Metadata-Version: 1.1
Name: footballdata
Version: 0.3.0
Summary: A collection of wrappers over football (soccer) 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.
Home-page: https://github.com/skagr/footballdata
Author: Skag Rijsdijk
Author-email: skag.rijsdijk@gmail.com
License: MIT
Description: Football Data Analysis Toolkit
        ==============================
        
        .. image:: https://img.shields.io/pypi/v/footballdata.svg
            :target: https://pypi.python.org/pypi/footballdata
            :alt: Latest PyPI version
        
        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.
        
        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 <http://pandas.pydata.org/>`_
        - `Requests <http://docs.python-requests.org/en/master/>`_
        
        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 3.3-3.6
        
        Licence
        -------
        
        MIT
        
Keywords: football,soccer,metrics,sports,statistics
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Software Development :: Libraries
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
