One of the challenges in data science within the NBA is diagnosis. Diagnosis is the process of collecting and dissecting data in an effort to reveal and understand the components of such data such that we can extrapolate intelligence. Within many NBA analytics circles, this is done heuristically: discussion of a question, hypothesizing new variables,…
To take a break from the heavy mathematics of recent articles, today we take a look at the early offense set called Pistol. Like many offensive wrinkles such as elevator doors, floppy, horns (etc.), a key goal of the offense is to force the opposing defense to be out of position. More importantly, not only…
Over the past decade a true emphasis on three point shooting has emerged. This can be credited to the understanding of effective field goal percentage being a better underlying parameter for points per field goal attempt than raw field goal percentage. And it’s become an emphasis for some top-tier teams such as the Houston Rockets.…
A tried-but-true strategy in pick-up (and grade school) basketball is the “dump-and-chase” offense. This offense takes as many jumpers as possible, regardless of capability, fully knowing that the team can either out-hustle their opponent for rebounds; or they have a behemoth of a rebounder on their team. As players become older, or more technically sound…
In our previous post on Stochastic Tracking, we took a look at motivating a Hierarchical Bayesian process in filtering tracking data and producing more robust estimators for the velocity. During the discussion, we limited the data sampled to be of two-dimensions only and had to assume that acceleration was constant between sampled points. Due to…
A problem that was posed in Dean Oliver’s Basketball on Paper (2003) revolved around the way one can credit assists. In his book, Oliver laments the lack of data available for crediting assists and he begrudgingly uses the one-half rule: credit both the scorer and the assist man with one-half of the assist. However, in…
Recently, we posted about a way to redefine gravity in terms of a joint model that can be used to quantify defensive interaction, offensive spacing, and spatio-temporal motion of a possession. The result yields a sparse N x 2P x Q x R x S x Z tensor that characterizes the interactions of players, locations on the court,…
