Title : 
Predicting football scores using machine learning techniques
         
        
            Author : 
Josip Hucaljuk;Alen Rakipović
         
        
            Author_Institution : 
University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia
         
        
        
            fDate : 
5/1/2011 12:00:00 AM
         
        
        
        
            Abstract : 
Predicting the results of football matches poses an interesting challenge due to the fact that the sport is so popular and widespread. However, predicting the outcomes is also a difficult problem because of the number of factors which must be taken into account that cannot be quantitatively valued or modeled. As part of this work, a software solution has been developed in order to try and solve this problem. During the development of the system, a number of tests have been carried out in order to determine the optimal combination of features and classifiers. The results of the presented system show a satisfactory capability of prediction which is superior to the one of the reference method (most likely a priori outcome).
         
        
            Keywords : 
"Classification algorithms","Bayesian methods","Games","Artificial neural networks","Training","Accuracy","Testing"
         
        
        
            Conference_Titel : 
MIPRO, 2011 Proceedings of the 34th International Convention
         
        
            Print_ISBN : 
978-1-4577-0996-8