Predicting the medals of the countries participating in the Tokyo 2020 Olympic Games using the test of networks of multilayer perceptron (MLP) - Fazlollahi, P.; Afarineshkhaki , A.; Nikbakhsh, R. (Annals of Applied Sport Science, 2021)
Background. International successes, especially in the Olympic Games, have become significantly important to many countries. Hence, the prediction can be better planning to gain this goal. Objectives. This study was conducted to predict the success of the participating countries in the Tokyo Olympic Games and this it was done using smart methods. Methods. This study was conducted in two stages of qualitative (determination of indicators) and quantitative (collecting data on selected countries). In the first stage of the research, through a study of research background and collecting of library data, a preliminary list of predictive indicators was identified. In the next step, semi-structured and in-depth qualitative interviews as non-random purposive were conducted with four elites aware of the subject of the research. The discussions continued until theoretical saturation. Results. According to the results of the research, the United States, China, and England will be ranked first to third in these games. The Islamic Republic of Iran will also be ranked 21 among the participating teams. Also, the coefficients of the predictive indicators of the rank of the countries participating in the Tokyo 2020 Olympic Games were calculated. Olympic Hosting. GDP per capita and the unemployment rate had the highest share in predicting countries, with 24.15%, 10.04% and 9.74%, respectively. Conclusion. Using the theoretical model (PEST+S) and the neural network model, the countries` sports policymakers were enabled to use the identified indicators and components in their future planning to successfully participate in the Olympics Games.