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.
- Learning the Value of Teamwork to Form Efficient Teams. Ryan Beal, Narayan Changder, Timothy Norman, Sarvapali Ramchurn. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020). February 2020.
- Interpretable Prediction of Goals in Soccer. Tom Decroos and Jesse Davis. AAAI 2020 Workshop on AI in Team Sports. February 2020. Presentation.
- Valuing On-the-Ball Actions in Soccer: A Critical Comparison of xT and VAEP. Maaike Van Roy, Pieter Robberechts, Tom Decroos and Jesse Davis. AAAI 2020 Workshop on AI in Team Sports. February 2020.
- Player Chemistry: Striving for a Perfectly Balanced Soccer Team. Lotte Bransen and Jan Van Haaren. Proceedings of the 2020 MIT Sloan Sports Analytics Conference. March 2020. Talk.
- The Right Place at the Right Time: Advanced Off-Ball Metrics for Exploiting an Opponent’s Spatial Weakenesses in Soccer. Sergio Llana, Pau Madrero and Javier Fernández. Proceedings of the 2020 MIT Sloan Sports Analytics Conference. March 2020.
- Seeing in to the Future: Using Self-propelled Particle Models to Aid Player Decision-making in Soccer. Francisco Peralta, Pablo Piñones, David Sumpter and Javier Fernández. Proceedings of the 2020 MIT Sloan Sports Analytics Conference. March 2020.
- Optimising Game Tactics for Football. Ryan Beal, Georgios Chalkiadakis, Timothy Norman and Sarvapali Ramchurn. Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020). May 2020. Talk.
- Using Player’s Body-Orientation to Model Pass Feasibility in Soccer. Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández, Coloma Ballester and Gloria Haro. CVPR-2020 Workshop on Computer Vision in Sports (CVsports 2020). June 2020. Talk.
- Group Activity Detection From Trajectory and Video Data in Soccer. Ryan Sanford, Siavash Gorji, Luiz Hafemann, Bahareh Pourbabaee and Mehrsan Javan. CVPR-2020 Workshop on Computer Vision in Sports (CVsports 2020). June 2020. Talk.
- Cracking the Black Box: Distilling Deep Sports Analytics. Xiangyu Sun, Jack Davis, Oliver Schulte and Guiliang Liu. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020). July 2020. Code.
- Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players. Yudong Luo, Oliver Schulte and Pascal Poupart. Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020). July 2020. Code.
- Deep Soccer Analytics: Learning an Action-Value Function for Evaluating Soccer Players. Guiliang Liu, Yudong Luo, Oliver Schulte and Tarak Kharrat. Data Mining and Knowledge Discovery. September 2020. Talk.
- Routine Inspection: A Playbook for Corner Kicks. Laurie Shaw and Sudarshan Gopaladesikan. ECML/PKDD 2020 Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2020). September 2020. Talk and Presentation.
- SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer. Javier Fernández and Luke Bornn. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2020). September 2020. Talk and Presentation.
- SoccerMix: Representing Soccer Actions with Mixture Models. Tom Decroos, Maaike Van Roy and Jesse Davis. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2020). September 2020. Talk and Presentation.
- Automatic Pass Annotation from Soccer Video Streams based on Object Detection and LSTM. Danilo Sorano, Fabio Carrara, Paolo Cintia, Fabrizio Falchi and Luca Pappalardo. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2020). September 2020. Talk and Presentation. Code.
- The Tactics of Successful Attacks in Professional Association Football: Large-Scale Spatiotemporal Analysis of Dynamic Subgroups Using Position Tracking Data. Floris Goes, Michel Brink, Marije Elferink-Gemser, Matthias Kempe and Koen Lemmink. Journal of Sports Sciences. October 2020.
- Soccer Analytics Meets Artificial Intelligence: Learning Value and Style from Soccer Event Stream Data. Tom Decroos. PhD Thesis. November 2020.
- A Framework for the Fine-Grained Evaluation of the Instantaneous Expected Value of Soccer Possessions. Javier Fernández, Luke Bornn and Daniel Cervone. arXiv pre-print. November 2020. Not published yet.
- Introducing: Absolute Unit. August 2020.
- The Currency of “Goal Difference”. August 2020.
- What About the Budget?. August 2020.
- Projections Deep Dive: Team Effects & Aging Curves. October 2020.
