How Our Predictions Work
A transparent look at the methodology behind our World Cup predictions. We combine historical data, statistical models, and Monte Carlo simulation to generate probability estimates for tournament outcomes.
Data Sources
Our predictions are built on comprehensive historical and current tournament data.
- •Historical FIFA World Cup matches (2002–2022) for model training
- •Current tournament groups, fixtures, and team assignments from official sources
- •All data sourced through API-Football v3
Team Strength Estimation
We estimate each team's strength using ELO ratings and attack-defense decomposition.
- •ELO rating system (K=40) based on historical match results
- •Accounts for margin of victory and match importance
- •Attack strength: goals scored relative to tournament average (>1 = above average)
- •Defense strength: goals conceded relative to tournament average (>1 = weaker defense, Dixon-Coles convention)
- •Bayesian shrinkage toward mean for teams with limited data
Match Probability Generation
Match outcomes are modeled using Poisson distributions for goal scoring.
- •Each team's expected goals derived from attack/defense ratings
- •Independent Poisson distributions for each team's goals
- •Full score matrix (0-8 × 0-8) computed for each match
- •Win/Draw/Loss probabilities derived from score matrix summation
Tournament Simulation
We run thousands of Monte Carlo simulations to estimate championship probabilities.
- •Monte Carlo simulation with thousands of tournament iterations
- •Each simulation: full group stage → knockout stage
- •Group standings with FIFA tiebreakers (points, GD, GF)
- •Knockout matches include extra time and penalty consideration
- •Championship probability = fraction of simulations where team wins final
What This Is and What It Isn't
Understanding the nature and purpose of these predictions.
- •IS: A probability-based projection using historical data and statistical models
- •IS: Updated when new data becomes available
- •IS NOT: A guarantee of any specific outcome
- •IS NOT: Betting advice or gambling recommendation
- •IS NOT: An official FIFA prediction
Known Limitations
Our model has limitations that users should be aware of.
- •Data timeliness: Ratings based on historical results may lag current team form
- •Squad changes: Injuries, suspensions, and roster changes not explicitly modeled
- •Home advantage: Simplified modeling (not venue-specific)
- •Political/psychological factors: Not captured in the model
- •Predictions update as new data arrives — values may change between visits
Frequently Asked Questions
How are the probabilities calculated?▼
How often are predictions updated?▼
Can I use these for betting?▼
Why do the probabilities change?▼
What does 'X% chance to win' mean?▼
Why might a 'weaker' team have higher odds than expected?▼
Do you account for injuries or suspensions?▼
Historical Model Performance
We evaluate our prediction model against historical World Cup data. Below are the results from our historical World Cup backtest.
Prediction Accuracy
+18.3 percentage points above random
Brier Score(lower is better)
Evaluation Method
Evaluated against 2022 FIFA World Cup matches using Brier Score and top-1 accuracy. Match outcome probabilities (Win/Draw/Loss) were compared to actual results.
⚠️Important Limitations
- •Based on a single tournament (64 matches)
- •Limited sample size for statistical confidence
- •Historical results may not predict future performance
- •Model does not account for injuries, form changes, or tactical adjustments
Static backtest data from historical FIFA World Cup tournaments. This evaluation is not automatically updated. Past results do not guarantee future accuracy.