Predicting Olympic Medal Tally: An XGBoost Model for Forecasting and Investment in Sports Development
收藏DataCite Commons2025-05-01 更新2025-05-07 收录
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https://figshare.com/articles/dataset/Predicting_Olympic_Medal_Tally_An_XGBoost_Model_for_Forecasting_and_Investment_in_Sports_Development/28466906/1
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We developed an XGBoost prediction model based on historical medal data, host country factors, participant numbers, and other non-economic variables. The model successfully forecasted Olympic medal totals from 1960 to 2024, achieving an outstanding performance with an NRMSE of ~0.05 and R² of ~0.9, outperforming Random Forest (RF) and Support Vector Machine (SVM) models. Using this model, we predicted the 2028 Olympic medal table and optimized it for countries that have never won medals, achieving an NRMSE of 0.0589 by incorporating the medal share of key nations. Our model also suggests a high probability (0.2655, odds: 2.77) that three countries will secure their first Olympic medal in 2028. Furthermore, we analyzed the "Great Coach Effect," identifying it as the most influential factor in medal success. Based on this, we highlighted three promising coaching investment opportunities. This model can also be utilized for calculating Olympic medal odds and guiding future investments in sports development.
提供机构:
figshare
创建时间:
2025-02-24



