Stochastic Tracking II: Next Gen Solutions and Player Performance

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…

Stochastic Tracking

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…