Evaluation, Prediction, and Recommendations of Olympic SDEs——Based on TOPSIS and Grey Prediction Models

Abstract

 The IOC is planning the 2032 Summer Olympics in Brisbane. Throughout Olympic history, SDEs have been introduced, removed, or reintroduced to reflect the times. We created a mathematical model that evaluates SDEs to provide well-reasoned recommendations and make quantitatively informed decisions about which SDEs best fit the Olympics' evolving vision. In our model, we identified various factors crucial for SDE decisions. We build an indicator system based on the International Olympic Committee's (IOC) criteria. We subdivide them into 21 indicators. We systematically assess SDEs against IOC criteria, leveraging the factors identified earlier. We collected data on 72 SDEs from diverse sources like official committees and social media and established the TOPSIS Evaluation Model. We used the Entropy Weight Method and the CRITIC Method to weigh and calculate the combined weight. SDEs with higher scores are Athletics, Basketball, and Swimming. Then, our model is rigorously tested using a diverse selection of SDEs. For SDEs added or removed recently, like Karate, Squash, and Baseball, we analyze their historical and current status in the Olympics. Moreover, an analysis was conducted on six aspects, such as popularity and accessibility, and a bar chart of their TOPSIS scores was drawn. For long-standing SDEs such as Swimming, Weightlifting, and Artistic Gymnastics, we have drawn a line chart to analyze their hosting frequencies and trends from 1896 to the present. Also, we explore their continued relevance and value. Besides, we introduce a time factor and use the Grey Model to predict changes in SDEs as the Olympics progresses over the next 12 years after a scale test. Esports, Ultimate, and Breaking are singled out by analyzing various factors. We identify these three sports with high potential for the 2032 Brisbane Olympics and 2036 Olympics and subsequent Games, thus potentially shaping the future of the Olympic program. Furthermore, we carried out the sensitivity analysis of the model and found that the coefficients in our model are not highly sensitive, which proves that the model is robust.