Junior Data Scientist Builds Model to Predict Promoted Clubs' Top-Flight Survival

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A beginner data scientist has launched a portfolio project aimed at predicting whether newly promoted clubs in Europe's top football leagues will avoid relegation in their debut season. The project is motivated by the fact that roughly two out of three promoted clubs are relegated in their first season back in the top flight. Using match data from football-data.co.uk dating back to 1993/94, the model will analyze only the first eight games of a club's debut season to generate early survival predictions. The tech stack includes pandas, scikit-learn, imbalanced-learn, and a Streamlit dashboard for interactive visualization. The project follows a public six-part timeline running from July 11 to August 8, 2026, with acknowledged challenges including a small dataset of around 60–100 samples and inconsistent team naming across data sources.

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