If you want to have rock-solid data, you should get raw play-by-play data and calculate each metric using the algorithms each person describes. There’s no particular reason to trust that anyone did any of their calculations correctly.

]]>It would definitely be possible, and people have suggested better, to do game-by-game accuracy. I just didn’t have the data at the time. The +/- measures, like APM and RAPM, are based on per-possession data, so you can go that fine-grained if you want.

]]>I am new to your site and I found it very interesting to use the +/- metrics to predict outcomes of basketball games.

Just to check: what do the numbers actually mean in the figures you have in this post? Are there standard error of wins or point differentials for the whole season.

Also, is it possible to benchmark the different metrics by comparing their predicting accuracy on a game-to-game basis? I am currently trying to work on something like that and hope you can give me some advice.

Thanks!

]]>