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Online competitive games have become a mainstream entertainment platform. Tocreate a fair and exciting experience, these games use rating systems to matchplayers with similar skills. While there has been an increasing amount ofresearch on improving the performance of these systems, less attention has beenpaid to how their performance is evaluated. In this paper, we explore theutility of several metrics for evaluating three popular rating systems on areal-world dataset of over 25,000 team battle royale matches. Our resultssuggest considerable differences in their evaluation patterns. Some metricswere highly impacted by the inclusion of new players. Many could not capturethe real differences between certain groups of players. Among all metricsstudied, normalized discounted cumulative gain (NDCG) demonstrated morereliable performance and more flexibility. It alleviated most of the challengesfaced by the other metrics while adding the freedom to adjust the focus of theevaluations on different groups of players.

The Evaluation of Rating Systems in Team-based Battle Royale Games