More Projection stuff
I've added in Marcel, Bill James, and Ron Shandler's projection OPS to the mix. I'm only looking at 114 players who had 500 or more AB, and I had to eliminate a few (Dan Uggla and Hanley Ramirez among others) because not all systems projected minor leaguers. Kenji Johjima had to go, as only ZIPs and CHONE even tried to project him (very well I might add). I don't have access to Baseball Prospectus 2006, so I'll look at Pecota in a week or so.
Here's the results:
Shandler .702
James .685
ZIPs .684
Chone .677
Marcel .664
So Chone is a little behind the more established systems, but at least it passes the monkey test. As I've read before, there's not a whole lot of room to improve. Shandler, the king of fantasy baseball, beats a first year amateur by 2.5%.
But there's something real interesting here. These algorithms all seems to have different workings. They like different players better than others. For example, Shandler had Paul Konerko at .921 - and Konerko did better than that, totally destroying the other projections, in the .850 range. But Shandler missed the boat on Grady Sizemore, projecting only .774. Sizemore beat all of our projections, but the other systems at least had him in the .800's
Take an average of the top 4 projection systems, and we can get an r of .714! (Adding Marcel subtracts from the combined r, all the others add). So the strategy should be to collect all the projection systems that pass the monkey test, combine them, and we have a projection that reaches uncharted waters in accuracy!
Give this a try, and dominate your fantasy league.
8 Comments:
Good stuff, Sean, but...
The question is whether or not these differences are statistically significant. Actually, that's not really a question. With just 114 observations, one standard deviation is around .093 points of correlation, which means that these differences are meaningless. With one year's worth of data, you actually can't really prove the superiority of one projection system over another.
Really you need over 1,000 observations for a difference of .05 points of correlation to be significant at the 5% level. That's many years of data and low plate appearance cut-off. Since systems are continually improved, and we probably have to assume that the order of their quality changes due to those improvements ( i.e., that they do not off-set, and some systems improve relative to other systems and not just in relation to themselves), I'm not sure you can run any kind of basic correlation test that will give you significant results.
You're probably right in being virtually impossible to state that one projection system beats another.
This is more like a batting championship. It doesn't prove that Joe Mauer is a better average hitter than Derek Jeter - but he had the best average last year.
As I remind people from time to time, there is no "magic" to a level that reaches some arbitrary level of significance (5%, 1%, etc.), so let's NOT call a difference that is not significant at the 5% level "meaningless." It is not meaningless. It simply reflects a "conclusion" with a certain level of uncertainty, more than some and less than others.
It is a really bad habit in the "real world" (ans sometimes even in science) to dismiss a result that is less than some arbitrary sigma level and "accept" it above that level.
The results of the "r's" suggest that each system is better than the one below it. Period.
As well, these things are often Bayesian problems with a priori probabilities. For example, we can probably assume that there is a high likelihood that Shandler is going to beat Marcel and perhaps even the other ones on the list, since Shandler is a smart guy and puts a lot of time and research into his projections.
MGL
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