Exercising Error: Quantifying Statistical Tests Under RAPM (Part IV)

In the Regularized Adjusted Plus-Minus (RAPM) model, one of the perceived challenges is understanding the error associated with the resulting posterior RAPM value a player receives. In a previous post, we noted that RAPM is a Bayesian model in which we assume that “player contribution” can be estimated through weighted offensive ratings conditioned on the…

Warping Play Registration

Synergy: Breaking Down Field Goal Types With the creation of Synergy, the basketball world gained valuable access to previously hard-to-obtain data on all field goal events in the league. One of the biggest introductions was the “primary defender” tag on field goal events. With play-by-play data, when a player drives to the basket or attempts…

Transitioning Turnovers: Case Study of Golden State and Toronto

In Dean Oliver’s Four Factors, we are interested in effective field goal percentage, offensive rebounding percentage, free-throw rate, and turnover percentage. If a team cannot dominate a couple of these categories, then it will be unlikely for that team to win. For instance, let’s consider effective field goal percentage. The Golden State Warriors have posted a .558 eFG% while limiting their…