Year-end Sale % OFF 
Abstract
The aim of this paper is to explore neural network-based modelling strategies for football betting. A neural network model and a challenger model based on a traditional econometric approach introduced by Dixon were estimated on data from five national leagues results including France, Spain, Italy, Germany, England) Our results show that the Neural network-based model has better predictive accuracy compared with the traditional econometric models. Betting strategies were implemented using prediction outputs generated with both econometric and neural networks models. The latter provides with a better return over investment. Nevertheless, both approaches lead to losses in the long run.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
