6 datasets found
  1. Matches Brazilian Football from 2003 to 2024

    • kaggle.com
    Updated Dec 9, 2024
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    Ricardo (2024). Matches Brazilian Football from 2003 to 2024 [Dataset]. http://doi.org/10.34740/kaggle/ds/1050099
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 9, 2024
    Dataset provided by
    Kaggle
    Authors
    Ricardo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Update [09/Dec/2024]

    Uploaded match data for Brasileirão 2024

    Update [07/Dec/2023]

    Uploaded match data for Brasileirão 2023

    Update [14/Nov/2022]

    Uploaded match data for Brasileirão 2022

    Update [12/Dec/2021]

    Uploaded match data for Brasileirão 2021

    General info

    This dataset contains the matches from 2003-2024 of the Brazilian Championship A-Series (BCAS). I stress the fact that the dataset is validated, i.e., the matches produce the final ranking ipsis literis The main file is the matches-2003-2024.txt with self-explanatory columns (header). The other files are complementary to this one and the other with official rankings (ranking-2003-2024.txt).

    Note for the 2020 Season

    All matches starting in January/2021 were modified to January/2020 (and subsequent months in 2021) so my scripts will keep functioning without any other tweaking around. This was necessary because of COVID-19. This is important ONLY for studies where the DATES of the matches do matter.

    ResearchGate paper

    A more comprehensive study may be accessed on ResearchGate, which used Markov Chains for predicting Top 4 and Bottom 4 teams per season.

    I stress the fact that the data has been thoroughly validated against official rankings and all exceptions that have happened during each season (detailed in the paper above, with some useful longitudinal statistics on scores).

    All files (e.g. Perl scripts) are in GitHub as well.

    Brazilian States

    Every team belongs to a state in the federation (totalling 27). In the file I list the team's name followed by its state (after a '/' symbol).

    AC: Acre AL: Alagoas AP: Amapá AM: Amazonas BA: Bahia CE: Ceará DF: Distrito Federal ES: Espírito Santo GO: Goiás MA: Maranhão MT: Mato Grosso MS: Mato Grosso do Sul MG: Minas Gerais PA: Pará PB: Paraíba PR: Paraná PE: Pernambuco PI: Piauí RJ: Rio de Janeiro RN: Rio Grande do Norte RS: Rio Grande do Sul RO: Rondônia RR: Roraima SC: Santa Catarina SP: São Paulo SE: Sergipe TO: Tocantins

  2. Classificacao Brasileirao 10 anos

    • kaggle.com
    Updated Jun 21, 2019
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    Joao Tostes (2019). Classificacao Brasileirao 10 anos [Dataset]. https://www.kaggle.com/joaotostes/classificacao-brasileirao-10-anos/tasks
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 21, 2019
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Joao Tostes
    Description

    I always want to do my best, and since I started at College I wanted to know more about Data Science. What's the best way to know about an area than going deep in the same? That's why I choose some friends to start a project in Data area.

    We are doing the basic, just to get started and aprove our knowledge, so we decided to pick a theme that we like. And in Brazil everybody likes soccer! So we are picking the datas from the championship table since the 2009's one. In the table have basicily all the data os the championship and the team like, victory, losses, draws, number of goals that the team made and have took. We will do some data visualization and try to get some insights and do some graphics.

    I am grateful to all the content that some friendly guys provides at internet, that's the best way to help who are getting started at this tech area at all. And the same way this guys are helping me I will try the help the most people I can, motivating, with content or whatever he needs!

    I am searching for knowleadge so help me do a good project. I need your help to khow the path I have to go, to khow the next step in my project. So I hope we can help eachother.

