Metodologia para análise preditiva de resultados de jogos esportivos: um estudo de caso por jogos da NBA.

Abstract

This article presents a methodology for predictive analysis of sports game results, using National Basketball Association (NBA) games as a case study. Specifically, the NBA is renowned for using data analytics and advanced statistics to improve team and player performance. The objectives of this work are to analyze the availability and quality of NBA data, select variables for predictive analysis, apply machine learning techniques to predict NBA game results and evaluate the effectiveness of the proposed methodology. The methodology includes data collection obtained through the data scraping technique used on the official NBA website, data pre-processing, selection of the most relevant variables through the PCA technique, modeling and evaluation. The results obtained demonstrate an effective methodology for predictive analysis of results of sports games, regarding the identification of the most important variables to predict results of NBA games and statistics of prediction success. The present work, therefore, contributes to the advancement of predictive analytics in sports and other fields of application.