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…
In the era of tracking data, a need for a new style of analysis has emerged. Long gone are the regularized regression models and the simple counting techniques. Instead, we require leveraging shot-noise distributed systems such as Dan Cervone’s competing risks model, or Matthias Kempe’s self-organizing maps, or Peter Carr’s Imitation Learning. The list is…
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…
When we learn about computational mathematics, software engineering, or data science in general, one of the most important questions we have to answer is how many operations are required. The answer isn’t to show the prowess of our algorithm, but rather identify how quickly the algorithm can perform. We need to know if the answer…
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,…
Back in 2014, STATS Inc. introduced the notion of gravity, which was explained by Kevin Pelton as a series of two measures: gravity score and distraction score. In Pelton’s explanation, gravity score measures the relative distance a primary defender strays from their offensive counterpart and distraction score quantifies the amount of attention that same defender…
When we measure the defensive impact of a player, typically the first arguments we make are the number of blocks and steals that player has obtained. We celebrate players like Dikembe Mutombo and Maurice Cheeks for their prowess in obtaining blocks (2nd all time) and steals (5th all time), respectively. In the latter case, a…
The usage of an NBA player consists of the number of chances a player takes out of the possible chances a team has when that player is on the court. A chance being the number of possessions that can result in a scoring possession. The higher the usage for a particular player, the more likely…
The terms offensive rating and defensive rating refers to the amount of points scored by a team and by the team’s opponents, respectively, over 100 possessions. The normalization to 100 possessions allows for the ability to compare teams as pace of games can skew points per game comparisons. Both ratings are still considered box score…
As of the morning of November 19th, 2017, the Minnesota Timberwolves have found themselves at 10-5, atop the Northwest Division and third on the Western Conference behind the Golden State Warriors (12-4) and the Houston Rockets (13-4). In a recent match-up, the Timberwolves dispatched the San Antonio Spurs 98 – 86 in Minnesota. With the…