Soccer Result Prediction Using Deep Learning and Neural Networks

In the present world, the prediction of the results of football matches is being done by both machines and football experts. Football as a game produces a huge amount of statistical data about the players of the team; the matches played between the teams and the environment in which the match is being played. This statistical data can be exploited using various machine learning techniques to predict various information related to a particular football match, namely the result of a particular game, injury of a player, performance of a player in a particular match, and spotting new talents in the game, etc. In this work, previous works are reviewed on the prediction of the outcome of a football match, evaluate the merits and demerits of different approaches and then attempt to design a prediction system powered by Recurrent Neural Networks (RNNs) and Long Short Term Memory (LSTMs).