https://github.com/skagr/footballdata

A collection of wrappers over football data from various websites / APIs.
https://github.com/skagr/footballdata

data-science dataset football pandas python soccer

Last synced: 10 months ago
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A collection of wrappers over football data from various websites / APIs.

• Host: GitHub
• URL: https://github.com/skagr/footballdata
• Owner: skagr
• License: mit
• Created: 2017-06-16T15:26:09.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2018-06-14T16:29:22.000Z (about 8 years ago)
• Last Synced: 2025-07-15T07:33:30.780Z (12 months ago)
• Topics: data-science, dataset, football, pandas, python, soccer
• Language: Jupyter Notebook
• Homepage:
• Size: 4.66 MB
• Stars: 37
• Watchers: 6
• Forks: 7
• Open Issues: 6
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

README

          
Football Data

=============

.. image:: https://img.shields.io/pypi/v/footballdata.svg

    :target: https://pypi.python.org/pypi/footballdata

    :alt: Latest PyPI version

.. image:: https://travis-ci.org/skagr/footballdata.png

   :target: https://travis-ci.org/skagr/footballdata

   :alt: Latest Travis CI build status

A collection of wrappers over football [*]_ data from various websites / APIs. You get: Pandas dataframes with sensible, matching column names and identifiers across datasets. Data is downloaded when needed and cached locally. Example Jupyter Notebooks are in the Github repo.

.. [*] Soccer, if you're a heathen

Data sources:

-------------

fivethirtyeight.com

~~~~~~~~~~~~~~~~~~~

(https://projects.fivethirtyeight.com/soccer-predictions)

Season 2016-17 predictions and results for the top European and American leagues.

* Data no longer available on fivethirtyeight.com, I've `added it to the repository `_

football-data.co.uk

~~~~~~~~~~~~~~~~~~~

(http://www.football-data.co.uk/)

Historical results, betting odds and match statistics for English, Scottish, German, Italian, Spanish, French, Dutch, Belgian, Portuguese, Turkish and Greek leagues, including a number of lower divisions. Level of detail depends on league.

clubelo.com

~~~~~~~~~~~

(http://clubelo.com)

First team relative strengths, for all (?) European leagues. Recalculated after every round, includes history.

Roadmap:

--------

Add player stats, transfers, injuries and suspensions.

Installation

------------

.. code:: bash

    $ pip install footballdata

Dependencies

~~~~~~~~~~~~

- `Numpy `_

- `Pandas `_

- `Requests `_

- `Unidecode `_

Usage

-----

.. code:: python

    import footballdata as foo

    # Create class instances

    five38 = foo.FiveThirtyEight()

    elo = foo.ClubElo()

    mhist = foo.MatchHistory('ENG-Premier League', '2016-17')

    # Create dataframes

    matches = five38.read_games()

    forecasts = five38.forecasts()

    current_elo = elo.read_by_date()

    team_elo_history = elo.read_team_history('Barcelona')

    epl_2016 = mhist.read_games()

See the Jupyter Notebooks here for more elaborate examples: https://github.com/skagr/footballdata/tree/master/notebooks

Compatibility

-------------

Tested against Python 2.7 and 3.4-3.6

Licence

-------

MIT