The effect of injuries on football players' market values - the role of player positions

Detalhes bibliográficos
Autor(a) principal: Beyerlein, Julian
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/161181
Resumo: Football players’ market values are intensively researched as the focus gradually shifts from qualitative approaches and subjective perception to data-driven estimation. Previous work drew on player characteristics and top-level performance metrics but only few included injuries. This thesis resorts to data from Opta and Transfermarkt and leverages MLR and machine learning approaches to derive market values. The LightGBM and MLR models predict market values accurately and identify direct impacts of injuries. Additionally, I found that player positions matter for injury incidence and severity.
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spelling The effect of injuries on football players' market values - the role of player positionsFootballMarket valuesInjuriesMachine learningLightGBMMLROptaTransfermarktDomínio/Área Científica::Ciências Sociais::Economia e GestãoFootball players’ market values are intensively researched as the focus gradually shifts from qualitative approaches and subjective perception to data-driven estimation. Previous work drew on player characteristics and top-level performance metrics but only few included injuries. This thesis resorts to data from Opta and Transfermarkt and leverages MLR and machine learning approaches to derive market values. The LightGBM and MLR models predict market values accurately and identify direct impacts of injuries. Additionally, I found that player positions matter for injury incidence and severity.Brinca, PedroRUNBeyerlein, Julian2023-12-13T09:49:23Z2022-12-162022-12-162022-12-16T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/161181TID:203317645enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:44:01Zoai:run.unl.pt:10362/161181Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:58:24.684785Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The effect of injuries on football players' market values - the role of player positions
title The effect of injuries on football players' market values - the role of player positions
spellingShingle The effect of injuries on football players' market values - the role of player positions
Beyerlein, Julian
Football
Market values
Injuries
Machine learning
LightGBM
MLR
Opta
Transfermarkt
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short The effect of injuries on football players' market values - the role of player positions
title_full The effect of injuries on football players' market values - the role of player positions
title_fullStr The effect of injuries on football players' market values - the role of player positions
title_full_unstemmed The effect of injuries on football players' market values - the role of player positions
title_sort The effect of injuries on football players' market values - the role of player positions
author Beyerlein, Julian
author_facet Beyerlein, Julian
author_role author
dc.contributor.none.fl_str_mv Brinca, Pedro
RUN
dc.contributor.author.fl_str_mv Beyerlein, Julian
dc.subject.por.fl_str_mv Football
Market values
Injuries
Machine learning
LightGBM
MLR
Opta
Transfermarkt
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Football
Market values
Injuries
Machine learning
LightGBM
MLR
Opta
Transfermarkt
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description Football players’ market values are intensively researched as the focus gradually shifts from qualitative approaches and subjective perception to data-driven estimation. Previous work drew on player characteristics and top-level performance metrics but only few included injuries. This thesis resorts to data from Opta and Transfermarkt and leverages MLR and machine learning approaches to derive market values. The LightGBM and MLR models predict market values accurately and identify direct impacts of injuries. Additionally, I found that player positions matter for injury incidence and severity.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-16
2022-12-16
2022-12-16T00:00:00Z
2023-12-13T09:49:23Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/161181
TID:203317645
url http://hdl.handle.net/10362/161181
identifier_str_mv TID:203317645
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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