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Other than the "statistical formula" that they did win 85 games, anybody got any idea what they're talking about?
Edit: And looking over at BPro, third order winning percentage has them as an 83 win team. Not too far off of 85.
Of course, I think the entire premise of projecting a team based on prior season record (or pythag, or third order wins, or whatever) is pretty stupid anyway.
As for the projection thing, I just don't see the point of using the performance of a different roster in a one season sample as a starting point for our expectations when its just not that hard to develop a true talent estimate of the current roster using multiple years of data. Teams change, players performances change... there's just no real reason to use pythag or WAR or third order wins or anything else from last year to project this year. Use CHONE or ZIPS. The extra two minutes it takes to look up a true talent estimate is worth it.
This page shows all of the second and third order wins and losses from 2009. What Dave Cameron says is confirmed by the "third order" AEQR/AEQRA numbers.
This is how the AL West would have finished last year using expected runs (3rd):
Team - AEQR - AEQRA
Angels 86.8 - 75.2
Rangers 85.3 - 76.7
Mariners 83.0 - 79.0
Athletics 81.8 - 80.2
In other words, the AL West was fairly tight. If Sheets does not fall apart and Duchsherer's arm does not fall off, the A's may be a bit better; Seattle should be better once Lee comes back from his suspension and King Felix is King Felix and Chone is Chone; the Rangers could be better with a manager who is not doing lines off the trainer's table; and the Angels should suck.
Tooooo late.
Well, it is true in the abstract. The problem is that in general, the teams that overperform their pythag as a group should* be relatively average in the other "luck" categories, which go into run scoring/preventing, that have allready been mentioned. So when look at a specific example, where two factors were opposing each other, you should expect each of those to regress, and those effects will at least partially cancel each other out.
*I'm guessing, I have no evidence for this
That doesn't mean that the differences are all luck or that they don't mean anything, just that in the aggregate that's the result you get. So I wouldn't doubt the existence of exceptions for whatever reason, just that they are indeed exceptions and the general rule is it doesn't mean much. Generally after about three years even the pythags start not to matter anymore.
Something a little interesting is that if you go a few years back, a negative relationship between actual record three or four years ago shows up that sometimes is very close to a statistical significance standard (IE, the better your actual record then, the worse the predicted record in the future). This may be due to behavior from front offices or more likely draft position or it just might not mean anything since it's not a very strong indicator.
And David, it's actually stronger than regression. Two forms of regression were among the factors James identified. As a group good teams tended to decline. Further, teams which improved a lot in one season tended to decline the next.
Seattle was in the slight plus.
I don't see any reason why we would look at individual players' OBP and SLG numbers to establish their talent level, and then throw that away when we look at team's talent level and instead focus on the number of runs scored and allowed.
And of course, no need to stop at OBP and SLG, since those things are a manifestation of their actual talent levels. (So, if you can translate a player's talent level visually, then you don't need numbers at all. Not that we're there yet.)
Anyway, the more luck you add in, the less you know. That's why you need to focus alot more on individual OBP and SLG than on team runs scored.
The other 3 factors were quality of AAA team, record from August 1 and team age.
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