Metadata-Version: 2.1
Name: rugbypy
Version: 1.0.0
Summary: Repository for rugby data analytics
Home-page: https://github.com/seanyboi/rugbypy
Author: seanyboi
Author-email: oconnorjamessean@gmail.com
License: Apache Software License 2.0
Description: rugbypy
        ================
        
        <!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
        
        `rugbypy` is a Python package that aims to make rugby data more
        available to aid in the development of rugby analytics. Currently we
        only have 2023 data available with previous years coming soon!
        
        ![PyPI - Downloads](https://img.shields.io/pypi/dm/rugbypy)
        
        ## Requirements
        
        python version 3.8
        
        ## Install
        
        ``` sh
        pip install rugbypy
        ```
        
        ## How to use
        
        ### Match Stats
        
        You can fetch all the matches that occured on a particular date with:
        
        ``` python
        matches = fetch_matches(date="20230101")
        matches
        ```
        
            Fetching matches on date:20230101...
        
        <div>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>match_id</th>
              <th>competition_id</th>
              <th>home_team_id</th>
              <th>away_team_id</th>
              <th>date</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>595735</td>
              <td>267979</td>
              <td>25907</td>
              <td>25901</td>
              <td>20230101</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        Then using that match id you can feed it into the match details
        function:
        
        ``` python
        match_details = fetch_match_details(match_id="595735")
        match_details
        ```
        
            Fetching match details for match_id:595735...
        
        <div>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>match_id</th>
              <th>date</th>
              <th>competition_id</th>
              <th>competition</th>
              <th>venue_id</th>
              <th>venue</th>
              <th>city_played</th>
              <th>home_team</th>
              <th>away_team</th>
              <th>home_team_id</th>
              <th>away_team_id</th>
              <th>completed</th>
              <th>is_tournament</th>
              <th>played_on_grass</th>
              <th>attendance</th>
              <th>home_team_form</th>
              <th>away_team_form</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>595735</td>
              <td>20230101</td>
              <td>267979</td>
              <td>Premiership Rugby</td>
              <td>26070</td>
              <td>cinch Stadium at Franklin's Gardens</td>
              <td>Northampton</td>
              <td>Northampton Saints</td>
              <td>Harlequins</td>
              <td>25907</td>
              <td>25901</td>
              <td>True</td>
              <td>True</td>
              <td>True</td>
              <td>None</td>
              <td>LLWWL</td>
              <td>WLWLL</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        ### Team Stats
        
        You can then fetch the team stats for a particular team on a particular
        date with:
        
        ``` python
        team_stats = fetch_team_stats(team_id="25901", date="20230108")
        team_stats
        ```
        
            Fetching team stats for team_id:25901 on date:20230108...
        
        <div>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>team</th>
              <th>game_date</th>
              <th>team_id</th>
              <th>team_vs</th>
              <th>team_vs_id</th>
              <th>clean_breaks</th>
              <th>conversion_goals</th>
              <th>defenders_beaten</th>
              <th>kick_percent_success</th>
              <th>kicks</th>
              <th>...</th>
              <th>scrums_total</th>
              <th>scrums_won</th>
              <th>tackles</th>
              <th>territory</th>
              <th>total_free_kicks_conceded</th>
              <th>total_lineouts</th>
              <th>tries</th>
              <th>turnover_knock_on</th>
              <th>turnovers_conceded</th>
              <th>yellow_cards</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>Harlequins</td>
              <td>20230108</td>
              <td>25901</td>
              <td>Sale Sharks</td>
              <td>25908</td>
              <td>3.0</td>
              <td>0.0</td>
              <td>24.0</td>
              <td>0.5</td>
              <td>0.0</td>
              <td>...</td>
              <td>7.0</td>
              <td>5.0</td>
              <td>125.0</td>
              <td>0.41</td>
              <td>0.0</td>
              <td>11.0</td>
              <td>2.0</td>
              <td>8.0</td>
              <td>17.0</td>
              <td>0.0</td>
            </tr>
          </tbody>
        </table>
        <p>1 rows × 40 columns</p>
        </div>
        
        ### Player Stats
        
        We have the ability to fetch player stats for all the games they have
        bene involved in. We firstly identify the \`player_id\`\` of a player by
        searching our player manifest file.
        
