6 datasets found
  1. FPL (Fantasy Premier League) API 23-24

    • kaggle.com
    Updated May 28, 2024
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    Plavak Das (2024). FPL (Fantasy Premier League) API 23-24 [Dataset]. https://www.kaggle.com/datasets/plavak10/fpl-fantasy-premier-league-api-23-24/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 28, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Plavak Das
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Fantasy Premier League or popularly known as FPL in short, is the most popular fantasy game played worldwide. It is the official fantasy game of the English Premier League and runs throughout the duration of the league itself. The number of registered users keep on growing season by season and the FPL community or so we call it, has grown tremendously over the recent years. To keep it short, FPL can be called an opportuniy - an opportunity to learn tactics; to make friends and the accompanied banters, 'mini-leagues'; to add an extra spice to watching matches etc. and the list can go on

    You can find all the details at - FPL Official Site

    There are basically 3 datasets: - Gameweeks.csv : Contains all the 38 Gameweeks' data - Players.csv : Contains all players' data - Teams.csv : Contains all clubs' data

    Basically the idea behind this datasets is to perform an extensive EDA

  2. Premier League Dataset (2000-2019)

    • kaggle.com
    Updated Sep 8, 2020
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    Prateek Agrawal (2020). Premier League Dataset (2000-2019) [Dataset]. https://www.kaggle.com/prateekagrawal1405/premier-league-score-20002019/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 8, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Prateek Agrawal
    Description

    Context

    I am a machine learning enthusiast who tries to learn something new everyday. I don't know why but I searched for a dataset of Premiere League Scores and couldn't find what I wanted so I created this using web scraping. I really look forward to people using this . Thank You

    Content

    The following dataset consists of the final score tables for Premiere League from the year 2000 to 2019.

    DOWNLOAD API

    kaggle datasets download -d prateekagrawal1405/premier-league-score-20002019

  3. e

    Caribbean Premier League | See Full Import/Export Data | Eximpedia

    • eximpedia.app
    Updated Jan 22, 2025
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    Seair Exim (2025). Caribbean Premier League | See Full Import/Export Data | Eximpedia [Dataset]. https://www.eximpedia.app/
    Explore at:
    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset updated
    Jan 22, 2025
    Dataset provided by
    Eximpedia Export Import Trade Data
    Eximpedia PTE LTD
    Authors
    Seair Exim
    Area covered
    Mauritius, Djibouti, Vietnam, El Salvador, Togo, Zimbabwe, Tanzania, Barbados, Grenada, Ascension and Tristan da Cunha, Caribbean
    Description

    Caribbean Premier League Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

  4. Nepal Premiere League (NPL) Dataset API

    • kaggle.com
    Updated Feb 10, 2025
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    Subesh Yadav (2025). Nepal Premiere League (NPL) Dataset API [Dataset]. https://www.kaggle.com/datasets/subeshyadav/nepal-premiere-league-npl-dataset-api/versions/3
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 10, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Subesh Yadav
    License

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

    Area covered
    Nepal
    Description

    Dataset

    This dataset was created by Subesh Yadav

    Released under MIT

    Contents

  5. d

    Odds & Betting Data | Global Coverage | Soccer, Tennis, Basketball |...

    • datarade.ai
    .bin
    Updated Apr 11, 2025
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    VOdds (2025). Odds & Betting Data | Global Coverage | Soccer, Tennis, Basketball | Historical Data [Dataset]. https://datarade.ai/data-products/odds-betting-data-global-coverage-soccer-tennis-baske-vodds
    Explore at:
    .binAvailable download formats
    Dataset updated
    Apr 11, 2025
    Dataset authored and provided by
    VOdds
    Area covered
    Slovenia, Senegal, Mali, Jersey, Zimbabwe, Guadeloupe, Malawi, Svalbard and Jan Mayen, Guinea-Bissau, Northern Mariana Islands
    Description

    The UNITY Odds Feed API – Historical Data Access offers a rich dataset of sports betting odds, covering a global array of leagues and events. This API enables users to retrieve detailed historical odds for both pre-match and live/in-play markets. It includes specific betting metrics such as Asian Handicap, Totals (Over/Under), Corners, and Cards, with data sourced from numerous major Asian sportsbooks and exchanges.

    This historical feed is particularly well-suited for:

    Data scientists and analysts building predictive models

    Sportsbooks improving odds-making strategies

    Media platforms generating betting insights

    Researchers analyzing market efficiency and odds movement

    Key Features: Pre-match and In-play Odds: Track how betting lines moved before and during events.

    Multi-Sport Coverage: Includes football (soccer), basketball, and tennis—spanning top leagues like the Premier League, NBA, and Grand Slam tournaments.

    Market Breadth: Extensive odds data for niche markets such as corners and cards.

    Bookmaker Diversity: Historical odds from a wide range of Asian bookmakers and betting exchanges with low spreads and back/lay functionality.

    Structured & Filterable: Access raw or formatted data by sport, league, event, or market.

    This API delivers the tools needed to extract meaningful insights from betting markets—whether you're building advanced algorithms, enhancing app features, or deep-diving into betting behavior trends.

  6. o

    History of the SuperBowl

    • public.opendatasoft.com
    • data.smartidf.services
    • +6more
    csv, excel, geojson +1
    Updated Feb 1, 2018
    + more versions
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    (2018). History of the SuperBowl [Dataset]. https://public.opendatasoft.com/explore/dataset/super-bowl/
    Explore at:
    excel, csv, geojson, jsonAvailable download formats
    Dataset updated
    Feb 1, 2018
    License

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

    Description

    The Super Bowl is an annual American football game that determines the champion of the National Football League (NFL). The game culminates a season that begins in the previous calendar year, and is the conclusion of the NFL playoffs. The contest is held in an American city, chosen three to four years beforehand, usually at warm-weather sites or domed stadiums. Since January 1971, the winner of the American Football Conference (AFC) Championship Game has faced the winner of the National Football Conference (NFC) Championship Game in the culmination of the NFL playoffs. Before the 1970 merger between the American Football League (AFL) and the National Football League (NFL), the two leagues met in four such contests. The first two were known as the "AFL–NFL World Championship Game". Super Bowl III in January 1969 was the first such game that carried the "Super Bowl" moniker, the names "Super Bowl I" and "Super Bowl II" were retroactively applied to the first two games.[3] The NFC/NFL leads in Super Bowl wins with 26, while the AFC/AFL has won 24. Nineteen different franchises, including teams that relocated to another city, have won the Super Bowl.-Wikipedia: List of Super Bowl Champions

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Plavak Das (2024). FPL (Fantasy Premier League) API 23-24 [Dataset]. https://www.kaggle.com/datasets/plavak10/fpl-fantasy-premier-league-api-23-24/code
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FPL (Fantasy Premier League) API 23-24

Fantasy Premier League API Data - Players/Gameweeks/Teams

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 28, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Plavak Das
License

Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically

Description

Fantasy Premier League or popularly known as FPL in short, is the most popular fantasy game played worldwide. It is the official fantasy game of the English Premier League and runs throughout the duration of the league itself. The number of registered users keep on growing season by season and the FPL community or so we call it, has grown tremendously over the recent years. To keep it short, FPL can be called an opportuniy - an opportunity to learn tactics; to make friends and the accompanied banters, 'mini-leagues'; to add an extra spice to watching matches etc. and the list can go on

You can find all the details at - FPL Official Site

There are basically 3 datasets: - Gameweeks.csv : Contains all the 38 Gameweeks' data - Players.csv : Contains all players' data - Teams.csv : Contains all clubs' data

Basically the idea behind this datasets is to perform an extensive EDA

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