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This is a Quantitative Study study.

Research on Olympic Medal Prediction and Influencing Factors Based on Multi-Dimensional Feature Fusion and Machine Learning

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This research demonstrates machine learning can improve medal predictions in the Olympics, suggesting resource allocation strategies.

A hybrid machine learning framework predicts Olympic medals through multi-dimensional feature fusion.
Two major methodologies include a multiple linear regression with an RMSE of 0.25 and gradient boosting tree for interpretability.
The study innovates by quantifying the impact of coach attributes dynamically on medal successes.
Findings suggest actionable strategies for countries to optimize their Olympic resource allocation based on model insights.

Chen et al. (2025) studied this question.

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