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.
Assumption-lean inference for generalised linear model parameters.Journal of the Royal Statistical Society Series B: Statistical Methodology
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Residual-on-residual regression estimates effects encoded in partially linear models by OLS regression of outcome residuals on exposure residuals after confounder adjustment, showing comparable or better performance than AIPW/TMLE in simulations and a pregnancy cohort study.
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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.