Clustering and predictive algorithms for Olympic medal distribution analysis

This study leverages clustering and predictive algorithms to forecast 2028 Los Angeles Olympic medal distributions and evaluate coaching impacts. Historical Olympic data is preprocessed through integration, cleaning, and feature extraction for quality assurance. KMeans clustering categorizes countries by sports system maturity, informing tailored predictions. ARIMA and Random Forest models predict medal counts, indicating a potential U.S. gold medal decline in 2028, while China, the UK, and France remain stable, driven by event settings. A comprehensive evaluation algorithm, integrating factors like coaching experience and athlete performance, quantifies the significant role of exceptional coaches in enhancing medal success. These algorithmic insights provide Olympic committees with data-driven tools to optimize sports strategies, resource allocation, and coach development.