Big Data in Football: What Clubs Actually Use

Professional football clubs generate terabytes of data every season. This article reveals the specific big data technologies, platforms, and workflows used behind the scenes at elite clubs.

A single Premier League match produces approximately 3.5 million tracking data points, 2,000-3,000 event data entries, 90 minutes of multi-angle video, and physical performance data from GPS devices worn by every player. Over a full season including training, a top club generates over 10 terabytes of structured data.

Data collection happens automatically during training and matches via GPS vests and optical tracking systems. Raw data is uploaded to cloud servers where automated pipelines clean, validate, and structure the information. Analysts access processed data through custom dashboards, generating reports for coaching staff, medical teams, and recruitment departments.

Most clubs use relational databases (PostgreSQL, MySQL) for structured match and player data, supplemented by NoSQL databases (MongoDB) for unstructured data like video metadata and scouting reports. Data lakehouse architectures combining the benefits of data lakes and data warehouses are gaining popularity for their flexibility in handling diverse data types.