Our study aims to analyze the impact of the “great coach” effect on the Olympic medal counts of athletes from different countries, with a focus on the situation where athletes cannot change teams due to nationality restrictions, as well as the influence of coach mobility on performance in specific sports. Our study first collects data on coach-athlete pairings, including the personal characteristics of the coaches and medal data, along with athletes’ performance records in various Olympic Games. In the data processing stage, this research appropriately handle missing values and standardize the historical performance and experience of the coaches to ensure the integrity and fairness of the dataset. By utilizing methods such as correlation matrices and principal component analysis, this paper identifies key features related to medal counts and build a fixed effects regression model to quantify the direct contribution of coaches to athletes’ medal counts. The analysis results indicate that athletes from different countries gain more gold medals in specific events due to the coach effect. A heatmap is used to visualize the distribution of gold medals across different sports for various countries, while model evaluation metrics such as R-squared, AIC, and BIC are employed to assess the balance between model fit and complexity. Finally, sensitivity tests, including 5-fold cross-validation and regularization methods, are conducted to ensure the stability and generalizability of the model across different data subsets. The findings of the study demonstrate that the influence of coaches is significant, and the established model performs well in both predictive ability and explanatory power, providing valuable references for countries’ future investments in sports and coaching strategies.
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