Olympic Medal Prediction Based on Multi-Factor Analysis Model

Abstract

The Olympic Games, as a world-renowned sporting event have garnered considerable attention due to their immense influence. Predicting Olympic medals holds significant guidance for related industries and national development strategies. This paper first conducts correlation analysis using references and practical situations to identify factors influencing medal wins. It employs the entropy weight method to determine the weight of each factor and applies the TOPSIS method to weigh medal data from different years. Subsequently , multi-factor analysis and multiple regression equations are established to predict countries' medal-winning potential and probability scores. After ranking, initial models for medal rankings and estimated medal counts are established. Considering population, the number of participants from each country in various events, historical medal losses, and the probability of medal seizure, the binomial distribution is then used to estimate the probability of medal seizure and predict its variation range for each country, leading to the final medal rankings forecast. Combined with Pareto analysis, suggestions for potential advantageous events are provided. Mathematical models are used to predict countries' Olympic award situations as accurately as possible, offering effective guidance for their future competitions and related industries and promoting the rational allocation of resources and the correct implementation of strategies.