FanPick Blog
Latest news and insights
Quantifying Home Advantage โ How to Build It Into Your Football Prediction Model
Home advantage is worth +0.30-0.45 goals per match. Learn what drives it, how COVID proved crowd effects, and four methods to build it into your prediction model.
July 5, 2026
How to Update Football Predictions in Real Time During Live Matches
Learn how Bayesian inference and non-homogeneous Poisson processes power real-time football prediction that updates with every match event.
July 3, 2026
Football Prediction for Knockout Matches โ Why Cup Games Need Different Models Than League Games
Germany and the Netherlands both lost on penalties in the Round of 32. Learn why league prediction models fail in knockout football and how to adjust your Poisson, Elo, and penalty models for cup matches.
July 2, 2026
Random Forest and Gradient Boosting for Football Predictions โ Tree-Based Models That Actually Work
Learn how tree-based ensemble models predict football match outcomes. Random Forest vs XGBoost vs LightGBM compared with practical tuning tips and feature engineering.
June 30, 2026
How to Calibrate Your Football Prediction Model โ Brier Score, Log Loss, and Reliability Diagrams Explained
Learn how to calibrate your football prediction model using Brier score, log loss, and reliability diagrams. A practical guide to making your probability estimates trustworthy.
June 29, 2026
Does Team Form Actually Predict Match Results? How to Measure Momentum with Data
Everyone talks about momentum in football. But does team form actually predict match outcomes? A data-driven guide to measuring form with EMA and rolling averages.
June 27, 2026
Feature Engineering for Football Prediction Models โ The Inputs That Actually Matter
Learn how to engineer features for football prediction models. Time-decay form, strength-of-schedule, Elo ratings, and the 10 features every model needs to beat the market.
June 26, 2026
Expected Threat (xT) โ The Football Analytics Metric That Values Every Touch
Expected goals only values shots. Expected Threat (xT) values every pass, dribble, and carry on the pitch. Learn how this Markov chain model predicts football better than xG alone.
June 24, 2026
Logistic Regression for Football Predictions โ The Foundation Every Model Needs
Learn how logistic regression powers football prediction models. From the sigmoid function to win/draw/loss probabilities, this guide breaks down the math that drives match forecasting.
June 22, 2026
Advanced Football Statistics Beyond xG โ The Metrics That Actually Predict Match Outcomes
Expected goals is just the start. Learn PPDA, field tilt, progressive passes, xAG, and the advanced metrics that professional analysts use to predict football outcomes.
June 22, 2026
How to Read Betting Odds and Convert Them into Probabilities
Learn to convert decimal, fractional, and American odds into implied probabilities. Find value bets, understand the overround, and make sharper predictions.
June 21, 2026
The Kelly Criterion for Football Predictions โ Optimal Bet Sizing for Maximum Growth
Learn how the Kelly Criterion sizes football prediction bets for maximum bankroll growth. Formula, worked examples, fractional Kelly, and a practical workflow.
June 19, 2026