Software

SoccerAction

SoccerAction is a Python package for objectively quantifying the impact of the individual actions performed by soccer players using event stream data. It contains converters for the event streams of various data providers to our SPADL format and an implementation of three frameworks to value the contributions of soccer players: VAEP, Atomic-VAEP and xT.

Code PyPI Documentation Research

SoccerMix

A Python implementation of a soft clustering technique based on mixture models to decompose soccer event stream data into a number of prototypical actions of a specific type, location, and direction. This is used to analyze playing style.

Code Research

AMIE

Patients with sports-related injuries need to learn to perform rehabilitative exercises with correct movement patterns. Unfortunately, the feedback a physiotherapist can provide is limited by the visitation frequency of the patient. AMIE is a machine learning pipeline that detects the exercise being performed, the exercise's correctness, and if applicable, the mistake that was made using a Microsoft Kinect camera.

Code Research

Soccer xG

A Python package for training and analyzing expected goals (xG) models in soccer. In particular, it contains code for experimenting with an exhaustive set of features and machine learning pipelines for predicting xG values from soccer event stream data

Code PyPI Research

ETSY

ETSY is a rule-based synchronization algorithm to synchronize soccer event data with its corresponding tracking / positional data.

Code

un-xPass

un-xPass is a framework to evaluate the creative abilities of soccer players using StatsBomb 360 data.

Code Research