How a top tier European soccer team sped up their data processing and reduced costs by 50%

This post details how a European soccer team (AFC Richmond) used Modal for processing spatio-temporal match data. The solution involved ingesting tracking data, running inference with a custom transformer-based model on GPUs, and writing results to cloud storage. Modal's serverless, usage-based pricing and fast container startup times led to a 50% cost reduction and processing times reduced from hours to minutes. The team also built an in-memory vector database on Modal for semantic search, demonstrating cost-effectiveness compared to managed solutions.