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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.
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.
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.
How to use Elo ratings for football predictions
A practical guide to using Elo ratings in football predictions, from team strength and home advantage to draw probability, league adjustments, and model improvement.
The best data sources for AI soccer predictions
A practical guide to the best data sources for AI soccer predictions, covering event data, tracking data, odds, injuries, and open datasets, plus how to choose, validate, and combine them.
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.