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Originally Posted by BCOURTNEY
Depends on your model choice to model place probability.
Harville (1973). Stern (1990), Henery (1981), Bacon-Shone et al (1992) Lo and Bacon-Shone (1994)
Normal probability models best fit the data, yet suffer from favorite and longshot bias. i.e. the probability of finishing first or second or third is overestimate for horses which have a high probability and underestimated for horses having a low probability of winning
There has historically been some limited success with obscure gamma ranking models as well
Fast way would be to compute Harville probabilities then adjust the Harville values based on a regression with track data.
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You have links to those ?
Interesting, I agree with your observations.
But it's besides the point.
Suppose we have the crudest of probability estimates.
Like for example convert the morning line place prices shown on the tv screen to place place probabilities. Or if the place prices are not displayed use the win prices and crude reduction method to compute 2nd place probabilities and place probabilities.
Those will be "the probabilities". If somebody-somewhere has any better then good for him.
Again the problem is how to compute the probability of one catch in the set of lines.
Do you have placepots or only winpots in the States ?