        ``` python
        player_manifest = fetch_all_players()
        player_manifest.head()
        ```
        
        <div>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>player_id</th>
              <th>player_name</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>246815</td>
              <td>Will Edwards</td>
            </tr>
            <tr>
              <th>1</th>
              <td>158708</td>
              <td>Tommaso Allan</td>
            </tr>
            <tr>
              <th>2</th>
              <td>299436</td>
              <td>Oscar Beard</td>
            </tr>
            <tr>
              <th>3</th>
              <td>299031</td>
              <td>Fin Baxter</td>
            </tr>
            <tr>
              <th>4</th>
              <td>298485</td>
              <td>Jordan Els</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        Or we can search for a certain player through our similarity tool:
        
        ``` python
        individual_player = fetch_player(name="johnny sexton")
        individual_player
        ```
        
        <div>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>player_id</th>
              <th>player_name</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>267</th>
              <td>149315</td>
              <td>Anthony Watson</td>
            </tr>
            <tr>
              <th>294</th>
              <td>16004</td>
              <td>Johnny Sexton</td>
            </tr>
            <tr>
              <th>796</th>
              <td>291349</td>
              <td>Ayden Johnstone</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        We can also fetch the player stats for any player using their
        `player_ids`. In this example we fetch Johnny Sextons player stats:
        
        ``` python
        player_stats = fetch_player_stats(player_id="16004")
        player_stats
        ```
        
            Fetching all player stats for player_id:16004...
        
        <div>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>player_id</th>
              <th>game_date</th>
              <th>name</th>
              <th>team</th>
              <th>team_id</th>
              <th>competition_id</th>
              <th>competition</th>
              <th>team_vs</th>
              <th>team_vs_id</th>
              <th>weight</th>
              <th>...</th>
              <th>rucks_won</th>
              <th>runs</th>
              <th>tackles</th>
              <th>total_free_kicks_conceded</th>
              <th>total_lineouts</th>
              <th>tries</th>
              <th>try_assists</th>
              <th>turnover_knock_on</th>
              <th>turnovers_conceded</th>
              <th>yellow_cards</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>0</th>
              <td>16004</td>
              <td>20230204</td>
              <td>Johnny Sexton</td>
              <td>Ireland</td>
              <td>3</td>
              <td>180659</td>
              <td>Six Nations Championship</td>
              <td>4</td>
              <td>Wales</td>
              <td>92.0</td>
              <td>...</td>
              <td>3.0</td>
              <td>8.0</td>
              <td>7.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>1.0</td>
              <td>0.0</td>
            </tr>
            <tr>
              <th>0</th>
              <td>16004</td>
              <td>20230211</td>
              <td>Johnny Sexton</td>
              <td>Ireland</td>
              <td>3</td>
              <td>180659</td>
              <td>Six Nations Championship</td>
              <td>9</td>
              <td>France</td>
              <td>92.0</td>
              <td>...</td>
              <td>1.0</td>
              <td>5.0</td>
              <td>3.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
            </tr>
            <tr>
              <th>0</th>
              <td>16004</td>
              <td>20230312</td>
              <td>Johnny Sexton</td>
              <td>Ireland</td>
              <td>3</td>
              <td>180659</td>
              <td>Six Nations Championship</td>
              <td>2</td>
              <td>Scotland</td>
              <td>92.0</td>
              <td>...</td>
              <td>2.0</td>
              <td>5.0</td>
              <td>9.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>2.0</td>
              <td>0.0</td>
            </tr>
            <tr>
              <th>0</th>
              <td>16004</td>
              <td>20230318</td>
              <td>Johnny Sexton</td>
              <td>Ireland</td>
              <td>3</td>
              <td>180659</td>
              <td>Six Nations Championship</td>
              <td>1</td>
              <td>England</td>
              <td>92.0</td>
              <td>...</td>
              <td>6.0</td>
              <td>9.0</td>
              <td>5.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>1.0</td>
              <td>2.0</td>
              <td>0.0</td>
            </tr>
            <tr>
              <th>0</th>
              <td>16004</td>
              <td>20230909</td>
              <td>Johnny Sexton</td>
              <td>Ireland</td>
              <td>3</td>
              <td>164205</td>
              <td>Rugby World Cup</td>
              <td>12</td>
              <td>Romania</td>
              <td>92.0</td>
              <td>...</td>
              <td>0.0</td>
              <td>5.0</td>
              <td>4.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>2.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
            </tr>
            <tr>
              <th>0</th>
              <td>16004</td>
              <td>20230916</td>
              <td>Johnny Sexton</td>
              <td>Ireland</td>
              <td>3</td>
              <td>164205</td>
              <td>Rugby World Cup</td>
              <td>16</td>
              <td>Tonga</td>
              <td>92.0</td>
              <td>...</td>
              <td>1.0</td>
              <td>1.0</td>
              <td>2.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>1.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
              <td>0.0</td>
            </tr>
          </tbody>
        </table>
        <p>6 rows × 40 columns</p>
        </div>
        
Keywords: nbdev jupyter notebook python
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: dev
