63 datasets found
  1. English Premier League 19-20 Player Stats data

    • kaggle.com
    zip
    Updated Sep 7, 2020
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    Jaseem Mohammed (2020). English Premier League 19-20 Player Stats data [Dataset]. https://www.kaggle.com/machinemind/english-premier-league-1920-player-stats-data
    Explore at:
    zip(16598 bytes)Available download formats
    Dataset updated
    Sep 7, 2020
    Authors
    Jaseem Mohammed
    Description

    Dataset

    This dataset was created by Jaseem Mohammed

    Contents

    It contains the following files:

  2. Data from: The Business of the English Premier League

    • store.globaldata.com
    Updated Oct 31, 2020
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    GlobalData UK Ltd. (2020). The Business of the English Premier League [Dataset]. https://store.globaldata.com/report/the-business-of-the-english-premier-league/
    Explore at:
    Dataset updated
    Oct 31, 2020
    Dataset provided by
    GlobalDatahttps://www.globaldata.com/
    Authors
    GlobalData UK Ltd.
    License

    https://www.globaldata.com/privacy-policy/https://www.globaldata.com/privacy-policy/

    Time period covered
    2020 - 2024
    Area covered
    Global
    Description

    Detailed analysis of the business of the English Premier League, focusing on sponsorship and the media landscape Read More

  3. xG Data for Each team, Premier League 21/22

    • kaggle.com
    zip
    Updated Aug 25, 2022
    + more versions
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    MHumph (2022). xG Data for Each team, Premier League 21/22 [Dataset]. https://www.kaggle.com/datasets/mhumph/xg-data-for-each-team-premier-league-2122
    Explore at:
    zip(11171 bytes)Available download formats
    Dataset updated
    Aug 25, 2022
    Authors
    MHumph
    License

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

    Description

    Dataset

    This dataset was created by MHumph

    Released under CC BY-SA 4.0

    Contents

  4. Revenue of Premier League clubs 2013-2025, by stream

    • statista.com
    Updated Jul 17, 2024
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    Statista (2024). Revenue of Premier League clubs 2013-2025, by stream [Dataset]. https://www.statista.com/statistics/556893/premier-league-clubs-revenue-by-stream/
    Explore at:
    Dataset updated
    Jul 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom (England)
    Description

    In 2022/23, broadcasting revenue was worth over three billion euros to clubs in the Premier League, representing their most significant source of income. Meanwhile, revenue from matchdays totaled nearly 870 million euros.

  5. 2022-2023 Football Player Stats

    • kaggle.com
    Updated Feb 12, 2023
    + more versions
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    Vivo Vinco (2023). 2022-2023 Football Player Stats [Dataset]. https://www.kaggle.com/datasets/vivovinco/20222023-football-player-stats/versions/5
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 12, 2023
    Dataset provided by
    Kaggle
    Authors
    Vivo Vinco
    License

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

    Description

    Context

    This dataset contains 2022-2023 football player stats per 90 minutes. Only players of Premier League, Ligue 1, Bundesliga, Serie A and La Liga are listed.

    Content

    +2500 rows and 124 columns. Columns' description are listed below.

