Predicting the success of nations at the Summer Olympics using neural networks

In this paper, we construct several models that try to predict a country's success at the Summer Olympic Games. Our data set consists of total scores for over 271 sporting events for 195 countries that were represented at the 1996 Summer Games and information we gathered on 17 independent variables. We build linear regression models and neural network models and compare the predictions of both types of models. Overall, the best neural network model outperformed the best regression model. Scope and purpose Every four years, an enormous amount of attention is focused on the Summer Olympic Games. Sports fans and analysts do their best to predict the outcomes with respect to many sporting events and the overall performance of nations competing at the Olympics. In this paper, we develop and compare socio-economic-based models for predicting the success of nations at the Summer Olympics. (C) 1999 Elsevier Science Ltd. All rights reserved.