whoscraped 0.1.0

Scrape football data from WhoScored

WhoScraped

Library for scraping football data from WhoScored matches.

Installation

To install this library, use:

pip install whoscraped

To upgrade the library, use:

pip install --upgrade whoscraped

Prerequisites

1. Python 3.6 or higher
2. Google Chrome browser
3. Chromedriver installed and added to your system's PATH

How to Use It

The library provides the following functions:

1. Get data from the match URL in JSON format:

from whoscraped import get_match_data

match_url = "https://www.whoscored.com/Matches/1699239/Live/International-FIFA-World-Cup-2022-Argentina-France"
match_data = get_match_data(match_url)

This function retrieves match data from the specified URL. The data is returned as a Python dictionary in JSON format.

2. Get all passes from both teams from a match URL or match json data:

from whoscraped import get_match_passes

match_url = "https://www.whoscored.com/Matches/1699239/Live/International-FIFA-World-Cup-2022-Argentina-France"
passes_df = get_match_passes(match_url)

or

from whoscraped import get_match_data, get_match_passes

match_url = "https://www.whoscored.com/Matches/1699239/Live/International-FIFA-World-Cup-2022-Argentina-France"
data = get_match_data(url)
passes_df = get_match_passes(data)

This function gets all pass events from the specified match URL or json object with match data and returns a Pandas DataFrame containing the pass information.

3. Get all stats from both teams from a match URL or match json data:

from whoscraped import get_team_stats

match_url = "https://www.whoscored.com/Matches/1699239/Live/International-FIFA-World-Cup-2022-Argentina-France"
stats_df = get_team_stats(match_url)

or

from whoscraped import get_match_data, get_team_stats

match_url = "https://www.whoscored.com/Matches/1699239/Live/International-FIFA-World-Cup-2022-Argentina-France"
data = get_match_data(url)
stats_df = get_team_stats(data)

This function gets all the home and away team stats from the specified match URL or json object with match data and returns a Pandas DataFrame containing the information.

Handling Errors

If you encounter an error, such as CantGetMatchData, ensure that the match URL is correct and that the WhoScored page has the necessary data.

Contributing

If you would like to contribute to this project, please fork the repository and submit a pull request. Ensure that your code passes all tests and adheres to the project's coding standards.