I've made the same types of charts--hexbins encoded by size (for shot frequency) and color (for Effective Field Goal Percentage) using shot coordinate data scraped off of ESPN--and my charts don't come out anywhere near as smooth and "trend-depicting" as his do. I've concluded that he must be smoothing the data so much that the result barely resembles reality.<p>First of all, the frequency of shots near the basket so overwhelms that of shots anywhere else that the hexbins away from the basket end up being so minuscule that they're barely visible. So there must be some kind of frequency capping or logarithmic scaling somewhere in his charts. This is not the most egregious "lie" in his charts but it hides an interesting truth: 70% of shots are taken from 30% of the half-court (I'm making those numbers up but you get the idea.)<p>Secondly, I found that a player's (or even a team's) eFG% varies so much from bin to bin that you rarely get smooth color patterns like the ones that show up in his charts. His charts show orangered hexbins close to the basket that somewhat evenly and predictably get lighter and yellower as distance from the basket increases. But in practice, this is nearly impossible. Each hexbin would have to span hundreds if not thousands of shots--much more than an entire season's worth of data for a single player--for a pattern like that to appear. To me, this is almost deceitful because it tells a "story" that isn't there. eFG% is much more "random" than his charts depict. A player might go 10/20 from one location and 5/30 from the one directly adjacent.
A curious non-sequitor:<p>"The data wasn't exactly private, but neither was it public—Goldsberry scraped it from the web."<p>If Goldsberry scraped the data from the web, wasn't the data inherently public?
"Now, as new technologies start to generate terabytes of data about players and tactics, that next great competitive advantage will go to the number crunchers and analysts who can make sense of all those signals. Take the statistical tsunami of SportVU in the NBA. “It's not an exaggeration to say that 85 percent of the teams don't know what to do with this data,” Goldsberry says. “The idea that this is going to revolutionize the NBA—well, I'm not sure that's true unless teams awaken really quickly to things like machine learning and data visualization.""
I have worked with some NBA teams and they are already using software to track ball, players, referee, training, sleep, Heart Rate etc.. there is really nothing revolutionary in this article