Abstract:
Football results prediction has gained popularity in recent years. Nonhybrid approaches have shown complex and low prediction results. Data mining tools with insufficient features, however, have also yielded low predictions. In our research, machine learning has been used to develop a hybrid football match result predictive model for NFL. We constructed a more comprehensive system with improved prediction accuracy by using a hybridized approach. Our prediction system for football match results was implemented using a hybrid of artificial neural network (ANN) and linear regression (LR) techniques with Rapid Miner as a data mining tool. The technique yielded 90.32% prediction accuracy. With this output, it is observed that the prediction accuracy is higher than those of existing systems.
