Predictively consistent priors let complex Bayesian models match or beat the out-of-sample performance of selected simpler models across linear, logistic, and nonlinear examples without explicit selection.
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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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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.