A PageRank Model for Player Performance Assessment in Basketball, Soccer and Hockey

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Common player metrics in the sports of basketball, soccer and hockey normally fit into one of two categories: offensive and defensive statistics. Comparing players becomes ambiguous across numerous metrics, even in the same category. Hence it would be ideal to be able to compare players with a meaningful statistic that encompasses some measure of both categories, while rewarding playmaking as well. We construct a directed graph from the flow of a game and then calculate a new statistic, based on the well-known PageRank algorithm, for each player in the game. Players can be compared via their “relative ranks”, which is a measure of their importance to the flow of the game, taking into account the offensive and defensive plays the player has made during the game. In this paper we explore this model, through its basic mathematical properties as well as through experimental examples, and propose it as a valid metric that could easily be implemented in mainstream sports analytics culture for any passing sport.

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