Prediction of Olympic Medal Based on Multiple Linear Regression and Logistic Regression

Abstract

This paper focuses on the issue of Olympic medal distribution and conducts in-depth exploration by comprehensively applying multiple models and algorithms. A medal-counting prediction model is constructed using multiple linear regression. By considering factors such as historical medal counts and the host-country effect, the medal standings of the 2028 Los Angeles Olympics are predicted. Through the construction of indicators such as the country-project alignment degree, the impact of competition events on medal distribution is analyzed. A logistic regression model is used to predict countries that will win medals for the first time and to identify potential medal - winning countries. The research reveals the laws of medal distribution and clarifies the influence mechanisms of various factors. These models provide a scientific basis for countries to develop sports development strategies, help optimize resource allocation, enhance the competitiveness of Olympic medals, and have important reference value for sports event planning and national sports development.