Automated Classification of Passing in Football.

A knowledgeable observer of a game of football ( soccer) can make a subjective evaluation of the quality of passes made between players during the game. In this paper we consider the problem of producing an automated system to make the same evaluation of passes. We present a model that constructs numerical predictor variables from spatiotemporal match data using feature functions based on methods from computational geometry, and then learns a classification function from labelled examples of the predictor variables. In addition, we show that the predictor variables computed using methods from computational geometry are among the most important to the learned classifiers.