Curious: could you use these numbers along with Hollinger’s pure point rating to make an adjust pure point rating?
The reason I like PPR is that it effectively accomplishes what people miss when people talk about a point guard’s turnovers: how well he balances the harm of creating turnovers for the team with the benefit of creating a scoring opportunity for others.
Hollinger’s PPR formula just uses assist and turnover rates (not adjusted for anything except pace). Here was my reply:
Adjusted Four Factors
that’s really what matters for every position
a good point guard will have high ratings in each offensive category, except arguably offensive rebounding:
If I were going to make a pure point rating, I’d probably start with that, giving appropriate weighting to each and creating an index.
That was a few days ago, but apparently I work fast. I’ve just posted my methodology for A4PM which weights each of the FF on offense and defense using regression on 2.5-year RAPM. So now I can do precisely what I commented above. Specifically, I can make the following index:
The idea here is that a point guard helps his team (as a “pure” point guard) primarily by improving the scoring efficiency of his team (I would argue either by passing or his own efficient scoring) and by protecting possessions through his ball-handling skills. Of the 8 factors, O1, O2, and O4, seem to me to be most reflective of these attributes. This is not to say that rebounding and defense are not important for point guards, because they clearly have an effect on the overall A4PM and RAPM ratings. For example, Jason Kidd, to my surprise, does not have a great PGI, but his overall rating is held up by his defensive contributions (according to the regression analysis, anyway).
Here are the results for point guards with greater than 5000 possessions played in the last “2.5” seasons (2010 through last week).
Adjusted 3-Factor Point Guard Index (A3PGI)
All I can say is, Denver has two pretty good point guards. Also, a bit surprised to see Derek Fisher as high up as he is, and Jason Kidd as low as he is. And no surprise whatsoever to see Chris Paul, Steve Nash, and Deron Williams at the top of a list like this.
This should give you a good idea of where we can go from here. You may want to use the adjusted FF data to create your own indices. Also, future iterations may break down the FF into additional factors that give even more insight into how players help or hurt their teams. Fun times to be had here at The City. Hope you enjoy.