But your solution is cool, too.
But your solution is cool, too.
My first iteration of the baseball model took this to an extreme. I broke down every single step from the pitcher deciding which pitch to throw to the pitcher deciding where to throw it to the pitcher throwing it at a certain speed in a certain spot, and on and on. It was something like 17 sequential PyTorch models. My directive to myself was to not care how much compute it would take to run, just get it to the most right version it could possibly go.
Turns out just predicting the end result of each pitch is far more accurate than sequential modeling. I still to this day have a hard time believing it. But the results are pretty stark when I compare the two methods.
Anyway, I really appreciate the kind words and for taking the time to check it out.