Great post , Repped. I even tho I really hate math, am very interested in bball stats esp interpreting them and puting them in their right context and your post was very enlightening. Thanx. I want to also add, that another drawback is the system of the defence. Depending on the system perimeter defenders dont' have the same responsibillities. For example the two teams I'm more accustomed with, the perimeter defenders of the Bucks have much more responsibillities than the Rocket's ones. Also the forward who has to hedge high in contrast to the Rockets. On the contrary the Rocket's Chave much bigger responsibillities than the Bucks C. That can't be shown in the stats.
My pleasure. I agree, you still need to infer a lot to interpret defensive statistics. For example, it doesn't account for issues with players like Ariza or Tony Allen, who are often thrown against the other team's best guys regardless of position. But it does highlight how good of a defender Chris Paul has been over the past few years - even if you can't figure out how he is denying his man shots on the perimeter (and at the rim), you get the sense that he is closing out and switching out effectively on pick and rolls in order to stay near his man, something which passes the eye test as well. But I think the spatial element is very important in defensive statistics and starts to address some of the "intangibles" that people readily recognize when watching or playing the game.
This isn't in RPM but in a splittering stat as you said. The fg% when defending aplayer and also maybe the total distance covered in defence. (Again one has to put this one in the context of the defensive sheme). Maybe with more SportVu data being made available finally we will be able to determine better who screws up rotations and who doesnt'.
