Prediction on Olympic Medal Based on Random Forest and Logistic Regression

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.

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Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2025-09-28
DOI
https://doi.org/10.54097/4ctyr936
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
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article

Prediction on Olympic Medal Based on Random Forest and Logistic Regression

Yanqing Zhou, Yuekun Li, Zhanglin Lin Cui
Highlights in Science Engineering and Technology
Sports Analytics and Performance
article

Prediction on Olympic Medal Based on Random Forest and Logistic Regression

Yanqing Zhou, Yuekun Li, Zhanglin Lin Cui
article en

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.

Highlights in Science Engineering and TechnologyVol. 155
Openalex Percentile: Top 62%
Sports Analytics and Performance
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