Prediction on Olympic Medal Based on Random Forest and Logistic Regression

Abstract

The Olympic Games, as a highly renowned global sports event, attract significant attention, and the Olympic medal table is a focal point of public interest. The medal table not only showcases athletes' exceptional competitive abilities but also reflects a nation's overall strength. In this paper, a Random Forest model was developed to predict the medal rankings for the 2028 Olympic Games. The model innovatively considers not only economic factors but also athlete performance, the number of events participated in, and host nation advantages. By integrating these comprehensive factors, it forecasts that the United States, China, and the United Kingdom will secure the top three positions. Additionally, the study focuses on countries that have never won Olympic medals—groups that receive little attention—using Logistic Regression to predict that nations like Tuvalu have a 3.530% probability of gaining their first Olympic medals in 2028. This study not only provides forecasts for the Olympic medal table but also offers a scientific basis for countries to develop sports strategies and optimize resource allocation, which is significant for enhancing international sports.