Public project · Oct 2026
Football, Visualized
An interactive football analytics app that makes expected goals tangible: move a shot, inspect its features, and explore the model behind the estimate.
The interactive pitch lets visitors change shot conditions and inspect eight model features alongside an expected-goals estimate. I connected a reproducible StatsBomb Open Data pipeline to XGBoost training and evaluation, then brought inference into the browser with a Next.js/React interface.
The playground is available in five languages and includes methodology and evaluation results. It brings my data, applied ML, backend-to-interface integration, and product work into one public project: visitors can explore what the model does, while the repository exposes how the result was built.
- Next.js
- React
- TypeScript
- Python
- XGBoost
- StatsBomb Open Data