Python package for scraping soccer data from a variety of sources

“Safest, Fastest, Easiest, and Most advanced” Python HTTP Client. Production Ready! Drop-in replacement for Requests. HTTP/1.1, HTTP/2, and HTTP/3 supported.

Make awesome display tables using Python.

Machine Learning Engineering Open Book

Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.

Constraint Solving Problem resolver for Python

Measuring soccer player's creativity

PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis

This football analytics package is based on a series of Towards Data Science articles by Ofir Magdaci. Using this package, you can to download pre-trained models or run and create your own.

U.S. Soccer Federation 2023 MIT Sloan Sports Analytics Conference Graph Neural Network soccer research repository

Book about interpretable machine learning

Creates dynamic html report from jupyter notebook.

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models l…

Cool experiments at the intersection of Computer Vision and Sports ⚽🏃

most pretty & lovely tables with matplotlib

Collection of tools and scripts for analysis and visualisation of football data.

scrape physical data for Bundesliga from https://www.sportschau.de/fussball/bundesliga

get football tracking data from TV broadcast using yoloV5, Deep sort

A tool for refurbishing and modernizing Python codebases

Library from http:https://pena.lt/y/blog for modelling and working with football (soccer) data

Getting started with soccer analytics

a shot at coordinating open source football analytics builders to work towards common standards with interoperability as the goal

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

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

An extension of LightGBM to probabilistic modelling

Distributional Gradient Boosting Machines

An extension of XGBoost to probabilistic modelling

jekyll extensions for the blogging scholar

Generate one page per yaml record in Jekyll sites.