Performance rating in chess, tennis, and other contexts

Abstract

In this note, I introduce Estimated Performance Rating (PRe^e), a novel system for evaluating player performance in sports and games. PRe^e addresses a key limitation of the Tournament Performance Rating (TPR) system, which is undefined for zero or perfect scores in a series of games. PRe^e is defined as the rating that solves an optimization problem related to scoring probability, making it applicable for any performance level. The main theorem establishes that the PRe^e of a player is equivalent to the TPR whenever the latter is defined. I then apply this system to historically significant win-streaks in association football, tennis, and chess. Beyond sports, PRe^e has broad applicability in domains where Elo ratings are used, from college rankings to the evaluation of large language models

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