Predicting Olympic Medal Distributions and Emerging Nation Breakthroughs: A Hybrid Negative Binomial and Logistic Regression Framework

Olympic medal distribution is affected by multiple factors, and accurate prediction of medal distribution in future Olympic Games is of great significance to optimize the sports resource architecture of each country. By constructing an Olympic medal count prediction model based on negative binomial regression and logistic regression, this paper predicts that the United States and China will dominate with 46 gold medals and 142 total medals, and 44 gold medals and 98 total medals, respectively; countries such as France and Germany present a balanced multi-sport profile. Of the five small countries selected for discussion, Mali, Bolivia, and Myanmar show high probabilities. At the same time, Yemen and Angola are significantly lower, with the rise of sports underdogs highlighting the diversity of the sports competition landscape. The study reveals the dynamic changes in global sports' competitive strength and the driving factors behind it, providing a scientific basis for the National Olympic Committees to optimize the allocation of sports resources.