Quote:
Originally Posted by Mark17
All of this is just listing many variables involved, and I'm sure many more can be added. The obvious difficulties that remain are:
1. How do these variables play together? Are they additive, multiplicative, subtractive, and to what degree. How do you combine and weigh them?
2. How do you value them, with respect to specific players?
For example, let's say you are comparing 2 pitchers who both have a right fielder with a .985 fielding average. But one has a weak throwing arm and the other is Clemente. How much does having Clemente help, with his reputation discouraging runners taking an extra base?
First you'd need to give a weight to the variable - what impact does the right fielder's reputation play? Second, you have to value Clemente.
Suppose there are two catchers with equal fielding percentages, and throw out equal percentages of baserunners. But one is a very astute signal caller and the other is a dolt. Take Grove having Cochrane for example. First, how much can a smart, observant catcher help a pitcher? Second, what value do you assign to Cochrane (or Roseboro?)
All you have done is thrown out a bunch of factors to consider. The real trick would be to come up with an algorithm that can effectively combine and weigh the variables, and then, there's the (sometimes subjective - like the brains of a catcher) value you assign to each specific player involved.
In short, the above is not anywhere close to an actual predictive model.
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The answers to most of your questions are explained above. The fact that you don't understand how a hierarchical mixed-effect model works (or even my high-level explanation of it) does not mean that it in fact does not work. I was responding to AndrewJerome, who asked,
"The value of a replacement level player could be very different in a time period where quality of play overall is very high as compared to a time period where quality of play was lower. But how in the world can we figure out relative quality of play? If you want the coeffecients (or "weights") from such a model, you'd have to build one. But it's a LOT of work, and I don't see anyone here volunteering to pay me for my efforts. I'm simply explaining, at a very high level, how one could solve for it. I have better things to do with my time than to prove to you guys that Lefty Grove benefitted greatly from pitching in an era where his competition was lacking or that Babe Ruth was effectively swinging at home run derby "pitches" a significant percentage of the time. That much should be obvious to anyone operating on the right side of the bell curve.