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Expected goals explained and how AI uses xG to predict results
Understand expected goals (xG) from first principles and see how AI uses xG, shot quality, and team context to predict football results with stronger accuracy and calibration.
Over and under goals: how AI predicts goal totals
Learn how AI predicts over and under goals by estimating expected goals, tempo, team styles, and variance, then converting them into calibrated probabilities for total goals markets.
If Alonso is not good enough for Real, then who is?
Philipp Lahm has come to the defense of his former teammate Xabi Alonso. The Basque was dismissed earlier this year by Real Madrid, and Lahm sees the coaching job at Los Blancos as the ultimate challenge in world football.
The impact of VAR on penalties and match outcomes
Learn how VAR affects penalties, match outcomes, football predictions, and betting models by changing decision accuracy, game state, scoring probability, and late-match volatility.
How odds move and what AI can learn from bookmakers
Learn why football odds move, what drives bookmaker price changes from opening to closing lines, and how AI models can use odds and line movement without leakage.
Value betting explained with examples from AI probabilities
A clear, example-driven guide to value betting using AI probabilities, showing how to convert odds into implied probabilities, spot positive expected value, size stakes responsibly, and avoid common traps.