Rating Competitors in Games with Strength-Dependent Tie Probabilities
Pub. online: 4 December 2025
Type: Statistical Data Science
Open Access
Open Access
Received
13 June 2025
13 June 2025
Accepted
25 November 2025
25 November 2025
Published
4 December 2025
4 December 2025
Abstract
Competitor rating systems for head-to-head games are typically used to measure playing strength from game outcomes. Ratings computed from these systems are often used to select top competitors for elite events, for pairing players of similar strength in online gaming, and for players to track their own strength over time. Most implemented rating systems assume only win/loss outcomes, and treat occurrences of ties as the equivalent to half a win and half a loss. However, in games such as chess, the probability of a tie (draw) is demonstrably higher for stronger players than for weaker players, so that rating systems ignoring this aspect of game results may produce strength estimates that are unreliable. We develop a new rating system for head-to-head games based on a model that explicitly acknowledges that a tie may depend on the strengths of the competitors. The approach uses a Bayesian dynamic modeling framework. Within each time period, posterior updates are computed in closed form using a single Newton-Raphson iteration evaluated at the prior mean. The approach is demonstrated on a large dataset of chess games played in International Correspondence Chess Federation tournaments.
Supplementary material
Supplementary Material
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Appendices.pdf : Appendices A and B.
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Code_and_Data.zip : Zip file consisting of code and data to run the analyses in this manuscript.
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