Research on Olympic Medal Prediction Based on PLSR

Zhikang Yuan

doi:10.54097/xbz61j44

Authors

Zhikang Yuan

DOI:

https://doi.org/10.54097/xbz61j44

Keywords:

PLSR, Prediction Model, Bootstrap Method, Logistic Regression.

Abstract

The medal table at every Olympic Games can always get keen attention from all over the world. However, due to the dynamic nature of competitive sports, which leads to the low reference value of early historical data and the small amount of recent data, it is difficult to predict the number of medals in the next Olympic Games. In order to solve this problem, this article plans to establish a comprehensive evaluation system of national sports strength, using the PLSR algorithm suitable for small sample size, combined with the bootstrap method to predict the number of medals of some countries in the next Olympic Games. At the same time, for countries that have not won Olympic medals in history, the logistic regression algorithm is used to estimate the probability of the number of medals exceeding 0 in the next Olympic Games. By integrating both macro and micro dimensions of sports competitiveness, this article not only addresses data limitations but also pioneers a systematic approach to capture national strengths, providing a missing link between traditional socio-economic analysis and sport-specific dynamics.

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