Real-time forecasting within soccer matches through a Bayesian lens

Autor:	Divekar, Chinmay, Deb, Soudeep, Roy, Rishideep
Rok vydání:	2023
Předmět:	Statistics - Applications Statistics - Methodology
Zdroj:	Volume 187, Issue 2, April 2024, Pages 513-540
Druh dokumentu:	Working Paper
DOI:	10.1093/jrsssa/qnad136
Popis:	This paper employs a Bayesian methodology to predict the results of soccer matches in real-time. Using sequential data of various events throughout the match, we utilize a multinomial probit regression in a novel framework to estimate the time-varying impact of covariates and to forecast the outcome. English Premier League data from eight seasons are used to evaluate the efficacy of our method. Different evaluation metrics establish that the proposed model outperforms potential competitors inspired by existing statistical or machine learning algorithms. Additionally, we apply robustness checks to demonstrate the model's accuracy across various scenarios. Comment: 31 pages, 11 figures, 2 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2303.12401 Zobrazit plný text záznamu View this record from Arxiv