    JP. :)

  3. Brazilian Soccer Database

    • kaggle.com
    zip
    Updated Oct 27, 2022
    + more versions
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    Ricardo Mattos (2022). Brazilian Soccer Database [Dataset]. https://www.kaggle.com/ricardomattos05/brazilian-soccer-database
    Explore at:
    zip(59653 bytes)Available download formats
    Dataset updated
    Oct 27, 2022
    Authors
    Ricardo Mattos
    Area covered
    Brazil
    Description

    Brazilian Soccer Data

    This repository consists of collecting the history and current data of all the most important competitions that Brazilian teams compete, the principal competitions are:

    • Brasileirão(Brazilian soccer league)
    • Libertatodes(Principal South america Competition)
    • Sudamericana(South American secondary competition)
    • Copa do Brasil(Brazilian Cup)

    Next Steps: - structure the collection of the games of the sudamericana and copa do brasil - Gather data from the main state championships(SP, RJ, MG, RS) - Gather more data from these championships, such as match statistics

    Any questions or suggestions are welcome, feel free to collaborate on the github repository

  4. u

    Data from: Um estudo sobre a aderência normativa dos relatórios dos...

    • repositorio.ufpb.br
    Updated Dec 1, 2021
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    (2021). Um estudo sobre a aderência normativa dos relatórios dos auditores independentes emitidos para os clubes de futebol participantes do Brasileirão Série A [Dataset]. https://repositorio.ufpb.br/jspui/handle/123456789/21762
    Explore at:
    Dataset updated
    Dec 1, 2021
    License

    Attribution-NoDerivs 3.0 (CC BY-ND 3.0)https://creativecommons.org/licenses/by-nd/3.0/
    License information was derived automatically

    Description

    Esta pesquisa teve por objetivo analisar, de forma crítica, o nível de aderência dos relatórios dos auditores independentes emitidos, no biênio 2019 e 2020, para os clubes de futebol do brasileirão série A, em relação as normas brasileiras de contabilidade técnicas de auditoria que disciplinam a sua emissão. Para a realização desta pesquisa utilizou-se a metodologia documental, tendo como fonte primária 18 relatórios emitidos por auditores independentes para os clubes de futebol, para cada um dos anos analisados. Foi realizada uma abordagem qualitativa dos dados para identificar as características de cada relatório e verificar o nível de aderência normativa. Esses dados possibilitaram atestar que a aderência parcial e/ou a não aderência à quantidade de seções compatíveis com o tipo de opinião, à emissão de seção de principais assuntos de auditoria e à identificação apropriada da estrutura do relatório financeiro aplicável presentes em norma, ocasiona uma falha de padronização do Relatório de Auditoria Independente podendo sinalizar uma baixa qualidade no nível da informação prestada.

  5. Brazilian Soccer Odds Data

    • kaggle.com
    Updated Dec 28, 2024
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    Felipe Bandeira (2024). Brazilian Soccer Odds Data [Dataset]. https://www.kaggle.com/datasets/felipebandeiraramos/brazilian-soccer-odds-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 28, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Felipe Bandeira
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Brazil
    Description

    This dataset contains odds data for all matches in the Brazilian soccer championship (Brasileirão) between 2012 and 2024. We started with a dataset from https://www.football-data.co.uk/ and expanded it by scraping oddsportal. The main columns are:

    1. Home, Away: the teams involved
    2. HG, AG, Res: number of goals scored by each team and final result of the match (Home, Draw, or Away)
    3. PSC(x): Pinnacle odds for Home, Draw, Away
    4. MaxC(x),: maximum market odds for Home, Draw, Away
    5. AvgC(x): average market odds for Home, Draw, Away
    6. AvgOver(x), AvgUnder(x), HighOver(x), HighUnder(x): odds for over and under X goals
    7. NumBookmakers(x): the number of bookmakers in the pool where the odds for overs and unders came from
    8. rounds: round of the tournament (counted from the very first round in 2012)
  6. u

    Data from: Gestão dos clubes de futebol do Nordeste: análise econômica e...

