This course explores how football evolved from intuition-driven decision-making to a fully data-powered sport. Learners will uncover the origins of sports analytics through the “Moneyball” revolution in baseball, the rise of shot-quality models in basketball and hockey, and the early pioneers who first applied scientific thinking to football. From Charles Reep’s handwritten data charts to Lobanovskyi’s cybernetic model, the course traces how ideas from statistics, engineering, and computer science gradually reshaped how the game is played and understood.

As technology advanced, video analysis, event data, and tracking systems transformed how clubs evaluated performance, recruited players, and designed tactics. Case studies show how modern clubs exploit data to find market inefficiencies and gain competitive advantages. By the end of this course, learners will understand the milestones, people, and technologies behind football’s analytics revolution — and how they paved the way for the sophisticated models used today.