So long DIon. Its an end to the And ONNNNNNEEEEE era in Oklahoma City and boy was it a ride. It was a dysfunctional, often broken and always exasperating ride, but there was a perpetual line of people ready to get on. The trade for Dion is seen as yet another low point in the Sam Presti trade legacy. Not coincidentally the same people complaining most vocally about the Waiters trade are the same that have at one point in time screamed, "How could you trade James Harden?!", but I digress. Removing the lense of past bias lets take a look at this trade with some hindsight and see how it looks with that 20/20 perspective.
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I've always wondered if you could used boxscore statistics to qualify a player's position. It's a meaningless problem to solve in this era of positionless basketball, but it's always interested me. Recently, I acquired access to a robust but easy to use statistical package (Spotfire), and my time spent trying to figure out how to use ggplot in R has dropped significantly. I threw together a small script to scrape some NBA.com data and threw it into Spotfire to see what I could come up with.
I was playing with treemaps to see what I could see, when suddenly I had apparently created a chart that defined positions. Granted, this was not basic boxscore data, it was SportsVu data, but my mind was happy with what I saw. Apparently, average time per touch is a decent position identifier. Check it out. |
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