Divekar, Chinmay and Deb, Soudeep and Roy, Rishideep (2024) Real-time forecasting within soccer matches through a Bayesian lens. Journal of the Royal Statistical Society Series A: Statistics in Society, 187 (2). pp. 513-540. DOI https://doi.org/10.1093/jrsssa/qnad136
Divekar, Chinmay and Deb, Soudeep and Roy, Rishideep (2024) Real-time forecasting within soccer matches through a Bayesian lens. Journal of the Royal Statistical Society Series A: Statistics in Society, 187 (2). pp. 513-540. DOI https://doi.org/10.1093/jrsssa/qnad136
Divekar, Chinmay and Deb, Soudeep and Roy, Rishideep (2024) Real-time forecasting within soccer matches through a Bayesian lens. Journal of the Royal Statistical Society Series A: Statistics in Society, 187 (2). pp. 513-540. DOI https://doi.org/10.1093/jrsssa/qnad136
Abstract
his article employs a Bayesian methodology to predict the results of soccer matches in real-time. Using sequential data of various events throughout the match, we utilise 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.
Item Type: | Article |
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Uncontrolled Keywords: | Bayesian method; in-game forecasting; ordered multinomial probit model; soccer prediction |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 27 Sep 2024 14:00 |
Last Modified: | 30 Oct 2024 21:35 |
URI: | http://repository.essex.ac.uk/id/eprint/37600 |