Web of Science: 3 cites, Scopus: 2 cites, Google Scholar: cites
A probabilistic model for explaining the points achieved by a team in football competition : forecasting and regression with applications to the Spanish competition
Gómez-Déniz, Emilio (Universidad de Las Palmas de Gran Canaria)
Dávila Cárdenes, Nancy (Universidad de Las Palmas de Gran Canaria)
Pérez Sánchez, José María (Universidad de Las Palmas de Gran Canaria)

Data: 2019
Resum: In the last decades, a lot of research papers applying statistical methods for analysing sports data have been published. Football, also called soccer, is one of the most popular sports all over the world organised in national championships in a round robin format in which the team reaching the most points at the end of the tournament wins the competition. The aim of this work is to develop a suitable probability model for studying the points achieved by a team in a football match. For this purpose, we built a discrete probability distribution taking values, zero for losing, one for a draw and three for a victory. We test its performance using data from the Spanish Football League (First division) during the 2013-14 season. Furthermore, the model provides an attractive framework for predicting points and incorporating covariates in order to study the factors affecting the points achieved by the teams.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Matèria: Covariate ; Football data ; Forecasting ; Regression ; Sport statistics ; Truncated distribution ; Weighted distribution
Publicat a: SORT : statistics and operations research transactions, Vol. 43 Núm. 1 (January-June 2019) , p. 95-112 (Articles) , ISSN 2013-8830

Adreça alternativa: https://raco.cat/index.php/SORT/article/view/356183
DOI: 10.2436/20.8080.02.81

18 p, 437.6 KB

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