Soccer Analytics 2020 Review

Collection of the soccer analytics content that I liked the most in 2020!

Wednesday, December 30, 2020

The increased availability of free data, tutorials and tools has led to an explosion of interest in soccer analytics. The number of research papers, blog posts, webinars, podcasts and events has spiked in 2020. Access to granular data has been a privilege for data analysts and data scientists within clubs and companies until recently, but that situation is fortunately slowly changing. The release of several match event and tracking datasets has enabled more academics and amateur analysts to develop their own metrics and to perform more profound analysis. This blog post provides an overview of the content that I liked the most!

Although many exciting new ideas have entered the soccer analytics community as a result, separating the wheat from the chaff has also become more challenging for the followers of the community. To keep track of the latest developments in the soccer analytics community, I maintain a list of Twitter handles that share relevant content. This blog post lists the datasets, research papers, blog posts, news articles, invited talks, webinars, podcasts, Python libraries, events and newsletters that I believe are worth checking out.

My personal highlights of 2020 were finishing as runners-up in the research-paper competition at the MIT Sloan Sports Analytics Conference with a paper titled Player Chemistry: Striving for a Perfectly Balanced Soccer Team with Lotte Bransen, running a video tutorial series on valuing actions in soccer for Friends of Tracking with Lotte Bransen and contributing a chapter titled How Does Context Affect Player Performance in Football? to Barça Innovation Hub’s Football Analytics Guide 2021 with Lotte Bransen, Pieter Robberechts, Jesse Davis and Tom Decroos.


Research papers

Blog posts

Absolute Unit

American Soccer Analysis

DTAI Sports Analytics Lab

Get Goalside!

space space space


News articles

The Athletic

Training Ground Guru



Invited talks



Python libraries

  • kloppy Deserialize event data and tracking data from different data providers. Code. Documentation. Announcement.
  • codeball Apply tactical models and pattern matchers to event data and tracking data. Code. Documentation.
  • socceraction Compute VAEP and xT. Code.
  • soccer_xg Train and analyze expected-goals models. Code.
  • statsbombpy Consume the StatsBomb API. Code. Announcement.
  • Synchronize soccer datasets. Code.
  • mplsoccer Draw soccer pitches and load StatsBomb data. Code. Documentation.
  • soccerplots Draw soccer analytics visualizations. Code.
  • football_packing Compute packing rates for passes. Code. Documentation.


In memoriam