ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO PREDICT TEAMS POSITION OF THE BRAZILIAN FOOTBALL CHAMPIONSHIP

TÉCNICAS DE INTELIGÊNCIA ARTIFICIAL APLICADAS PARA PREVISÃO DA POSIÇÃO DE TIMES DO CAMPEONATO BRASILEIRO DE FUTEBOL

ABSTRACT

This study presents a classifier prediction in groups for the Brazilian Football Championship of both A and B leagues, from the results of the first half of each championship. With assertive predictions of the group where a team will end the championship, strategic planning can be performed in the squad, such as new hiring, specific training for athletes, and possible championships that the team will be entitled to participate in according to the group classification. In order to find the predictions, two techniques of artificial intelligence were applied: Multi-Layer Perceptron (MLP), which is a type of artificial neural network, and Support Vector Machine (SVM). Preliminary results show that the proposed methodology is very promising, with more than 40% successful cases with MLP and almost 50% with SVM. Moreover, results indicate that the methodology is able to make a reasonable prediction by missing one group of the true group at the end of the championship. The SVM technique was slightly better than MLP. A post-processing analysis of the SVM results was applied to the 2018 A league data from the Brazilian championship, resulting in 85% success indicator of groups.

Keywords:
Brazilian football championship; Reasonable predictions; Post-processing results