    • Rk : Rank
    • Player : Player's name
    • Nation : Player's nation
    • Pos : Position
    • Squad : Squad’s name
    • Comp : League that squat occupies
    • Age : Player's age
    • Born : Year of birth
    • MP : Matches played
    • Starts : Matches started
    • Min : Minutes played
    • 90s : Minutes played divided by 90
    • Goals : Goals scored or allowed
    • Shots : Shots total (Does not include penalty kicks)
    • SoT : Shots on target (Does not include penalty kicks)
    • SoT% : Shots on target percentage (Does not include penalty kicks)
    • G/Sh : Goals per shot
    • G/SoT : Goals per shot on target (Does not include penalty kicks)
    • ShoDist : Average distance, in yards, from goal of all shots taken (Does not include penalty kicks)
    • ShoFK : Shots from free kicks
    • ShoPK : Penalty kicks made
    • PKatt : Penalty kicks attempted
    • PasTotCmp : Passes completed
    • PasTotAtt : Passes attempted
    • PasTotCmp% : Pass completion percentage
    • PasTotDist : Total distance, in yards, that completed passes have traveled in any direction
    • PasTotPrgDist : Total distance, in yards, that completed passes have traveled towards the opponent's goal
    • PasShoCmp : Passes completed (Passes between 5 and 15 yards)
    • PasShoAtt : Passes attempted (Passes between 5 and 15 yards)
    • PasShoCmp% : Pass completion percentage (Passes between 5 and 15 yards)
    • PasMedCmp : Passes completed (Passes between 15 and 30 yards)
    • PasMedAtt : Passes attempted (Passes between 15 and 30 yards)
    • PasMedCmp% : Pass completion percentage (Passes between 15 and 30 yards)
    • PasLonCmp : Passes completed (Passes longer than 30 yards)
    • PasLonAtt : Passes attempted (Passes longer than 30 yards)
    • PasLonCmp% : Pass completion percentage (Passes longer than 30 yards)
    • Assists : Assists
    • PasAss : Passes that directly lead to a shot (assisted shots)
    • Pas3rd : Completed passes that enter the 1/3 of the pitch closest to the goal
    • PPA : Completed passes into the 18-yard box
    • CrsPA : Completed crosses into the 18-yard box
    • PasProg : Completed passes that move the ball towards the opponent's goal at least 10 yards from its furthest point in the last six passes, or any completed pass into the penalty area
    • PasAtt : Passes attempted
    • PasLive : Live-ball passes
    • PasDead : Dead-ball passes
    • PasFK : Passes attempted from free kicks
    • TB : Completed pass sent between back defenders into open space
    • Sw : Passes that travel more than 40 yards of the width of the pitch
    • PasCrs : Crosses
    • TI : Throw-Ins taken
    • CK : Corner kicks
    • CkIn : Inswinging corner kicks
    • CkOut : Outswinging corner kicks
    • CkStr : Straight corner kicks
    • PasCmp : Passes completed
    • PasOff : Offsides
    • PasBlocks : Blocked by the opponent who was standing it the path
    • SCA : Shot-creating actions
    • ScaPassLive : Completed live-ball passes that lead to a shot attempt
    • ScaPassDead : Completed dead-ball passes that lead to a shot attempt
    • ScaDrib : Successful dribbles that lead to a shot attempt
    • ScaSh : Shots that lead to another shot attempt
    • ScaFld : Fouls drawn that lead to a shot attempt
    • ScaDef : Defensive actions that lead to a shot attempt
    • GCA : Goal-creating actions
    • GcaPassLive : Completed live-ball passes that lead to a goal
    • GcaPassDead : Completed dead-ball passes that lead to a goal
    • GcaDrib : Successful dribbles that lead to a goal
    • GcaSh : Shots that lead to another goal-scoring shot
    • GcaFld : Fouls drawn that lead to a goal
    • GcaDef : Defensive actions that lead to a goal
    • Tkl : Number of players tackled
    • TklWon : Tackles in which the tackler's team won possession of the ball
    • TklDef3rd : Tackles in defensive 1/3
    • TklMid3rd : Tackles in middle 1/3
    • TklAtt3rd : Tackles in attacking 1/3
    • TklDri : Number of dribblers tackled
    • TklDriAtt : Number of times dribbled past plus number of tackles
    • TklDri% : Percentage of dribblers tackled
    • TklDriPast : Number of times dribbled past by an opposing player
    • Blocks : Number of times blocking the ball by standing in its path
    • BlkSh : Number of times blocking a shot by standing in its path
    • BlkPass : Number of times blocking a pass by standing in its path
    • Int : Interceptions
    • Tkl+Int : Number of players tackled plus number of interceptions
    • Clr : Clearances
    • Err : Mistakes leading to an opponent's shot
    • Touches : Number of times a player touched the ball. Note: Receiving a pass, then dribbling, then sending a pass counts as one touch
    • TouDefPen : Touches in defensive penalty area
    • TouDef3rd : Touches in defensive 1/3
    • TouMid3rd : Touches in middle 1/3
    • TouAtt3rd : Touches in attacking 1/3
    • TouAttPen : Touches in attacking penalty area
    • TouLive : Live-ball touches. Does not include corner kicks, free kicks, throw-ins, kick-offs, goal kicks or penalty kicks.
    • ToAtt : Number of attempts to take on defenders while dribbling
    • ToSuc : Number of defenders taken on successfully, by dribbling past them
    • ToSuc% : Percentage of take-ons Completed Successfully
    • ToTkl : Number of times tackled by a defender during a take-on attempt
    • ToTkl% : Percentage of time tackled by a defender during a take-on attempt
    • Carries : Number of times the player controlled the ball with their feet
    • CarTotDist : Total distance, in yards, a player moved the ball while controlling it with their feet, in any direction
    • CarPrgDist : Total distance, in yards, a player moved the ball while controlling it with their feet towards the opponent's goal
    • CarProg : Carries that move the ball towards the opponent's goal at least 5 yards, or any carry into the penalty area
    • Car3rd : Carries that enter the 1/3 of the pitch closest to the goal
    • CPA : Carries into the 18-yard box
    • CarMis : Number of times a player failed when attempting to gain control of a ball
    • CarDis : Number of times a player loses control of the ball after being tackled by an opposing player
    • Rec : Number of times a player successfully received a pass
    • RecProg : Completed passes that move the ball towards the opponent's goal at least 10 yards from its furthest point in the last six passes, or any completed pass into the penalty area
    • CrdY : Yellow cards
    • CrdR : Red cards
    • 2CrdY : Second yellow card
    • Fls : Fouls committed
    • Fld : Fouls drawn
    • Off : Offsides
    • Crs : Crosses
    • TklW : Tackles in which the tackler's team won possession of the ball
    • PKwon : Penalty kicks won
    • PKcon : Penalty kicks conceded
    • OG : Own goals
    • Recov : Number of loose balls recovered
    • AerWon : Aerials won
    • AerLost : Aerials lost
    • AerWon% : Percentage of aerials won

