ORIGINAL RESEARCH article
Front. Sports Act. Living
Sec. Sports Politics, Policy and Law
Volume 7 - 2025 | doi: 10.3389/fspor.2025.1596196
Quantifying Future Olympic Sport Selection: A Data-Driven Framework for SDE Evaluation and Selection
Provisionally accepted
- 1Sendelta International Academy, Shenzhen, China
- 2School of Media, Yangtze University, Jingzhou, Hubei Province, China
- 3Southern University of Science and Technology, Shenzhen, Guangdong Province, China
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The Olympic Games are the world's foremost sporting event, with over 200 countries participating.As the Games evolve, sports, disciplines, and events (SDEs) are periodically added or removed. The selection process for Olympic sports is inherently subjective, as seen with breakdancing's inclusion in the 2024 Paris Olympics and exclusion from the 2028 Los Angeles Olympics. Thus, developing a quantitative decision-making model is crucial for the International Olympic Committee (IOC). This study evaluates IOC criteria for new sports by considering factors such as social media engagement, TV viewership across demographics, affordability, gender equity, youth appeal, cultural diversity, and global involvement. Our model employs a scoring and labelling system based on the Analytic Hierarchy Process (AHP), which calculates the relative importance of each factor. Using Principal Component Analysis (PCA) for feature extraction, we apply a k-nearest neighbour (KNN) classifier for further evaluation. We apply this model to assess potential SDEs for the 2032 Brisbane Olympics, considering their popularity in Australia and alignment with Olympic criteria. Our findings suggest that Esports, Australian rules football, and pickleball are the top candidates for inclusion, while tug of war, bowling, and chess are also recommended based on their historical relevance and global popularity.
Keywords: The Olympic Games and SDEs, Scoring and Labelling System, Analytic hierarchy process, Principal Component Analysis, k-nearest neighbour classifier
Received: 19 Mar 2025; Accepted: 04 Jul 2025.
Copyright: © 2025 Song, Rui, Zhang and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yizhuo Sun, Sendelta International Academy, Shenzhen, China
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