Predicting African Participation in Olympics: Gender and Sport Type Trends

Document Type

Conference Proceeding

Publication Date

2025

Abstract

This paper presents a comprehensive analysis of historical Olympic Games data, with a particular focus on trends in athlete participation, gender distribution, medal counts, and sports popularity. Using a dataset from Kaggle that spans over 252,566 athlete records, the study delves into the evolving landscape of the Olympics, highlighting a notable increase in female participation over recent decades a trend aligned with the International Olympic Committee's efforts toward gender equality. Country performance analysis underscores the dominance of nations like the United States, China, and Russia, while also shedding light on emerging contributions from African countries, including South Africa, Kenya, Egypt, and Nigeria. Additionally, this study uses machine learning models to predict participation trends and medal outcomes in future Olympic Games, with a specific focus on forecasting the performance of African nations. The findings offer valuable insights into both historical patterns and potential future developments in global sports, contributing to a deeper understanding of the Olympics’ changing dynamics and aiding policymakers in promoting equitable participation and success.

Comments

Part of the book series: Lecture Notes in Networks and Systems

Included in the following conference series: Intelligent Systems Conference

DOI

10.1007/978-3-031-99958-1_15

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