The model does not claim to know the future. It repeatedly simulates the tournament from team strength, market priors, roster context, and player availability, then counts how often each team, player, and possible matchup lands in each knockout slot.
Each team starts with observable football signals and transparent assumptions. We use the signals to estimate relative team strength, not to hard-code a winner.
FIFA ranking points anchor each team's baseline quality.
Squad market value adds a market-based signal for depth and star power.
Betting-market priors convert advance and title odds into implied probabilities.
Form, health, chemistry, and host status adjust the baseline for current context.
Player availability and expected knockout usage shape player appearance chances.
rating = FIFA points + market value signal + odds signal + form + health + chemistry + host boostThe exact weights keep FIFA points as the anchor while allowing current market, odds, and squad-context signals to move teams up or down.
strength gap → expected goals → simulated score → knockout winnerStronger teams win more often, but every match is still sampled with randomness so upsets and narrow paths remain possible.
P(team in M78) = count(team appears in M78) / simulationsFor every match number, we count how often each team arrives there. That is the “team path” number shown in the planner.
A player can only appear in a match if their team reaches that match. After that, the model applies availability, status, expected usage, and later-round attrition.
P(player appears in match) = P(team reaches match) × P(player appears | team reaches)Example: if Norway has a 33% path to a match and the player has an 85% chance to play if Norway gets there, the overall player appearance chance is about 28%.
These labels are meant to answer different fan questions: who might be there, who might play, who might win, and which exact matchup is most likely.
How often that team appears in that exact knockout fixture across all simulated tournaments.
How often that player appears in that exact fixture. It equals team path probability times player-play probability if the team gets there.
The conditional chance the player appears after their team has already reached that match.
The probability of a specific team-vs-team matchup happening in that match slot.
For team mode, the conditional chance the team wins that match once it has reached it.
The chance the match contains at least one elite tracked player from either side.
20,000 simulations: enough to make the biggest match-slot probabilities stable to roughly a few tenths of a percentage point from simulation noise alone.
Odds are inputs: betting markets are useful crowd-price signals, but they are blended with football data and are not treated as advice.
Path-aware players: a player on a strong team can have more late-round chances even if their conditional appearance rate is similar to another player.
Matchups matter: a match slot can be likely for one team while the exact opponent remains highly uncertain.