Data product
World Cup Analytics
An analytics product to explore World Cup 2026 data, including matches, teams, players, rankings, xG, shots, shot maps, and individual profiles.
Status: Live · Focus: Data engineering, API, visualization, football analytics
PythonPostgreSQLFastAPIReactDockerCloudflare
Problem: Raw match data doesn't tell a story on its own, and serving complex aggregations at request time doesn't scale as the competition progresses.
What I built: A bronze/gold pipeline with PostgreSQL and FastAPI that serves pre-computed payloads in 30–40 ms, with editorial curation over the cases where raw data lies (penalties, final score, shot maps).
Personal project
World Cup Match Ratings
Subjective ratings for all 104 matches of the 2026 World Cup — five criteria, custom weights, and a live dashboard powered by a spreadsheet. No data science pretensions.
Status: Live · Focus: Football analytics, visualization, subjective data
Problem: Objective stats (xG, rankings) don't capture what it felt like to watch a match.
What I built: A rating system with per-criterion weights, fed by a spreadsheet and served on a public dashboard — open-sourced so anyone can clone it and run their own version.