Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength

  • Rémi Coulom
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5131)

Abstract

Whole-History Rating (WHR) is a new method to estimate the time-varying strengths of players involved in paired comparisons. Like many variations of the Elo rating system, the whole-history approach is based on the dynamic Bradley-Terry model. But, instead of using incremental approximations, WHR directly computes the exact maximum a posteriori over the whole rating history of all players. This additional accuracy comes at a higher computational cost than traditional methods, but computation is still fast enough to be easily applied in real time to large-scale game servers (a new game is added in less than 0.001 second). Experiments demonstrate that, in comparison to Elo, Glicko, TrueSkill, and decayed-history algorithms, WHR produces better predictions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Rémi Coulom
    • 1
  1. 1.Université Charles de Gaulle, INRIA SEQUEL, CNRS GRAPPALilleFrance

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