There are 6 repositories under soccer-data topic.
📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
Convert soccer event stream data to SPADL and value player actions using VAEP or xT
⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.
A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
A curated list of football analytics awesome resources, articles, books and more!
A Comprehensive Database on the Premier League and the English Football League (1888-2022)
football (soccer) datasets
The Open-Source Live Football Standing
It's a crawler for statistics of corners and goals for the future games and a bot for Telegram to send the statistics.
Flatiron School Capstone project. Trying to find out how well players' on-field performance metrics can be used to predict their transfer values.
Create a database of ⚽️ data from understat.com
Live Score Client for api-football.com
A bot that provides soccer predictions using Poisson regression
This is a web scraper that helps to scrape football data from FBRef.com. It can scrape data from the top 5 Domestic League games. It can be easily edited to scrape data from other leagues as well as from other competitions such as Champions League, Domestic Cup games, friendlies, etc.
Mainly football leagues database of 2023/2024 season in JSON format
wyscoutapi is an extremely basic API client for the Wyscout API (v2 & v3) for Python
⚽️💥⚽️Live soccer scores, fixtures, and results. It uses API to retrieve up-to-date information from a reliable source, and presents it in an easy-to-use interface. Whether you're a soccer fan or just need to stay informed for work or research, this project is a great tool for keeping track of the latest scores, fixtures, and results.
Scraping and updating of data from the championships that Brazilian soccer teams participate in
StrangeR things: Visualizing Soccer Data with R… on a Soccer Pitch? How to analyze, visualize and report soccer data and strategies on a soccer pitch with the "ggsoccer" package
This project aims to rate football players using data and statistics recorded from the last match they participated in. Much of the code included in this project can be used for other purposes when working with the Wyscout data set. For example minutes_played.py, fitting_functions.py and KPI_functions.py.
Predicting EPL results improving the betting odds.
Home of football data
soccer_data_crawling
Provide some examples for creating a data pipeline with the {googledrive} package and Github Actions
The top teams in the English Premier League in the 2021-22 season, Manchester City and Liverpool FC, have gone ahead during this off season to add classic NO.9s to their already stellar attack options. Let's see how these two player stack up against each order using radar plot. Data source is FBref via Statsbomb.
This is a computer vision project that utilizes object detection algorithms to analyze football matches videos by finding the position of players, ball and referees on the football pitch and finding out to which team each player belongs.
This repository will contain all sorts of basic visualisation to step into the world of football analytics
FBref player stats scraper
This project utilizes machine learning regression algorithms to predict the outcomes and standings of the current English Premier League (EPL) season. By analyzing historical data and leveraging various regression models, it offers insights into team performance and aims to provide a glimpse into how the EPL season may unfold.