    Acknowledgements

    Data from Football Reference. Image from Sky Sports.

    If you're reading this, please upvote.

  6. Results for group 1 v group 2 balanced data set (Best Average Test...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    + more versions
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    Donald Barron; Graham Ball; Matthew Robins; Caroline Sunderland (2023). Results for group 1 v group 2 balanced data set (Best Average Test Performance = 61.5% and Best Average Test Error = 11.6% with a combination of seven variables) and group 1 v group 2 model variables as means and standard deviations for player groupings. [Dataset]. http://doi.org/10.1371/journal.pone.0205818.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Donald Barron; Graham Ball; Matthew Robins; Caroline Sunderland
    License

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

    Description

    Results for group 1 v group 2 balanced data set (Best Average Test Performance = 61.5% and Best Average Test Error = 11.6% with a combination of seven variables) and group 1 v group 2 model variables as means and standard deviations for player groupings.

  7. Most added time in the Premier League 2023-2024, by club

    • statista.com
    Updated Oct 18, 2023
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    Statista (2023). Most added time in the Premier League 2023-2024, by club [Dataset]. https://www.statista.com/statistics/1418271/premier-league-added-time-by-club/
    Explore at:
    Dataset updated
    Oct 18, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom (England)
    Description

    In 2023/24, Aston Villa had more time added on to matches than any other Premier League club, with an average of 14 minutes and 33 seconds being added on to games. Meanwhile, Luton Town typically only had around eight minutes and 26 seconds of added time.

  8. VAR decisions in the Premier League 2023-2024, by club

    • statista.com
    Updated Mar 25, 2024
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    Statista (2024). VAR decisions in the Premier League 2023-2024, by club [Dataset]. https://www.statista.com/statistics/1458004/var-decisions-premier-league/
    Explore at:
    Dataset updated
    Mar 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom (England)
    Description

    As of March 17, 2024, Nottingham Forest had the highest net VAR decision score in the Premier League with four. Meanwhile, three clubs had a net VAR decision score of -3: Liverpool, Sheffield United, and Wolverhampton Wanderers.

  9. h

    Data from: indian-premier-league

    • huggingface.co
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    DeepKlarity, indian-premier-league [Dataset]. https://huggingface.co/datasets/deepklarity/indian-premier-league
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset authored and provided by
    DeepKlarity
    License

    https://choosealicense.com/licenses/cc/https://choosealicense.com/licenses/cc/

    Area covered
    India
    Description

    Indian Premier League Dataset

    This dataset contains info on all of the IPL(Indian Premier League) cricket matches. Ball-by-Ball level info and scorecard info to be added soon. The dataset was scraped in July-2022.

