A cool way to summarize a basketball player’s contribution to his team is the plus-minus statistic or “Roland rating,” which is “the difference in how the team plays with the player on court versus performance with the player off court.”

I had heard of this somewhere and found the details searching on the web, via this page of links on basketball statistics, which led me to Kevin Pelton’s statistical analysis primer, which led me to this page by Dan Rosenbaum. I had been wondering if the plus-minus statistic could be improved by adjusting for the qualities of the other players and teams on the court, and Rosenbaum has done just that.

I have a further thought, which is to apply a multilevel model to be able to handle thinner slices of the data. The issue is that, unless sample sizes are huge, the adjustments for the abilities of other players and other teams will be noisy. Multilevel modeling should help smooth out this variation and allow for adjusting for more factors, or for adjusting for the same factors for shorter time intervals. Sort of like the work of Val Johnson on adjusting grade point averages for the different abilities of students taking different courses.