O uso do jogo eletrônico Football Manager e do portal Transfermarkt para mensurar o potencial de futebolistas promissores
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Data
2022-07-12
Autores
Rocha-Lima, Eric Matheus [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
Técnicas e recursos computacionais, direcionados para a análise de dados, estão ganhando espaço no futebol, sobretudo por permitir que amplos volumes de dados dos futebolistas sejam analisados e que relações, que apontem padrões a serem explorados, possam ser obtidas. Deste modo a utilização de simuladores futebolísticos, como o Football Manager (FM) e de websites especializados em futebol, como o Transfermarkt (TM), também podem contribuir para a aquisição de dados que auxiliem os clubes a identificar e investir em jovens futebolistas. Sendo assim, o presente trabalho tem o objetivo de identificar relações entre indicadores de futebolistas que apontem o desenvolvimento da capacidade potencial destes atletas. Para atingir este objetivo, foi aplicada uma pesquisa qualiquantitativa, de caráter descritivo e documental. A amostra é composta por 1309 futebolistas, entre 15 e 20 anos, presentes em uma lista do FM Scout de 2014. A coleta das informações dos futebolistas foi realizada nas versões FM 2015 e FM 2019 do Football Manager e no TM, neste último, em dois momentos: ao término das temporadas 2014/2015 e 2018/2019. Para as análises, foram utilizadas técnicas da chamada mineração de dados (MD), com o auxílio do software Weka. Os resultados indicam que, dos futebolistas que estavam no nível profissional na temporada 2014/2015, foi alta a porcentagem dos que permaneceram nesta condição no período de 2018/2019. Também indicam que se mostra interessante investir em atletas com menos de 18 anos, pois apresentaram maior porcentagem de aumento de capacidade atual (CA). Além disso, para gerar aumento CA, sugere-se uma quantidade de 30 ou mais partidas para os futebolistas. Em relação aos valores de mercado (VM), o Weka indicou que se mostra interessante aumentar o VM para obter melhora de CA em todas as classes de capacidade potencial e, para aumentar VM, não realizar uma transferência e empréstimos surgiram como sugestões. Por fim, conclui-se que a utilização do FM se apresenta como uma ferramenta complementar e de pertinente utilidade para auxiliar os gestores futebolísticos em suas tomadas de decisão na identificação e na contratação de jovens futebolistas com capacidade potencial a ser desenvolvida.
Computational techniques directed to data analysis are gaining space in football, above all by allowing wide volume of footballers’ data to be analyzed and that relations, that point patterns to be exploited, can be obtained. So, the use of football simulators like Football Manager (FM) and football specialized websites like Transfermarkt (TM) can also contribute to data acquisition that helps clubs to identify and to invest in young footballers. Therefore, the present work aims to identify relations among footballers’ indicators that point these young athletes’ potential ability development. To achieve this objective, a descriptive and documentary’s qualitative research will be applied. The sample consists of 1309 footballers, between 15 and 20 years old, present on a 2014 FM Scout list. The footballer’s data collection was made at FM 2015, FM 2019 and TM’s website at the end of seasons 2014/2015 and 2018/2019, looking forward the footballers’ potential ability development verification. So, data mining (MD) techniques were used with the Weka software’s help. The obtained results indicated high stay of footballers that were in a professional level at season 2014/2015, in season 2018/2019, like it appeared interesting to invest in athletes younger than 18 years old in the initial season of the research, since they presented a higher chance to improve current ability (CA). Besides, to generate higher CA, it is suggested the quantity of 30 or more matches to the players. Treating the market values (MV), Weka indicated that seems to be interesting the MV increasement in order to improve CA for all classes of potential ability and, to obtain a higher MV, no transfer moves and loans appeared as suggestions. Lastly, it is possible to conclude that FM’s use is a useful additional tool to help football managers in their decision making about identifying and signing young players with potential ability to be developed.
Computational techniques directed to data analysis are gaining space in football, above all by allowing wide volume of footballers’ data to be analyzed and that relations, that point patterns to be exploited, can be obtained. So, the use of football simulators like Football Manager (FM) and football specialized websites like Transfermarkt (TM) can also contribute to data acquisition that helps clubs to identify and to invest in young footballers. Therefore, the present work aims to identify relations among footballers’ indicators that point these young athletes’ potential ability development. To achieve this objective, a descriptive and documentary’s qualitative research will be applied. The sample consists of 1309 footballers, between 15 and 20 years old, present on a 2014 FM Scout list. The footballer’s data collection was made at FM 2015, FM 2019 and TM’s website at the end of seasons 2014/2015 and 2018/2019, looking forward the footballers’ potential ability development verification. So, data mining (MD) techniques were used with the Weka software’s help. The obtained results indicated high stay of footballers that were in a professional level at season 2014/2015, in season 2018/2019, like it appeared interesting to invest in athletes younger than 18 years old in the initial season of the research, since they presented a higher chance to improve current ability (CA). Besides, to generate higher CA, it is suggested the quantity of 30 or more matches to the players. Treating the market values (MV), Weka indicated that seems to be interesting the MV increasement in order to improve CA for all classes of potential ability and, to obtain a higher MV, no transfer moves and loans appeared as suggestions. Lastly, it is possible to conclude that FM’s use is a useful additional tool to help football managers in their decision making about identifying and signing young players with potential ability to be developed.
Descrição
Palavras-chave
Futebol, Football Manager, Jovens futebolistas, Mercado de transferências, Mineração de dados, Footbal, Youth players, Transfer market, Data mining