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.