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OPS: Begone! Part 2
May 27, 2003 - Dave Studenmund
We know that BaseRuns is not a precise measure of run production for hitters (only for pitchers and teams).
Tango, I've completely missed this along the way. What do you mean by the above statement? Have you covered that in some of your previous articles? And why isn't it a precise measure for hitters -- because of team context?
Sorry if I'm rehashing old ground.
SABR 301 - Talent Distributions (June 5, 2003)
Discussion ThreadPosted 12:49 p.m.,
June 6, 2003
(#22) -
Dave Studenmund
(homepage)
Just a comment to help me fully understand the line of reasoning. Maybe add a graph that replicates #6 (placed before current #5), but by number of major leaguers instead of plate appearance opportunities. This would make the distinction between median and average more apparent.
Also, I have an incredibly picky point: the graphs are a bit big for my 800x600 screen resolution, and the right sides get lost. Sorry for being picky, but I thought you might like this pointed out.
SABR 301 - Talent Distributions (June 5, 2003)
Posted 11:29 p.m.,
June 6, 2003
(#24) -
Dave Studenmund
(homepage)
I originally thought of your first idea, Tango, but you're right. The second idea is better. Actually, it would be interesting to impose the one distribution on top of the other so the difference would be more apparent. Just an idea.
2003 Win Shares, updated (June 24, 2003)
Posted 10:51 a.m.,
June 25, 2003
(#2) -
Dave Studenmund
(homepage)
Good question. In fact, both Philly catchers have 0 win shares. The Phillies are getting no fielding contribution from their catchers, according to James.
The underlying reason is that Phillies' catchers have allowed 60 SB with only 8 CS, and have made 5 errors with only 22 assists.
2003 Win Shares, updated (June 24, 2003)
Posted 12:04 p.m.,
June 25, 2003
(#4) -
Dave Studenmund
(homepage)
Yes, that's one of my bigger beefs with Win Shares. It uses Saves to try and get at the "Leverage Index" Tango has put together. Obviously, the Leverage Index is much better than just total saves, but it requires pbp data. James probably overweighted the points given to saves, because he had nothing else.
The Nomo/Gagne ratio might no be that far off, however. I believe that the best leverage index Tango came up with recently over a four-year period was for Troy Percival's, at just under 2. If Gagne has pitched in a lot of one-run ballgames so far this year, or come in the middle of innings a lot, then 3 is possible. Especially if you add in the lower ERA (or component ERA, in this case).
2003 Win Shares, updated (June 24, 2003)
Posted 2:43 p.m.,
June 25, 2003
(#6) -
Dave Studenmund
(homepage)
Thanks, Tango. So to restate the "could be" argument, Gagne's leveraged index could double his contribution to the Dodgers. I checked, and half of his appearances have been with a one-run swing on the line. Seems to me an LI of 2.0 is conceivable.
Plus, his component ERA is substantially better than Nomo's. Gagne's FIP is -2.50, while Nomo's is 0.96. Add that to the LI, and an overall WS/IP ratio of 3.0 is conceivable.
I'm not saying it's "right." I'm just saying that this one instance of weird-looking win shares distribution may, in fact, reflect reality.
Ballpark Effects - By Type of Player (June 26, 2003)
Posted 1:18 p.m.,
June 27, 2003
(#3) -
Dave Studenmund
(homepage)
MAH, I remember that Bill James did this sort of analysis in one of his Abstracts. He came to the conclusion that you mention: Shea didn't hurt home run hitters as much as other type of hitters. I'll try and find it in one of his old Abstracts. Your take on the evolution of Shea sounds right on.
Got to admit, at this point I'm just as fascinated by the idea that ballpark effects in general may impact good hitters more than bad ones. I want to run a better study of Shea effects, then add in other ballparks, to see if this hypothesis holds up. I'm trying to set up a larger, slightly more valid study, following Tango's suggestions. This will take me a little while, but I'll let you know how I do.
League Equivalency (July 2, 2003)
Discussion ThreadPosted 12:24 a.m.,
July 3, 2003
(#1) -
Dave Studenmund
(homepage)
Tango, I understand that regression to the mean is a problem with studies like this. MGL mentioned this regarding the park effects study (that I'm still working on). My question is, what's the math here? How should someone like me (a statistics 101 type) try to account for regression to the mean in my analyses?