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I use one model for all dirt (and synthetic) racing. There are different track specific parameter around things like post position and prevailing track bias.
It seems to me that there should be underlying logic to how it all works that is grounded in the nature of the thoroughbred animals running on a dirt surface.
Using all of the history gives plenty of data to fit the model properly (although I did this 20 years ago when I had far less data than I have today).
I think when you start slicing the data into small (track specific) pieces it elevates the noise above the basic truth behind the model.
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