Machine learning pipeline to predict FIFA World Cup 2026 match outcomes and simulate the tournament bracket using historical international football data.
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Updated
Jun 19, 2026 - Jupyter Notebook
Machine learning pipeline to predict FIFA World Cup 2026 match outcomes and simulate the tournament bracket using historical international football data.
Plataforma de scouting y predicción del rendimiento de futbolistas jóvenes (17–20 años) usando datos históricos de FIFA y modelos de Machine Learning y Deep Learning, desplegada en Streamlit.
ML-powered Premier League scouting dashboard with player similarity, percentile profiles, shot maps, and open-data event heatmaps.
Reproducible Serie A forward scouting pipeline built with Python and transparent recruitment proxies.
Event-level football analytics across 15 leagues and competitions, built from parsed WhoScored/Opta match data. Flask backend with 12 percentile-ranked metric categories per player, cross-league player comparison, statistical scouting, and single-metric stat exploration.
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