Tennis Betting Strategies Based on Neural Networks

Autor:	Jeremy Flahault, Nicolas Le Roger, Marius Frunza
Rok vydání:	2020
Předmět:	Artificial neural network Computer science business.industry Investment strategy Victory Statistical model Artificial intelligence business Machine learning computer.software_genre computer Risk profile Odds
Zdroj:	SSRN Electronic Journal.
ISSN:	1556-5068
DOI:	10.2139/ssrn.3660940
Popis:	The aim of this paper is to explore betting strategies for tennis matches using neural networks. We used public data and we implemented a neural network prediction model, with an accuracy of 85% on the validation and testing sets. Based on the predictive model we tested several investment strategies which incorporates investor's risk profile. The optimal strategy is to place bets on games where our model indicates a high likelihood of victory and an appropriate bookmaker's odds.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::51c18db97f176914215be04a933e8365 https://doi.org/10.2139/ssrn.3660940 Zobrazit plný text záznamu