Capitalizing on market inefficiencies with neural networks: a case study in football betting

Autores
Arana, Joaquín Matías
Año de publicación
2024
Idioma
inglés
Tipo de recurso
tesis de grado
Estado
versión corregida
Colaborador/a o director/a de tesis
Gómez Seeber, Matías José
Descripción
Fil: Arana, Joaquín Matías. Universidad de San Andrés. Departamento de Economía; Argentina.
This paper introduces a machine learning approach for profiting from sports betting markets, which are non-arbitraged inefficient markets that present opportunities for exploiting discrepancies between bookmaker odds and actual probabilities of outcomes. I will develop a Neural Network Model that accurately forecasts the events of two different football competitions: The English Premier League and The Argentine’s First Division. A betting strategy based on Markow’s portfolio theory is developed to exploit inconsistencies and maximize yield over time. The findings suggest that machine learning algorithms, like the one presented in this study, could potentially enable consistent profitability in sports betting by identifying inefficiencies in bookmaker odds.
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
Repositorio Digital San Andrés (UdeSa)
Institución
Universidad de San Andrés
OAI Identificador
oai:repositorio.udesa.edu.ar:10908/25214
Acceder
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network_name_str Repositorio Digital San Andrés (UdeSa)
spelling Capitalizing on market inefficiencies with neural networks: a case study in football bettingArana, Joaquín MatíasFil: Arana, Joaquín Matías. Universidad de San Andrés. Departamento de Economía; Argentina.This paper introduces a machine learning approach for profiting from sports betting markets, which are non-arbitraged inefficient markets that present opportunities for exploiting discrepancies between bookmaker odds and actual probabilities of outcomes. I will develop a Neural Network Model that accurately forecasts the events of two different football competitions: The English Premier League and The Argentine’s First Division. A betting strategy based on Markow’s portfolio theory is developed to exploit inconsistencies and maximize yield over time. The findings suggest that machine learning algorithms, like the one presented in this study, could potentially enable consistent profitability in sports betting by identifying inefficiencies in bookmaker odds.Universidad de San Andrés. Departamento de EconomíaGómez Seeber, Matías José2025-05-22T15:31:13Z2025-05-22T15:31:13Z2024-12Tesisinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/updatedVersionhttp://purl.org/coar/resource_type/c_7a1finfo:ar-repo/semantics/tesisDeGradoapplication/pdfapplication/pdfArana, J. M. (2024). Capitalizing on market inefficiencies with neural networks: a case study in football betting. [Tesis de grado, Universidad de San Andrés. Departamento de Economía]. Repositorio Digital San Andrés. https://repositorio.udesa.edu.ar/handle/10908/25214https://repositorio.udesa.edu.ar/handle/10908/25214enginfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/reponame:Repositorio Digital San Andrés (UdeSa)instname:Universidad de San Andrés2025-10-23T11:19:22Zoai:repositorio.udesa.edu.ar:10908/25214instacron:Universidad de San AndrésInstitucionalhttp://repositorio.udesa.edu.ar/jspui/Universidad privadaNo correspondehttp://repositorio.udesa.edu.ar/oai/requestmsanroman@udesa.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:23632025-10-23 11:19:22.959Repositorio Digital San Andrés (UdeSa) - Universidad de San Andrésfalse
dc.title.none.fl_str_mv Capitalizing on market inefficiencies with neural networks: a case study in football betting
title Capitalizing on market inefficiencies with neural networks: a case study in football betting
spellingShingle Capitalizing on market inefficiencies with neural networks: a case study in football betting
Arana, Joaquín Matías
title_short Capitalizing on market inefficiencies with neural networks: a case study in football betting
title_full Capitalizing on market inefficiencies with neural networks: a case study in football betting
title_fullStr Capitalizing on market inefficiencies with neural networks: a case study in football betting
title_full_unstemmed Capitalizing on market inefficiencies with neural networks: a case study in football betting
title_sort Capitalizing on market inefficiencies with neural networks: a case study in football betting
dc.creator.none.fl_str_mv Arana, Joaquín Matías
author Arana, Joaquín Matías
author_facet Arana, Joaquín Matías
author_role author
dc.contributor.none.fl_str_mv Gómez Seeber, Matías José
dc.description.none.fl_txt_mv Fil: Arana, Joaquín Matías. Universidad de San Andrés. Departamento de Economía; Argentina.
This paper introduces a machine learning approach for profiting from sports betting markets, which are non-arbitraged inefficient markets that present opportunities for exploiting discrepancies between bookmaker odds and actual probabilities of outcomes. I will develop a Neural Network Model that accurately forecasts the events of two different football competitions: The English Premier League and The Argentine’s First Division. A betting strategy based on Markow’s portfolio theory is developed to exploit inconsistencies and maximize yield over time. The findings suggest that machine learning algorithms, like the one presented in this study, could potentially enable consistent profitability in sports betting by identifying inefficiencies in bookmaker odds.
description Fil: Arana, Joaquín Matías. Universidad de San Andrés. Departamento de Economía; Argentina.
publishDate 2024
dc.date.none.fl_str_mv 2024-12
2025-05-22T15:31:13Z
2025-05-22T15:31:13Z
dc.type.none.fl_str_mv Tesis
info:eu-repo/semantics/bachelorThesis
info:eu-repo/semantics/updatedVersion
http://purl.org/coar/resource_type/c_7a1f
info:ar-repo/semantics/tesisDeGrado
format bachelorThesis
status_str updatedVersion
dc.identifier.none.fl_str_mv Arana, J. M. (2024). Capitalizing on market inefficiencies with neural networks: a case study in football betting. [Tesis de grado, Universidad de San Andrés. Departamento de Economía]. Repositorio Digital San Andrés. https://repositorio.udesa.edu.ar/handle/10908/25214
https://repositorio.udesa.edu.ar/handle/10908/25214
identifier_str_mv Arana, J. M. (2024). Capitalizing on market inefficiencies with neural networks: a case study in football betting. [Tesis de grado, Universidad de San Andrés. Departamento de Economía]. Repositorio Digital San Andrés. https://repositorio.udesa.edu.ar/handle/10908/25214
url https://repositorio.udesa.edu.ar/handle/10908/25214
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidad de San Andrés. Departamento de Economía
publisher.none.fl_str_mv Universidad de San Andrés. Departamento de Economía
dc.source.none.fl_str_mv reponame:Repositorio Digital San Andrés (UdeSa)
instname:Universidad de San Andrés
reponame_str Repositorio Digital San Andrés (UdeSa)
collection Repositorio Digital San Andrés (UdeSa)
instname_str Universidad de San Andrés
repository.name.fl_str_mv Repositorio Digital San Andrés (UdeSa) - Universidad de San Andrés
repository.mail.fl_str_mv msanroman@udesa.edu.ar
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