A generalization of Elo ratings updates player strengths via the score (log-likelihood gradient) for varied game outcomes, with derived properties of zero expected value, summation to zero, and reversion to unobserved true skills.
Large Sample Tests of Statistical Hypotheses Concerning Several Parameters with Applications to Problems of Estimation
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A double machine learning framework that residualizes standard outcome-above-expectation metrics to support valid frequentist inference and player-specific effect estimation in sports analytics.
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Score-Driven Rating System for Sports
A generalization of Elo ratings updates player strengths via the score (log-likelihood gradient) for varied game outcomes, with derived properties of zero expected value, summation to zero, and reversion to unobserved true skills.
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Rethinking player evaluation in sports: Goals above expectation and beyond
A double machine learning framework that residualizes standard outcome-above-expectation metrics to support valid frequentist inference and player-specific effect estimation in sports analytics.