Inferring Player Rating from Performance Data in Massively Multiplayer Online Role-Playing Games (MMORPGs)

This paper examines online player performance in EverQuest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. The study uses the game´s player performance data to devise performance metrics for online players. We report three major findings. First, we show that the game´s point-scaling system overestimates performances of lower level players and underestimates performances of higher level players. We present a novel point-scaling system based on the game´s player performance data that addresses the underestimation and overestimation problems. Second, we present a highly accurate predictive model for player performance as a function of past behavior. Third, we show that playing in groups impacts individual performance and that player-level characteristics alone are insufficient in explaining an individual´s performance, which calls for a different set of performance metrics methods.