Publicação
Exploring Stochastic Efficiency Analysis for Expected Goals in Football: Assessing Offensive Efficiency Across Europes’s Major Football Leagues
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | Damásio, Bruno Miguel Pinto | |
| dc.contributor.author | Vilela, João António Torres Fernandes | |
| dc.date.accessioned | 2024-11-15T14:21:37Z | |
| dc.date.available | 2024-11-15T14:21:37Z | |
| dc.date.issued | 2024-11-06 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics | pt_PT |
| dc.description.abstract | This thesis explores how football analytics have changed with the use of advanced metrics, especially focusing on expected goals (xG) to measure player and team performance. The goal is to understand how xG relates to some of the football statistics and metrics that are used a lot, like number of shots, age, and market value of the players in the top five European football leagues from the season 2014-2015 to the season 2022-2023 . Using data from reliable football analytics websites, this study uses Stochastic Frontier Analysis (SFA) to evaluate offensive inefficiency, using the xG metric as the output of the equation and market value, age, shots, and player position were the chosen inputs. The results demonstrate that defenders and goalkeepers showed that they have less impact on offensive efficiency than the forwards and the midfielders, who showed that they have a significant impact on the game. Even with certain data limitations, the conclusions offer football teams useful information to improve player efficiency and guide strategic investment choices. | pt_PT |
| dc.identifier.tid | 203777158 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/175312 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Expected Goals (xG) | pt_PT |
| dc.subject | Stochastic Frontier Analysis (SFA) | pt_PT |
| dc.subject | Offensive Efficiency | pt_PT |
| dc.subject | Performance Metrics | pt_PT |
| dc.subject | Football Analytics | pt_PT |
| dc.subject | SDG 8 - Decent work and economic growth | pt_PT |
| dc.subject | SDG 9 - Industry, innovation and infrastructure | pt_PT |
| dc.title | Exploring Stochastic Efficiency Analysis for Expected Goals in Football: Assessing Offensive Efficiency Across Europes’s Major Football Leagues | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Ciência de Dados e Métodos Analíticos Avançados, especialização em Métodos Analíticos para a Gestão | pt_PT |