    • repositorio.ufpb.br
    Updated Apr 6, 2020
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    (2020). Gestão dos clubes de futebol do Nordeste: análise econômica e esportiva das equipes nordestinas das séries A e B do campeonato brasileiro 2019 [Dataset]. https://repositorio.ufpb.br/jspui/handle/123456789/17868
    Explore at:
    Dataset updated
    Apr 6, 2020
    Description

    O futebol é uma modalidade esportiva amplamente praticada no Brasil e no mundo. Hoje pode ser considerado uma importante atividade econômica, atraindo cada vez mais olhares por todo o planeta. No Brasil não é diferente, com torcedores apaixonados, vibrantes nos estádios pelo país inteiro deixando de ser visto apenas como esporte e passando a ser considerado um negócio rentável e vantajoso. No nordeste os valores monetários no futebol são menores. Assim, a gestão profissional dos clubes assume papel fundamental para planejamento e organização do seu funcionamento. Diante do cenário que o futebol brasileiro atravessa o presente trabalho orientar- se – á no sentido de analisar a gestão através das variáveis de receitas e dividas total, e, as conquistas dos clubes do nordeste que disputaram as séries A e B do campeonato brasileiro de futebol em 2019. Trata se de um estudo descritivo sobre os valores referentes às receitas, dívidas e as conquistas dos clubes de futebol do nordeste. Quanto aos procedimentos é documental, devido à coleta de dados em arquivos, sites e estudos publicados. Os resultados apontam para dependência dos clubes em relação às receitas oriundas das cotas de tv, alguns clubes da amostra tiveram aumento de suas receitas, outros reduziram as dividas totais. No tocante aos títulos, os clubes da amostra dominam as conquistas de nível estadual, porém já alcançam resultados a nível nacional como os brasileiros de série B e C no período do estudo. Porém,em alguns casos o desempenho fora de campo não refletiu dentro, resultando em rebaixamentos para a segunda divisão do brasileiro, sendo necessária a atuação profissional do gestor. Conclui se que existe relação positiva entre a gestão e o desempenho esportivo, poisos resultados do estudo corroboram com pesquisas de autores nacionais e internacionais no que diz respeito à relação entre a gestão e o desempenho dentro de campo.

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Ricardo (2024). Matches Brazilian Football from 2003 to 2024 [Dataset]. http://doi.org/10.34740/kaggle/ds/1050099
Organization logo

Matches Brazilian Football from 2003 to 2024

Dataset with scores of the Brazilian National Football Championship - A Series

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Dec 9, 2024
Dataset provided by
Kaggle
Authors
Ricardo
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Update [09/Dec/2024]

Uploaded match data for Brasileirão 2024

Update [07/Dec/2023]

Uploaded match data for Brasileirão 2023

Update [14/Nov/2022]

Uploaded match data for Brasileirão 2022

Update [12/Dec/2021]

Uploaded match data for Brasileirão 2021

General info

This dataset contains the matches from 2003-2024 of the Brazilian Championship A-Series (BCAS). I stress the fact that the dataset is validated, i.e., the matches produce the final ranking ipsis literis The main file is the matches-2003-2024.txt with self-explanatory columns (header). The other files are complementary to this one and the other with official rankings (ranking-2003-2024.txt).

Note for the 2020 Season

All matches starting in January/2021 were modified to January/2020 (and subsequent months in 2021) so my scripts will keep functioning without any other tweaking around. This was necessary because of COVID-19. This is important ONLY for studies where the DATES of the matches do matter.

ResearchGate paper

A more comprehensive study may be accessed on ResearchGate, which used Markov Chains for predicting Top 4 and Bottom 4 teams per season.

I stress the fact that the data has been thoroughly validated against official rankings and all exceptions that have happened during each season (detailed in the paper above, with some useful longitudinal statistics on scores).

All files (e.g. Perl scripts) are in GitHub as well.

Brazilian States

Every team belongs to a state in the federation (totalling 27). In the file I list the team's name followed by its state (after a '/' symbol).

AC: Acre AL: Alagoas AP: Amapá AM: Amazonas BA: Bahia CE: Ceará DF: Distrito Federal ES: Espírito Santo GO: Goiás MA: Maranhão MT: Mato Grosso MS: Mato Grosso do Sul MG: Minas Gerais PA: Pará PB: Paraíba PR: Paraná PE: Pernambuco PI: Piauí RJ: Rio de Janeiro RN: Rio Grande do Norte RS: Rio Grande do Sul RO: Rondônia RR: Roraima SC: Santa Catarina SP: São Paulo SE: Sergipe TO: Tocantins

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