In his 2+ seasons as head coach of the Golden State Warriors, head coach Mark Jackson has clearly made improving the defense one of his highest priorities. So much so, in fact, that in a live blog/hangout yesterday morning from the Warriors training facility, Stephen Curry pointed out how all the photos of the team hanging on the wall depict the team defending the ball, as opposed to “posterizing” players on offense (so evidently “Barnes over Pekovic” is nowhere to be seen).
Curry goes on to show viewers a chart that Mark Jackson had created for the players to show them where they should try to force defenses to take shots, based on efficiencies. This is a great idea, and it’s one of the things you have almost come to expect as analytics has swept into front office and coaching mentalities across the league, with the Warriors, perhaps, being one of its top proponents.
There is a curious thing, however, in this chart. And it makes me wonder how much further analytics needs to go before its lessons are fully learned (or even appreciated).
Did you spot the problem? (If not, I suggest you read my Advanced Stats Primer!) Notice how the chart shows FG% in each region? From what we can see, there is no label as such, but to all of us who have studied the numbers even a little, it’s clear that the %’s given are field goal percentages. It’s sort of odd, right? I mean, if I was a player, the message I’d receive looking at this chart is that I’d rather force opponents to take “above the break” 3-pt shots (34.2%) as opposed to 16-23 ft jump shots (38.1%). But we know that a better metric to use here is “equivalent” or “effective” FG% (eFG%), which multiplies 3-pt shots by 1.5X, so that 34.2% becomes effectively 51% or so, much better than the long 2-pt jumpers.
And if you’re thinking the numbers aren’t important, that the players will only look at the colors (which to my eye are confusing, if anything), then why bother putting numbers at all? I see this as a window into the current state of affairs in the NBA. Analytics has definitely become the prominent way of thinking among the “NBA intelligentsia”, and players are most likely aware of the “take-home messages”, but there’s still quite a ways to go until analytics becomes part of the everyday language of basketball (especially for players) in the same way that “pick and roll” or “coming off a screen” have implicit meaning.