Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/69255
Título: | A probabilistic model for explaining the points achieved by a team in football competition: forecasting and regression with applications to the Spanish league | Autores/as: | Gómez Déniz, Emilio Dávila Cárdenes, María Nancy Pérez Sánchez, José María |
Clasificación UNESCO: | 5302 Econometría | Palabras clave: | Estadísticas deportivas Distribución lineal Fútbol Liga española de fútbol Covariate, et al. |
Fecha de publicación: | 2019 | Proyectos: | Aportaciones A la Toma de Decisiones Bayesianas Óptimas: Aplicaciones Al Coste-Efectividad Con Datos Clínicos y Al Análisis de Riestos Con Datos Acturiales. | Publicación seriada: | SORT | Resumen: | 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. | URI: | http://hdl.handle.net/10553/69255 | ISSN: | 1696-2281 | DOI: | 10.2436/20.8080.02.81 | Fuente: | Sort-Statistics And Operations Research Transactions [ISSN 1696-2281], v. 43 (1), p. 95-112 | URL: | http://dialnet.unirioja.es/servlet/articulo?codigo=7013162 |
Colección: | Artículos |
Citas SCOPUSTM
4
actualizado el 15-dic-2024
Citas de WEB OF SCIENCETM
Citations
4
actualizado el 15-dic-2024
Visitas
73
actualizado el 17-dic-2023
Descargas
14
actualizado el 17-dic-2023
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.