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Friday, October 30, 2009
How to calculate Linear Weights, part 2
Phil is back.
I’m going to disagree slightly with him that what he’s doing (which is the traditional way of doing it) is the same as his urn example. That’s because the run expectancy charts themselves are also samples. He’s relying on the fact that you have enough events that the 24 base/out matrix will look “normal”. However, even in one league-season, you will get impossible results, like being on 2b with 2 outs will lead to more runs than being on 3b with 2 outs. It has happened.
This is why you need a Markov approach, but which uses the empirical state-to-state transition rates (but you still need a sufficient sample size to get reasonable transition rates).
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