Advanced Stats for Basketball

Below are all the posts from the "PER" category. Click here to view all posts.

May 28, 2008

Comparing Player Ratings

Posted by Eli in Advanced Stats, PER, Plus/Minus

I’m still working on that follow-up post on regression to the mean, but in the meantime I wanted to put up a post comparing various player rating systems. For the most part this will be a subjective rather than objective evaluation of the metrics, along the lines of Dean Oliver’s “laugh test” (as in, “a rating system that thinks Dennis Rodman was better than Michael Jordan doesn’t pass the laugh test”). I think looking at how players are rated differently in various systems can tell us a lot about both those players and those rating systems.

The Player Ratings

I took a look at seven popular player ratings. Two basic linear weights metrics based on boxscore stats - John Hollinger’s Player Efficiency Rating (PER), and Dave Berri’s Wins Produced (WP). Two metrics built on Dean Oliver’s individual offensive and defensive ratings - Justin Kubatko’s Win Shares (WS), and Davis21wylie’s Wins Above Replacement Player (WARP). And three plus/minus metrics based on team point differential while the player is on the court - Roland Beech’s Net Plus/Minus (Net +/-), Dan Rosenbaum’s Adjusted Plus/Minus (Adj +/-), and Dan Rosenbaum’s Statistical Plus/Minus (Stat +/-). For the purposes of comparison I looked at the per-minute (or per-possession) versions of all these metrics (e.g. WP48 instead of WP, WSAA/48 instead of WSAA, WARPr instead of WARP).

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December 4, 2007

Evaluating Player Ratings: Year-to-Year Correlations

Posted by Eli in Advanced Stats, PER, Stat Theory

There has been a lot of debate recently about comprehensive player ratings such as John Hollinger’s PER, Dave Berri’s Wins Produced, and Dan Rosenbaum’s Adjusted Plus/Minus. Is one of these rating systems better than the others? What methods can be used to make such an assessment? One approach is to analyze and critique the theory behind each measure - does the way it was constructed make basketball (and statistical) sense? An alternative approach is to analyze them empirically - what happens when we actually start applying the ratings to players? Dean Oliver, the author of Basketball on Paper, has suggested two such empirical methods by which to evaluate player ratings:

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