Football_Prediction_Project and MatchOutcomeAI
These are competitors: both use machine learning to predict football match outcomes, but A focuses specifically on Premier League matches via api-football while B takes a broader data-driven approach with multiple algorithms, requiring users to choose between them for their prediction needs.
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 MatchOutcomeAI
ratloop/MatchOutcomeAI
A data-driven approach to predicting football match outcomes using advanced machine learning techniques. This project integrates various algorithms to forecast game results, providing insights for sports betting, team performance analysis, and sports enthusiasts.
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