p.m.,
September 14, 2003
(#5) -
James Fraser(e-mail)
(homepage)
Charles,
It would make sense, but I don't recall seeing such a study amongst all of those links (but I've only scanned through a lot of them). I'll let you know when I finish slogging through them.
James
Posted 11:32 p.m.,
September 14, 2003
(#6) -
Tangotiger
Charlie, I would guess it would not matter.
For example, I think MGL showed that there was a 2 to 3 run difference max / 600 PA with the quality of opposing pitchers for each batter. That is, 1 SD = 1 run / 600 PA. In there, it includes HR, BB, K. I would therefore guess that 1 SD would equal about .5 hits / 400 BIP, or 1 SD = .001.
1 SD for the park variation is .004, and the fielding is probably .007, and the pitching is .009.
So, I would guess that the hitting variation would be virtually insignificant.
Just an educated guess though...
Posted 7:55 a.m.,
September 15, 2003
(#7) -
studes
(homepage)
I think Charlie has a great idea. Just looking at BPro's lists randomly, Mike Mussina faced batters with a .273 BA, while Roy Halladay faced batters with a .266 BA. And we're not talking about big differences in BABIP for pitchers, are we?
I may be completely off, but it seems to me that batters are much more likely to face representative pitching samples than vice versa. A pitcher can start 30 games in a season but, due to scheduling quirks or just plan luck, face the same team 4 or 5 of those starts.
Posted 10:44 a.m.,
September 15, 2003
(#8) -
tangotiger
Remember, as long as the opposition hitting distribution is random, then we don't have to worry about it.
That is, you are trying to answer the following question:
"What is the true variance of the opposition hitting, over and above luck, that would produce the observed variance?"
If the observed variance is exactly as would be predicted by luck, then the true variance of the opposition hitting is zero, and we don't need to consider it as a variable. Don't forget that we are looking at the pitchers as a group, and we are not trying to pinpoint the effect on any single one pitcher.
I think that's right.