Football_Prediction_Project and football_predictions
These are competitors—both use historical match data and machine learning to predict football outcomes, but the first focuses specifically on Premier League matches while the second covers broader European leagues, making them alternative choices for the same prediction task rather than tools designed to work together.
About Football_Prediction_Project
mhaythornthwaite/Football_Prediction_Project
This project pulls past game data from api-football, and uses this to predict the outcome of future premier league matches with the use of classical machine learning techniques.
Constructs rolling 10-game performance metrics across 14 engineered features (goal difference, shot accuracy, possession, etc.) to capture relative team form, then trains scikit-learn classifiers (Random Forest, KNN, SVM) optimized via grid search and 5-fold cross-validation. The pipeline automatically refreshes from api-football's daily API calls, enabling continuous model retraining on recent fixtures while maintaining a nested dictionary structure organized by team and match ID for scalable data management.
About football_predictions
msoczi/football_predictions
Predicting the results of matches in European leagues
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