- Projections Deep Dive: Re-levering with a Team Performance Model. November 2020.
- Projections Deep Dive: The Game Model and “Player Fit”. December 2020.
American Soccer Analysis
- Data Based Coaching: How to Incorporate Data-Driven Decisions into Your Coaching Workflow. March 2020.
- Goals Added: Introducing A New Way To Measure Soccer. May 2020.
- Goals Added: Deep Dive Methodology. May 2020.
- Goals Added and The Great Possession Shift. May 2020.
- Goals Added: The Art of the Wheel. May 2020.
- Goals Added: How a Computer Watches Nicolas Lodeiro Play Soccer. May 2020.
- Defining Roles: How Every Player Contributes to Goals. August 2020.
- Introducing DAVIES: A Framework for Identifying Talent Across the Globe. September 2020. Webapp.
- The DePo Models: Bringing Moneyball to Professional Soccer. October 2020.
DTAI Sports Analytics Lab
- Exploring How VAEP Values Actions. April 2020.
- Introducing Atomic-SPADL: A New Way to Represent Event Stream Data. May 2020.
- How Data Availability Affects the Ability to Learn Good xG Models. May 2020.
- Illustrating the Interplay Between Features and Models in xG. May 2020.
- Our Thoughts on American Soccer Analysis’ g+ Metric. May 2020.
- How Data Quality Affects xG. July 2020.
- Enhancing xG Models with Freeze Frame Data. September 2020.
- SoccerMix: Representing Soccer Actions with Mixture Models. December 2020.
- A Smarter Approach to Squad-Building. July 2020.
- The Real Meaning of Moneyball. July 2020.
- How Can Tracking Data Help Defending Analytics?. August 2020.
- xG in FM? What Does This Mean?. November 2020.
space space space
- Neymar is a Choker (Scientifically Speaking). August 2020.
- Daddy, Where Do Transfer Fees Come From?. September 2020.
- An Introduction to Soccer Analytics. September 2020.
- Valuing Off-the-Ball Movement. Ricardo Tavares. January 2020.
- Getting into Sports Analytics 2.0. Sam Gregory. January 2020.
- Expected Goals and Conversion — A Probabilistic Approach. March 2020.
- Expected Potential (xPo). Aditya Kothari. April 2020.
- The Growing Importance of Football Analytics. Soccerment Research. May 2020.
- Meet the Model That’s Redefining Value and Plotting the Demise of Messi and Ronaldo. Ryan O’Hanlon. June 2020.
- Assorted Sports Analytics Mailbag. Sam Gregory. June 2020.
- Evolving Our Possession Value Framework. Jonny Whitmore. October 2020.
- Sports Analytics 101: The Case for Sports Analytics. Brendan Kent. October 2020.
- Finishing Ability: Uncovering The Signal. Charles William. August 2020.
- Quantifying Player Chemistry — Joint Expected Threat (JxT). Gerald Lim. December 2020.
- Sports Analytics 101: Descriptive vs. Predictive. Brendan Kent. December 2020.
- The Clinical Finishing Model. Abhishek Amol Mishra. December 2020.
- Measuring Freedom. Sagnik Das. December 2020.
- Explained: The 10 Commandments of Football Analytics. Tom Worville. March 2020. Video by Tifo Football.
- Football Remodelled: Why Transfers, Scouting and Coaching Are Drenched in Data. Adam Crafton. April 2020.
- How Data and Analytics Work at Chelsea from Top to Bottom. Liam Twomey, Adam Crafton, et al. August 2020.
- How Does Everton’s Recruitment Work?. Patrick Boyland. August 2020.
- Meet William Spearman, Liverpool’s Secret Weapon. Simon Hughes. September 2020.
Training Ground Guru
- William Spearman: How Liverpool Create Pitch Control Models. Simon Austin. April 2020.
- Dan Altman: Who’s Who in a Football Data Department?. Dan Altman. June 2020.
- Why Liverpool Hired a French Start-Up to Turn Video into Data. Simon Austin. August 2020.
- ‘Expected Threat’, ‘Width per Sequence’ — The Statistical Metrics You Haven’t Heard Of. Daniel Clark. February 2020.
- How Soccer Scouting Has Changed, And Why It’s Never Going Back. Robert Kidd. May 2020.
- Behind the Badge: The Physicist Who Leads Liverpool’s Data Department. Sam Williams. June 2020.
