Future of data and technology in football

Overview

This course explores the emerging technologies that will shape the future of football analytics, from advanced tracking systems and live data pipelines to machine learning, LLMs, and AI-driven decision tools. Learners will understand how innovations such as computer vision, skeleton tracking, body-orientation models, and contextual load monitoring are transforming the way clubs analyze performance, manage fatigue, and make in-match tactical adjustments.

The course also examines how AI is revolutionizing scouting and recruitment:

from automated LLM-generated scouting reports and narrative “wordalisation,” to web scraping, social-media analysis, and multimodal data pipelines. Finally, learners will explore cutting-edge developments in performance AI, including reinforcement-learning concepts inspired by AlphaZero, supervised learning for tactical tagging, and AI assistant-coach systems that recognize patterns across thousands of match situations.

By completing this course, learners will gain a forward-looking understanding of how machine learning, automation, and next-generation data systems will redefine competition, recruitment, coaching, and performance across the football industry.

Syllabus

• The rise of skeleton data
Discover how granular tracking of player movement—down to body orientation—offers new windows into decision-making and defensive mastery. This module unpacks both the opportunities and challenges of skeleton data, revealing how advanced tracking is poised to revolutionize tactical understanding and player evaluation.
• Live Data
Dive into the real-time world of live football analytics. Learn about current technological limits, the quest for more actionable in-game data, and how innovations in physical load tracking and tactical flagging are set to influence everything from substitutions to strategic adjustments on the fly.
• AI in Scouting
Examine the emerging role of artificial intelligence in player scouting. This module explores how large language models are automating report generation, the current obstacles in AI-driven evaluations, and how new data approaches are making player profiles more comprehensive and actionable than ever before.
• AI in Performance
Unpack the next wave of AI-driven performance analytics. From unsupervised learning inspired by chess to AI assistant coaches and automated data tagging, you’ll see how machine learning is reshaping not just how we analyze football, but how we understand and optimize the game itself.

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Taught by

Marisa Sáenz

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Subjects

Computer Science