Soccermatics Pro

For aspiring football data scientists who want to learn the full technical stack, from Python and stats to machine learning, needed to work in the professional game.

By Professor David Sumpter

When: November - January 2025

Duration: Ten weeks

Price: €1695 + VAT

Course introduction

On our Flagship course, you will learn how to understand the game using mathematics, statistics, and machine learning. It offers the technical skills, in Python, needed to work as a data scientist at a football club or in the football industry. The course utilises data from leading data providers, including event, tracking, and physical data. Taught by Soccermatics author David Sumpter and supported by Twelve experts as tutors, the course also features guest lectures from world-leading practitioners and researchers working with data in football.

Course content

  • Week 1: Visualising football data: passes, shots and defensive actions

  • Week 2: Statistical models and expected goals.

  • Week 3: Scouting: player metrics and radars.

  • Week 4: Position-based and action-based Expected threat.

  • Week 5: Developing team metrics for long-term success.

  • Week 6: Pitch control and tracking data.

  • Week 7: Advanced scouting metrics for off-ball movement.

  • Week 8: Using large language models in football.

  • Week 9: Introduction to deep learning.

  • Week 10: Student presentations.

Pedagogical approach

  • Live tutorial with David Sumpter (recorded for later viewing)

  • Small group sessions and one-on-one support

  • Group projects with peers working at real clubs

  • Access to rich event and tracking data for hands-on work

  • Get help with club-specific challenges from Twelve staff

Professor David Sumpter

Professor David Sumpter is a professor of applied mathematics at Uppsala University and the author of “Soccermatics,” a book that explores the application of mathematical modeling to football. He co-founded Twelve Football and has worked with major clubs and national federations worldwide.

Testimonials

"If you are interested in Analytics and Football, it’s an excellent learning resource and highly recommended."

Kenny McMillan, Aspire Academy.

"Thank you for all this course does for the community. I’ll be joining a Brazilian club as a data scientist in the upcoming weeks, and it is crystal clear that it would not happen without your course."

Rodrigo Salvador, Red Bull Bragantino.

"Learned a lot of new things and met incredible people. It was a great experience and I would highly recommend signing up for the course."

Mikha Gabechava, Head Scout, FC Dinamo Tbilisi.

"I appreciated the course very much. I recommend it for anyone interested in gaining (additional) knowledge in data science/analysis in their organization."

Martin Vogelbein, Scouting, Match Analysis and Diagnosis, Deutscher Fußball-Bund.

"My Python coding was a weak area for me, and I really wanted to improve in this so I can be more responsive to the needs of the coach and team. It was a great course, with such useful skills being covered. There are so many analysts working in football, but so much mathematics missing from their skillsets."

Mark Carter, English FA.

"The course tutor dedicated time to sit with me individually, start from scratch, and write a customised step-by-step plan to wrangle one of the file formats I provided him. For me, this was going above and beyond his duties and really assisted me as a relative beginner in Python."

Liam Cody, Pro Solutions Team Lead - APAC & Americas, Statsperform.

"The course combined mathematics, programming, and real-life cases from industry experts - along with three obligatory hand-ins in Python. Being able to apply this course to own data sources and develop bespoke metrics makes this course recommendable."

Simon Eilersen, Football Data Consultant, Danish League.

"I enjoyed the course very much. I enjoyed the relaxed atmosphere, in which I was nevertheless able to gain some exciting insights. It was a great opportunity for me to get familiar with event and tracking data in the context of game analysis/scouting. Especially the insight into presenting the results via Python Streamlit was a big game changer for me. We are now establishing this framework at TSG Hoffenheim."

Fabian Rupp, Business Intelligence & Data Analytics, Hoffenheim.