Early in the spring semester of 2013, Cervone and D’Amour proposed a new project to measure performance value in the NBA. The nature of their idea was relatively simple, but the computation required to pull it off was not. Their core premise was this:
Every “state” of a basketball possession has a value. This value is based on the probability of a made basket occurring, and is equal to the total number of expected points that will result from that possession. While the average NBA possession is worth close to one point, that exact value of expected points fluctuates moment to moment, and these fluctuations depend on what’s happening on the floor.
Furthermore, it was their belief that, using the troves of SportVU data, we could — for the first time — estimate these values for every split second of an entire NBA season. They proposed that if we could build a model that accounts for a few key factors — like the locations of the players, their individual scoring abilities, who possesses the ball, his on-ball tendencies, and his position on the court — we could start to quantify performance value in the NBA in a new way.
In other words, imagine if you paused any NBA game at any random moment. Cervone and D’Amour’s central thesis is that no matter where you pause the game, that you could scientifically estimate the “expected possession value,” or EPV, of that possession at that time.
If we can estimate the EPV of any moment of any given game, we can start to quantify performance in a more sophisticated way. We can derive the “value” of things like entry passes, dribble drives, and double-teams. We can more accurately quantify which pick-and-roll defenses work best against certain teams and players. By extracting and analyzing the game’s elementary acts, we can isolate which little pieces of basketball strategy are more or less effective, and which players are best at executing them.
But the clearest application of EPV is quantifying a player’s overall offensive value, taking into account every single action he has performed with the ball over the course of a game, a road trip, or even a season. We can use EPV to collapse thousands of actions into a single value and estimate a player’s true value by asking how many points he adds compared with a hypothetical replacement player, artificially inserted into the exact same basketball situations. This value might be called “EPV-added” or “points added.” … Read More