This paper describes the design and implementation of predictive models for sports betting. Specifically, we focused on exploiting Machine Learning (ML) techniques to predict football match results. To this aim, we realized an architecture that operates in two phases. First, it extracts data from the Web through scraping techniques. Then, it gives the collected data in input to different ML algorithms. Experimental tests showed encouraging performance in terms of the Return on Investment (ROI) metric.
Carloni, L., De Angelis, A., Sansonetti, G., Micarelli, A. (2021). A Machine Learning Approach to Football Match Result Prediction. In Communications in Computer and Information Science (pp.473-480). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-78642-7_63].
A Machine Learning Approach to Football Match Result Prediction
De Angelis A.;Sansonetti G.
;Micarelli A.
2021-01-01
Abstract
This paper describes the design and implementation of predictive models for sports betting. Specifically, we focused on exploiting Machine Learning (ML) techniques to predict football match results. To this aim, we realized an architecture that operates in two phases. First, it extracts data from the Web through scraping techniques. Then, it gives the collected data in input to different ML algorithms. Experimental tests showed encouraging performance in terms of the Return on Investment (ROI) metric.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
