Tracking the Bounce
The understanding of rebounds has slowly advanced from basic counting to the percentage of available rebounds. Now, there’s SportVU data. Unlike the first two iterations of how we understood rebounding, this isn’t just a sortable list of leaders. It provides a lot more context to understand rebounding, but also requires context to understand.
Jodie Meeks has collected 100% of rebounds that fall within a 3.5 foot radius of him. Best rebounder in the league, right? Well, 93% of his rebounds have been uncontested. And who cares if a player can get the rebound, what if the hardest part of rebounding is getting to that 3.5 foot radius around the rebound? Maybe part of the Lakers scheme is to have the point guard crash down and box out Meeks’ man while Meeks goes for the rebound?
That’s the most intriguing thing about this data — what it can tell us about team and player strategies. Take rebound opportunities, for example. It can be a proxy for time spent in the paint in the same way usage rate has been a proxy for touches. It can also tell us which big men leak out early or are normally on the perimeter at the end of possessions. Contested vs. uncontested rebound splits between pairs of big men can tell us a lot about how these players work together, without having to go on a massive play-charting project a la Dylan Murphy. Right now, offensive and defensive rebounds are lumped together, which makes things less accurate, but the data is still valuable.
One thing that always needs to be noted when discussing rebounds is their diminishing returns. It’s been proven multiple times. In short: players steal rebounds from each other. Put together a bunch of really good rebounders and the lineup won’t perform as well as one would expect from just adding up the individual’s defensive rebound rates. This phenomena can be looked at even more deeply using contested and uncontested rebound splits. Maybe some players just sit back and grab rebounds “by default”; if they didn’t grab it, it would still be rebounded by another player on their team. Contested rebounds on the other hand aren’t a guaranteed thing. Players who pull down lots of contested rebounds might be the ones who are really doing work, while players with high uncontested totals are just beneficiaries of the team scheme. The last part of that might not be true, though. Maybe getting uncontested rebounds is skill: maybe Trevor Ariza has so many uncontested rebounds because he boxes out so hard they’re uncontested and hones into anything that comes off the basket like a heat-seeking missile. This data creates more questions than answers.
There are a lot of possibilities with this new data, but while it adds clarity at the end of rebounds, it does little to clarify the murky waters of the pre-rebound scrum. How many players do the Spurs send to the offensive boards on average? How often does Dwyane Wade just stand instead of boxing out? What percentage of Kevin Love‘s boxouts are successful? With the endless possibilities now, it’s hard to imagine what can be done with all the data that’s on the horizon.