The Arbitrarian

NBA player similarities matrix revisited

February 25, 2008 · 3 Comments

In response to some questions at the APBRmetrics forum, I’ve put together a new NBA similarities network (Top 250 players version), wherein I use per-minute statistics, instead of my “patented” ratios method, just to see how it looks. In a lot of ways, this looks just as good or even better than the ratios version… I’m still somewhat torn, though: The ratios method, by ignoring time statistics completely, attempts to match players who, given a possession (or given an opponent with a possession), will do similar things with it, while the per-minute method does a better job of representing “substitutability.” I suppose I will let history be the judge, but I don’t think anyone loses when more pretty graphs are made:

nbaaltthumb.png NBA player similarities [pdf]

Another version with Extremely High Contrast Labels for Easy Reading: [pdf]

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3 responses so far ↓

  • NBA similarity networks « The Arbitrarian // February 25, 2008 at 11:05 am | Reply

    [...] Update:  More graphs, compiled with a somewhat different methodology, can be found here. [...]

  • edk // February 25, 2008 at 4:40 pm | Reply

    The question of per-minute or per-possession (or your ratio method) is not an easy one. As someone who has worked on this kind of stuff for a long time, I end up using per possession for “skill” stats (pts, ast, that kind of thing), and per-minute for the other stuff (reb, stl, to). I haven’t figured out a way to combine the best aspects of both.

    The bigs section of the graph is the most interesting to me — you have the scorers on the bottom and role players on the left and “tweeners” in the middle, with each group of bigs showing significant homogeneity.

  • Toward a basketball taxonomy « The Arbitrarian // February 26, 2008 at 4:02 pm | Reply

    [...] and genera of player types represented. I used the same methodology I’ve been using (with the per-minute, rather than ratio statistics), but generated the graph with fewer connections (just the single [...]

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