      Mantainers:
    

    Somya Gautam Kondrolla Dinesh Reddy Keshaw Soni

  10. w

    Books series that contain The ups and downs of the Premier League

    • workwithdata.com
    Updated Jul 3, 2024
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    Work With Data (2024). Books series that contain The ups and downs of the Premier League [Dataset]. https://www.workwithdata.com/datasets/book-series?f=1&fcol0=book&fop0=%3D&fval0=The+ups+and+downs+of+the+Premier+League
    Explore at:
    Dataset updated
    Jul 3, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about book series and is filtered where the books is The ups and downs of the Premier League, featuring 10 columns including authors, average publication date, book publishers, book series, and books. The preview is ordered by number of books (descending).

  11. Fantasy Premier League 2019/20 Player Data

    • kaggle.com
    zip
    Updated Aug 19, 2020
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    Plavak Das (2020). Fantasy Premier League 2019/20 Player Data [Dataset]. https://www.kaggle.com/plavak10/fpl-1920-player-data
    Explore at:
    zip(33703 bytes)Available download formats
    Dataset updated
    Aug 19, 2020
    Authors
    Plavak Das
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset

    This dataset was created by Plavak Das

    Released under CC0: Public Domain

    Contents

  12. 2024-2025 Spanish Ladies Premier League

    • actiongameplay.icu
    Updated Mar 15, 2025
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    FootballAnt (2025). 2024-2025 Spanish Ladies Premier League [Dataset]. https://www.actiongameplay.icu/liga%20mx
    Explore at:
    Dataset updated
    Mar 15, 2025
    Dataset provided by
    Football Ant
    Authors
    FootballAnt
    License

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

    Description

    2024-2025 Spanish Ladies Premier League schedule information, for more league information please click: https://www.footballant.com/football-data/league/1186

  13. Business of the English Premier League 2021-22 - Property Profile,...

    • store.globaldata.com
    Updated Sep 30, 2021
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    GlobalData UK Ltd. (2021). Business of the English Premier League 2021-22 - Property Profile, Sponsorship and Media Landscape [Dataset]. https://store.globaldata.com/report/business-of-the-english-premier-league-2021-22-property-profile-sponsorship-and-media-landscape/
    Explore at:
    Dataset updated
    Sep 30, 2021
    Dataset provided by
    GlobalDatahttps://www.globaldata.com/
    Authors
    GlobalData UK Ltd.
    License

    https://www.globaldata.com/privacy-policy/https://www.globaldata.com/privacy-policy/

    Time period covered
    2021 - 2025
    Area covered
    Global
    Description

    The Premier League agrees to roll over its existing domestic broadcast rights agreements for the 2022 to 2025 rights cycle, avoiding what was anticipated to be a further depreciation in the value of the league's domestic media rights. Read More

  14. La Liga Soccer League - Business Analysis, Sponsorship Portfolio and...

    • store.globaldata.com
    Updated Dec 31, 2020
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    GlobalData UK Ltd. (2020). La Liga Soccer League - Business Analysis, Sponsorship Portfolio and response to COVID-19 [Dataset]. https://store.globaldata.com/report/la-liga-soccer-league-business-analysis-sponsorship-portfolio-and-response-to-covid-19/
    Explore at:
    Dataset updated
    Dec 31, 2020
    Dataset provided by
    GlobalDatahttps://www.globaldata.com/
    Authors
    GlobalData UK Ltd.
    License

    https://www.globaldata.com/privacy-policy/https://www.globaldata.com/privacy-policy/

    Time period covered
    2020 - 2024
    Area covered
    Europe
    Description

    La Liga, Spain’s top soccer competition, is widely considered the second biggest domestic soccer property in the world behind the Premier League, with its top sides Barcelona and Real Madrid the most followed and supported around the world. Having been able to ensure a completed season, a worst case scenario of a $1.16 billion loss has been avoided, but challenges still remain in ensuring La Liga’s product remains competitive and desirable to an international audience Read More

