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Getting Started with Premier League Predictions

Published on December 6, 2025


Introduction


Welcome to our Premier League predictions platform! This article will walk you through how our betting model works and what our goals are with this project.


The Vision


Our mission is to provide data-driven predictions for Premier League matches using machine learning models. We combine historical match data, team statistics, expected goals (xG), and odds data to predict:


  • **Over/Under Goals** - Will a match have more or fewer than 2.5 or 3.5 goals?
  • **Match Winners** - Which team will win the match (Home Win, Draw, or Away Win)?

    • Our Models


    We currently use two primary machine learning models:


    ### KNN (K-Nearest Neighbors)

  • Simple yet effective approach
  • Finds similar historical matches and uses their outcomes to predict
  • Fast and interpretable
  • Optimal K value: typically between 5-15

    • ### XGBoost

  • Advanced gradient boosting algorithm
  • Considers multiple features and their interactions
  • Generally more accurate than KNN
  • Trained on 1000+ historical Premier League matches

    • Data Sources


    Our models are trained on comprehensive Premier League data including:


  • Match results and goal counts
  • Team possession statistics
  • Shot statistics (shots on target, shots off target)
  • Corner counts
  • Card counts
  • Pre-match betting odds
  • Expected Goals (xG) metrics
  • Historical team performance (Points Per Game)

    • Accuracy Metrics


    We track accuracy across multiple dimensions:


  • **Overall accuracy** across all matches
  • **By matchweek** performance to track consistency
  • **By goal threshold** (Over/Under 2.5 vs 3.5)
  • **Confidence calibration** - how well our confidence scores match actual accuracy

    • How to Use the Platform


  • **View Predictions** - Go to the Predictions page to see current week match predictions
  • **Check Results** - See how previous predictions performed with actual match results
  • **Analyze Models** - Review detailed model performance metrics and visualizations
  • **Champions League** - View our UEFA Champions League match winner predictions

    • Methodology


    Each week, we:


  • Fetch the latest match data and betting odds
  • Calculate features from historical data
  • Run our KNN and XGBoost models
  • Generate predictions with confidence scores
  • Display consensus predictions when both models agree
  • Track accuracy as matches complete

    • Next Steps


    In future updates, we plan to:


  • Expand to other leagues and competitions
  • Add more advanced features (team form, injuries, etc.)
  • Implement ensemble methods combining multiple models
  • Provide API access for predictions
  • Add user accounts for tracking personal predictions

    • Disclaimer


    These predictions are for analytical purposes only. Always gamble responsibly and never bet more than you can afford to lose. Past performance does not guarantee future results.



    Have questions? Check out our Methodology page for more technical details about how the models work.