Evaluating and predicting future Olympic Summer Games based on the combination of multiple mathematical models

Abstract

The Olympic Summer Games is a symbol of global sportsmanship and thus the world's finest athletes attend the Olympic Summer Games. However, the selection of sports, disciplines, or events (SDEs) is a complex process that requires modern value resonance and global audience attractiveness. Therefore, a future estimation for new additions or reintroductions of SDEs may lower the burden of the International Olympic Committee (IOC) and thus allowing the IOC to make quantitatively informed decisions. The article presents an evaluation model for sports programs by employing the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) together to assess sports based on six IOC criteria: Popularity and Accessibility, Sustainability, Relevance and Innovation, Safety and Fair Play, Gender Equity, and Inclusivity. AHP is used to compare these criteria and give each criterion a suitable weight while TOPSIS ranks alternatives, which are the sports, by calculating weighted sums and thus attaining the sums’ proximity to an ideal solution. This team then uses the results obtained by TOPSIS as input data to preform predictions through Gray Forecast Model. Combining the predictions attained with randomness predictions by Markov Chain, a comprehensive overall prediction model presented. In the end, this article concludes that most sports included in both 2024 and 2028 are likely to remain in 2032 and 2036. It suggests Boxing, Polo, and Roque as potential reintroductions for 2032 and 2036 based on overall predictions. The study may provide the future developments of the Olympic Summer Games with a ‘grand new design’ and technical support.