⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.

• UpdatedMar 13, 2025
• Python

A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat

• UpdatedFeb 14, 2025
• R

An asynchronous Python package forhttps://understat.com/.

• UpdatedJul 29, 2024
• Python

fetch understat data

• UpdatedSep 2, 2021
• R

Create a database of ⚽️ data from understat.com

• UpdatedOct 19, 2021
• Python

Fantasy Premier League prediction using Machine Learning

• UpdatedMar 19, 2021
• Python

UnderStat Web Scrapper

• UpdatedSep 4, 2022
• Jupyter Notebook

Python package for get data ofwww.understat.com

• UpdatedMay 25, 2023
• Python

Mo Salah had an exceptional season winning the PFA awards, Golden boot and finished with 13 assists making him assist king of 2021-22 season. This is his shotmap

• UpdatedJun 19, 2022
• Jupyter Notebook

Scrapping Understat for player, match, team and league data using BeautifulSoup

• UpdatedJun 15, 2022
• Jupyter Notebook

Basic comparison pizza chart. To compare two players The PFA released their Team of the season for the 2021-22 Premier League season. Thiago Alcântara of Liverpool FC was included in the midfield three. Many fans questioned the PFA's decision for the inclusion ahead of the likes of Rodri of Manchester City and Declan Rice of Westham United. Let…

• UpdatedJun 11, 2022
• Jupyter Notebook

A project to determine the centrality and closeness of a shot to goal.

• UpdatedNov 8, 2021
• R

Compiler and fetcher for data from Premier League API. Also used as a personal self-study to analyze and model performance metrics to maximize returns in a returns-based game called Fantasy Premier League (FPL).

• UpdatedJan 31, 2025
• Python

A Fantasy Premier League (FPL) dashboard which allows users to plot several key performance metrics against each other which allows users to obtain key insights on the statistical indicators of top players in the Premier League (EPL).

• UpdatedNov 28, 2020
• Jupyter Notebook

Integrating FPL, Transfermarkt, and Understat data, our strategy optimizes squad selection. This approach, leveraging market values and detailed player statistics, ensures both financial prudence and on-field performance. Strategic acquisitions align with set rules and budget constraints, emphasizing value-driven choices for a robust squad

• UpdatedFeb 4, 2024
• Jupyter Notebook

An R package for plotting understat data; an xG chart and a shot map.

• UpdatedMar 7, 2025
• R

A Hypothesis Testing Analysis of FC Barcelona's Season

• UpdatedMay 26, 2024
• Jupyter Notebook

A cutting-edge machine learning platform that transforms soccer analytics through intelligent data processing, player recommendations, and performance insights.

• UpdatedMar 17, 2025