Case Study: City Football Group achieves faster, more accurate decision-making and slashes model development from 500 to 9 hours with DataRobot

City Football Group - Customer Case Study

City Football Group, led by Brian Prestidge, needed to turn exponentially growing, complex football data into fast, trusted decisions across its ten global clubs—from in-game tactics to player recruitment and injury risk. To scale analytics, democratize AI across non‑data staff, and speed model development for high‑pressure match environments, the club adopted DataRobot’s AutoML capabilities to bring rigorous data science into everyday coaching and performance workflows.

DataRobot’s platform enabled City Football Group to analyze roughly 2,000,000 data points per match and track 500,000 players globally, while cutting model development time from about 500 hours (original quant models) to just 9 hours. Using DataRobot, the team improved forecasting accuracy, ran what‑if simulations (lineup changes, substitutions, load management), and delivered faster, evidence‑based decisions for coaches and recruitment—supporting on‑field performance and operational agility across the organization.

City Football Group

Brian Prestidge

Director of Insights and Decision Technology