Paris Olympic (2024) Medal Tally Prediction

The Olympics are one of the leading international sporting events, which are broadly classified into summer and winter sports. Being one of the toughest competitions, where an enormous number of athletes from various parts of the world participate in a diversity of competitions. These games are considered to be the oldest events which also makes them one of the world's foremost sports competitions, where we witnessed active participation of 205 nations over the globe in the 2020 Tokyo Olympics. During the study for a suitable model, we discovered that there are several socioeconomic factors/variables that are good predictors and are significantly impacting a nation’s Olympic success. There were initially 10 features in the model, which were further reduced, based on the techniques of feature selection. The prediction of the Medal Tally is a difficult task, as the distribution of classes for all attributes is not separated linearly and is caused by different scales. Regression (Ter Braak and Looman in Regression, 1995 [1]) techniques like Linear, Polynomial, Ridge, Lasso, Bayesian, etc., are capable to do the prediction; however, it is tough to choose which one is the best. Thus, for this purpose we have applied here some of the popular Regression methods on the dataset for prediction. Our source data for medal prediction was taken from Official Olympic website and Wikipedia— https://olympics.com/ , https://en.wikipedia.org/wiki/2020_Summer_Olympics_medal_table , https://en.wikipedia.org/wiki/2016_Summer_Olympics_medal_table .