- How the Volunteers of Data Website Transfermarkt Became Influential Players at European Top Football Clubs. Pepijn Keppel and Tom Claessens. December 2020.
- OptaPro Forum. 5 February 2020. London, United Kingdom.
- Workshop on Artificial Intelligence in Team Sports (AITS 2020). 8 February 2020. New York, United States. Schedule.
- Tactical Insights. 19 February 2020. Leicester, United Kingdom. Review.
- Google Sports Analytics Meetup. 5 March 2020. Virtual.
- MIT Sloan Sports Analytics Conference (MITSSAC 2020). 6-7 March 2020. Boston, United States.
- Friends of Tracking (FoT). Virtual. Code.
- IEEE International Workshop on Computer Vision in Sports (CVsports 2020). 19 June 2020. Virtual.
- Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2020). 18 September 2020. Virtual. Schedule.
- Carnegie Mellon Sports Analytics Conference (CMSAC 2020). 24-25 October 2020. Virtual. Schedule. Posters.
- Sports Tomorrow. 9-20 November 2020. Virtual. Football Analytics Guide 2021.
- Dynamic Analysis of Team Strategy in Professional Soccer by Laurie Shaw. AAAI 2020 Workshop on AI in Team Sports. February 2020.
- Tactical Insight Through Team Personas by David Perdomo Meza and Daniel Girela. OptaPro Forum 2020. February 2020. Blog post.
- I’m in a Wide Open Space: Creating Opportunities at Set Pieces by Dan Barnett. OptaPro Forum 2020. February 2020.
- Long or Short? How the New Short Goal Kick Rule Is Impacting Football by Tom Worville. OptaPro Forum 2020. February 2020.
- Learning to Watch Football: Self-Supervised Representations for Tracking Data by Karun Singh. OptaPro Forum 2020. February 2020. Blog post.
- Identifying and Evaluating Strategies to Break down a Low Block Defence by Vignesh Jayanth. OptaPro Forum 2020. February 2020. Blog post.
- Dynamic Analysis of Team Strategy in Professional Soccer by Laurie Shaw. Google Sports Analytics Meetup. March 2020.
- Seeing in to the Future: Modelling Football Player Movements by David Sumpter. Linköping University Seminar. April 2020.
- Learning Value and Style from Soccer Event Stream Data by Tom Decroos. Harvard University Sports Analytics Lab Seminar. December 2020.
- How Tracking Data is Used in Football and What are the Future Challenges with Javier Fernández, Suds Gopaladesikan, Laurie Shaw, William Spearman and David Sumpter. Friends of Tracking. April 2020.
- Why Do Clubs Need to Embrace Analytics to Stay Competitive? with Vosse de Boode, David Sumpter, Adrien Tarascon and Javier Fernández. Barça Innovation Hub. May 2020.
- William Spearman’s Masterclass in Pitch Control with William Spearman. Friends of Tracking. April 2020.
- Valuing Actions in Football: Introduction with Lotte Bransen. Friends of Tracking. May 2020.
- Valuing Actions in Football 1: From Wyscout Data to Rating Players with Jan Van Haaren. Friends of Tracking. May 2020. Code.
- Valuing Actions in Football 2: Generating Features with Lotte Bransen. Friends of Tracking. May 2020. Code.
- Valuing Actions in Football 3: Training Machine Learning Models with Jan Van Haaren. Friends of Tracking. July 2020. Code.
- Valuing Actions in Football 4: Analyzing Models and Results with Lotte Bransen. Friends of Tracking. October 2020. Code.
- The Process #16: The Future of Football with Ted Knutson. 13 January 2020.
- Open Source Sports: Player Chemistry in Soccer with Lotte Bransen. 13 September 2020.
kloppyDeserialize event data and tracking data from different data providers. Code. Documentation. Announcement.
codeballApply tactical models and pattern matchers to event data and tracking data. Code. Documentation.
socceractionCompute VAEP and xT. Code.
soccer_xgTrain and analyze expected-goals models. Code.
statsbombpyConsume the StatsBomb API. Code. Announcement.
sync.soccerSynchronize soccer datasets. Code.
mplsoccerDraw soccer pitches and load StatsBomb data. Code. Documentation.
soccerplotsDraw soccer analytics visualizations. Code.
football_packingCompute packing rates for passes. Code. Documentation.
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