Football analytics has rapidly evolved over the past five years, becoming a crucial part of professional and fan discourse. While much of the cutting-edge research remains hidden behind the fences of club training grounds, a growing ecosystem of open-source tools now enables anyone to develop advanced football analytics models.

In this talk, I'll showcase key open-source libraries—Polars for high-performance data processing, Keras for deep learning, and Spektral for Graph Neural Networks (GNNs)—to analyze millions of player coordinates from publicly available high-frequency positional tracking data. I'll demonstrate how these tools can be used to build in-game prediction models and extract advanced football metrics that only the most advanced football clubs currently use.