Simulation Methodology

Purpose of This Page

This page explains how the World Cup 2026 rankings and simulations are generated. It does not display rankings or results. Its sole purpose is to document the logic, assumptions and statistical mechanisms used to produce them.

The rankings page presents outcomes. This page explains the process behind those outcomes, ensuring transparency and allowing users to understand what the simulations represent — and what they do not.

Data Sources

The model relies primarily on FIFA ranking points as a baseline measure of team strength. These points are captured as a snapshot and are not updated dynamically during simulations.

When official data is incomplete or unavailable, fallback assumptions are applied to avoid excluding teams from simulations. These assumptions are conservative by design and aim to preserve relative balance rather than introduce artificial advantages.

Team Strength Calculation

Raw FIFA ranking points cannot be used directly in probabilistic simulations. They are therefore normalized onto a continuous scale between 0 and 1.

This normalization ensures that differences between teams influence probabilities smoothly, rather than producing abrupt or deterministic outcomes. The resulting value represents relative strength, not an expected score or guaranteed advantage.

This approach allows the model to compare teams across different confederations while avoiding overfitting to absolute ranking positions.

Match Outcome Model

Match results are generated probabilistically based on the relative strength of the two teams. A stronger team has a higher probability of winning, but weaker teams always retain a non-zero chance of success.

The model intentionally avoids deterministic predictions. Football outcomes are inherently uncertain, and the simulation reflects that uncertainty rather than attempting to eliminate it.

Monte Carlo Simulation Process

To capture uncertainty at scale, the tournament is simulated thousands of times using a Monte Carlo approach. Each simulation represents one plausible version of the tournament.

Percentages shown in the results do not represent certainty. They indicate how often a given outcome occurred across all simulations. For example, a 25% qualification rate means the outcome occurred in roughly one quarter of simulations.

This method allows patterns to emerge without assuming that any single simulation reflects the “true” future.

Tie-Breaking and Edge Cases

When teams finish level on points or goal difference, tie-breaking rules are applied following tournament logic. In cases where criteria remain equal, outcomes are resolved using controlled random selection.

These edge cases are intentionally included to prevent systematic bias and to reflect how real tournaments handle unresolved ties.

Limitations of the Model

This model does not account for injuries, squad rotation, tactical changes, coaching decisions or match-specific context such as weather or venue.

It should be viewed as a statistical exploration tool rather than a predictive oracle. The goal is to explore plausible tournament dynamics, not to forecast exact results.

Relationship to the Rankings Page

This methodology describes how simulations and rankings are generated. To view the outcomes produced by this model, visit the World Cup 2026 Rankings page.