Crow, I'll get to your request in the next couple of days. Probably after I did some minor changes that people here suggested
Mike G wrote:
And then why not separate all discrete events?
Yeah. I'll do that from now on
I would recommend using the 8-year equally-weighted RAPM that you compiled for me to compile the box-score weights...
I know that this and your ASPM should probably give the same results, but I'll try this approach. Maybe it adds some insight, maybe it doesn't. We'll have to certainly test it
Are you including regression to the mean, here, like in RAPM?
Finally, another observation is that the distribution of +/- results from the box score regressions appears to be flatter than that generated by the RAPM priors.
I assumed everyone would go back to 75% to what they did the season before. (I think it's a reasonable figure, based on the fact that it used to give the best prediction results with 'RAPM informed RAPM'. Those 75% can obviously be messed with to achieve slightly better results). I actually multiplied the BoxScore-derived ratings with that 0.75 factor *before* putting them online, which is something I haven't done with RAPM figures. Also, 'RAPM informed RAPM' uses multiple years of information, if you will. Single year 'uninformed RAPM' looks a lot flatter, also. All being equal, the BoxScore derived ratings are probably less flat
Did I misread your post?
No, I misread yours. Sorry
First of all, are you of the belief that this box score approach will outperform the year n-1 RAPM prior, and if so, why?
I'm not sure but it might. If it's not better as a prior, maybe a mix of n-1 RAPM and BoxScore prior is the best. One area where it probably has an edge on the n-1 RAPM prior is low minute players, which are very likely worse than 0, which is what n-1 RAPM used to give them. Rookies are another aspect where the n-1 RAPM prior is probably weak
And then there is the special, relative weakness of box score methods in measuring defensive performance
It's weak, but if there was no information in the BoxScore regarding defense, everything should just show up as 0. As it appears, even offensive statistics can give indications for future defensive performance
I'll put 2FG%, 3FG% and FT% in. I'll just need to find a good threshold for minimum attempts
The next steps, for me, should be these:
-Grab the now available PBP from bbr, so that I have more (reliable) matchupdata to fit the model on.
-Run this algorithm on the standard BoxScore. This should be translatable to college and euroleague if one wishes
-grab all other available player specific data for single seasons, like salary and actions we can read from the PBP, like goaltends, shots from different distances (or clock situations), different types of turnovers etc.. Then run the algorithm with the more detailed player specific data.
-Find out whether 'BoxScore(+PBP info) informed RAPM' beats 'RAPM informed RAPM' in retrodiction