Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength
- Cite this paper as:
- Coulom R. (2008) Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength. In: van den Herik H.J., Xu X., Ma Z., Winands M.H.M. (eds) Computers and Games. CG 2008. Lecture Notes in Computer Science, vol 5131. Springer, Berlin, Heidelberg
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.
Unable to display preview. Download preview PDF.