  15. Premier League 2021-2022 Match Data

    • kaggle.com
    zip
    Updated Oct 21, 2021
    + more versions
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    Dean Patel (2021). Premier League 2021-2022 Match Data [Dataset]. https://www.kaggle.com/datasets/deanpatel/premier-league-20212022-match-data
    Explore at:
    zip(16635 bytes)Available download formats
    Dataset updated
    Oct 21, 2021
    Authors
    Dean Patel
    Description

    Dataset

    This dataset was created by Dean Patel

    Contents

  16. Interest in Premier League clubs in England 2018

    • statista.com
    Updated Feb 23, 2022
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    Statista (2022). Interest in Premier League clubs in England 2018 [Dataset]. https://www.statista.com/forecasts/890403/interest-in-premier-league-clubs-in-england
    Explore at:
    Dataset updated
    Feb 23, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 22, 2018 - Jun 30, 2018
    Area covered
    United Kingdom (England)
    Description

    The displayed data on the interest in Premier League clubs shows results of the Statista European Football Benchmark conducted in England in 2018. Some 26 percent of respondents stated that they are interested in Liverpool F.C..

  17. Player injuries in the Premier League 2023-2024, by month

    • statista.com
    Updated Nov 25, 2024
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    Statista (2024). Player injuries in the Premier League 2023-2024, by month [Dataset]. https://www.statista.com/statistics/1498333/premier-league-injuries-by-month/
    Explore at:
    Dataset updated
    Nov 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom (England)
    Description

    In the 2023/24 season, the opening month of the Premier League saw the most player injuries, with a total of 100 across all clubs. Meanwhile, peaks were also seen in November and December 2023.

  18. IPL Players 2017

    • kaggle.com
    zip
    Updated Jan 17, 2018
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    zark muckerberg (2018). IPL Players 2017 [Dataset]. https://www.kaggle.com/datasets/akshay35c/ipl-players-2017
    Explore at:
    zip(552561 bytes)Available download formats
    Dataset updated
    Jan 17, 2018
    Authors
    zark muckerberg
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset

    This dataset was created by zark muckerberg

    Released under CC0: Public Domain

    Contents

  19. n

    Data from: Indian Premier League

    • wikipedia.tr-tr.nina.az
    Updated Jul 10, 2024
    + more versions
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    (2024). Indian Premier League [Dataset]. https://www.wikipedia.tr-tr.nina.az/Indian_Premier_League.html
    Explore at:
    Dataset updated
    Jul 10, 2024
    License

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

    Area covered
    Hindistan
    Description

    Indian Premier League Hindistan Premier Ligi veya sponsorluk anlaşması gereği TATA IPL Hindistan ın en üst düzey e

  20. Match statistics’ statistical summary.

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 20, 2023
    + more versions
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    Calvin C. K. Yeung; Rory Bunker; Keisuke Fujii (2023). Match statistics’ statistical summary. [Dataset]. http://doi.org/10.1371/journal.pone.0284318.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 20, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Calvin C. K. Yeung; Rory Bunker; Keisuke Fujii
    License

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

    Description

    While forecasting football match results has long been a popular topic, a practical model for football participants, such as coaches and players, has not been considered in great detail. In this study, we propose a generalized and interpretable machine learning model framework that only requires coaches’ decisions and player quality features for forecasting. By further allowing the model to embed historical match statistics, features that consist of significant information, during the training process the model was practical and achieved both high performance and interpretability. Using five years of data (over 1,700 matches) from the English Premier League, our results show that our model was able to achieve high performance with an F1-score of 0.47, compared to the baseline betting odds prediction, which had an F1-score of 0.39. Moreover, our framework allows football teams to adapt for tactical decision-making, strength and weakness identification, formation and player selection, and transfer target validation. The framework in this study would have proven the feasibility of building a practical match result forecast framework and may serve to inspire future studies.

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Jaseem Mohammed (2020). English Premier League 19-20 Player Stats data [Dataset]. https://www.kaggle.com/machinemind/english-premier-league-1920-player-stats-data
Organization logo

English Premier League 19-20 Player Stats data

Contains data of players from all the teams excluding the relegated ones.

Explore at:
zip(16598 bytes)Available download formats
Dataset updated
Sep 7, 2020
Authors
Jaseem Mohammed
Description

Dataset

This dataset was created by Jaseem Mohammed

Contents

It contains the following files:

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