ScoreStop introduces a functional score test for early stopping in gradient boosting, testing the null that the current predictor minimizes population risk with a scale-invariant statistic of known asymptotic distribution.
Large Sample Tests of Statistical Hypotheses Concerning Several Parameters with Applications to Problems of Estimation
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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.
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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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.