🎲 Simulatore Monte Carlo
Esegui 10.000 Simulazioni dei Mondiali 2026
Scopri chi ha più probabilità di vincere — con la matematica, non con l'intuito. Simuliamo il torneo completo di 48 squadre con ELO o ranking FIFA, migliaia di volte.
Classifica Elo del calcio mondiale
~3 s
Scegli le impostazioni e clicca su Avvia simulazione per vedere le probabilità previste per ogni squadra.
How the World Cup Simulator Works
The simulator uses the Monte Carlo method to predict outcomes for the 2026 FIFA World Cup. Instead of picking a single bracket, it runs the entire 48-team tournament thousands of times with randomized outcomes weighted by team strength. The result is a probability distribution that tells you not just who might win, but how likely every possible outcome is. Think of it as running 10,000 parallel World Cups and counting how often each team lifts the trophy.
1. Set your parameters
Choose how many simulations to run (1,000 for a quick estimate, 10,000 for reliable probabilities, or 100,000 for research-grade precision). Select your rating system: ELO Football ratings for a model based on historical match results, or FIFA World Ranking for the official points-based system updated monthly by FIFA. Each system weights teams differently, so you can compare how the choice of model affects predictions.
2. Run the simulations
Click "Run" and the simulator plays through every group-stage match, calculates standings by points, goal difference, and goals scored, advances teams to the Round of 32, and then simulates single-elimination knockout rounds through to the Final. Each match result is randomized but weighted by the strength gap between the two teams — stronger teams win more often, but upsets happen at realistic rates.
3. View probability results
After all simulations complete, you see a probability table showing every team's chance of reaching each round: group stage exit, Round of 32, Round of 16, Quarterfinals, Semifinals, Final, and Champion. Scan the results to find which teams are most likely to reach the Quarterfinals or which teams have the highest upset potential.
4. Compare scenarios
Run multiple simulations with different settings to compare outcomes. Switch from ELO to FIFA ranking and see how probabilities shift. Increase the simulation count for tighter confidence intervals. This is useful for comparing how different rating models value the same teams.
Understanding the Data Behind Simulations
The accuracy of any simulation depends on the quality of input data. Our simulator draws on three independent rating systems, each measuring team strength from a different angle. Using multiple sources helps reduce the bias inherent in any single metric.
FIFA World Ranking
The official ranking published by FIFA, updated after every international window. It uses a points-based formula that considers match result (win, draw, loss), match importance (friendly vs. World Cup qualifier vs. final tournament), strength of the opponent, and confederation strength. As of April 2026, Argentina holds the top spot with 1867.16 points, followed by France (1859.78) and Spain (1835.92). The FIFA ranking is widely cited by media but has known limitations: it can overweight friendlies and responds slowly to form changes because points decay gradually over a four-year cycle.
ELO Football Ratings
The ELO system, adapted from chess, rates teams based on actual match results weighted by goal difference, match importance, and opponent strength. Unlike FIFA's ranking, ELO adjusts after every single match and penalizes or rewards teams proportionally to the surprise factor of each result. A 1-0 win over the top-ranked team moves your rating more than a 1-0 win over the 100th-ranked team. As of April 2026, Argentina's ELO sits at approximately 2044, with Brazil at 2008 and France at 1991. ELO is generally considered more predictive because it focuses purely on competitive results and reacts faster to changes in team quality.
Weighted Mode (ELO + FIFA combined)
The simulator also offers a blended mode that combines both rating systems: 60% ELO and 40% FIFA ranking. This hedges against the weaknesses of either system alone. ELO can overweight recent friendlies, while FIFA ranking can underweight teams that play fewer matches. The blended mode tends to produce the most stable probability estimates across repeated simulation runs. There is also a pure random mode (50/50 for every match) useful for seeing what happens when team strength is ignored entirely — a useful baseline comparison.
What Can You Learn from 10,000 Simulations?
A single bracket prediction tells you one story. Ten thousand simulations tell you the full range of possible outcomes and how likely each one is. Here are the key outputs the simulator produces and what they mean for your World Cup analysis.
Win probability percentage
The headline number: how often each team wins the entire tournament across all simulations. This is not a guarantee — it is a statistical estimate. When the simulator says Brazil has a 12% chance of winning, it means that in 1,200 out of 10,000 simulated tournaments, Brazil lifted the trophy. The remaining 88% of the time, another team won. Even a team with 25% win probability loses three out of four times. This is why upsets are not just possible in football — they are mathematically expected.
Expected round of elimination
For each team, the simulator calculates the most likely round they exit the tournament. A mid-tier team might show 45% group exit, 30% Round of 32 exit, 15% Round of 16 exit, 8% Quarterfinal exit, and 2% deeper runs. This distribution is more informative than a single prediction because it shows the range of realistic outcomes. You can use this to evaluate whether a team is a realistic dark horse or whether their "underdog" narrative is statistically unfounded.
Most likely Final matchup
The simulator counts every Final pairing across all 10,000 runs and shows the most common matchups. In a 48-team tournament, even the most likely Final only occurs in a few percent of all simulations — roughly 1 in 24 times. This illustrates the enormous range of outcomes. The top 10 most likely Finals combined still account for less than 25% of all simulated tournaments.
Dark horse detection
Perhaps the most valuable output: which teams punch above their weight? The simulator identifies teams whose tournament performance exceeds their pre-tournament rating. A team ranked 20th by ELO that reaches the Quarterfinals in 18% of simulations (when their rating would predict 8%) signals a favorable draw, a weak group, or a bracket path that avoids the top seeds. These are the teams that offer the best value in bracket challenges and prediction pools.
Esempio pratico: come la posizione nel girone cambia tutto
Here is a worked example: run the simulation once with ELO ratings and once with the FIFA World Ranking, both at 10,000 runs. You will notice that some teams get very different results depending on the rating system — a team with high win probability in ELO mode might be rated significantly lower in FIFA mode, or vice versa. This difference shows how sensitive predictions are to the choice of rating model. The simulator helps you spot these model dependencies instead of blindly trusting a single ranking.
Simulator FAQ
What is a Monte Carlo simulation?+
A Monte Carlo simulation is a computational technique that uses repeated random sampling to estimate the probability of different outcomes. Named after the famous casino in Monaco, the method works by running a model thousands or millions of times with randomized inputs and then analyzing the distribution of results. In our World Cup simulator, each "run" plays through all tournament matches (72 group-stage + 31 knockout = 103 total) with randomized outcomes weighted by team strength ratings. After 10,000 runs, we count how often each team reaches each round to calculate probabilities. Monte Carlo methods are used widely in finance (portfolio risk), engineering (structural reliability), physics (particle interactions), and sports analytics. The key advantage is that they capture the full range of possible outcomes, including unlikely upsets and Cinderella runs that a single deterministic prediction would miss.
How accurate are the predictions?+
No prediction model can perfectly forecast a football tournament — the sport is inherently unpredictable, which is what makes it exciting. However, ELO-based Monte Carlo simulations have a strong track record in sports analytics. Studies comparing pre-tournament ELO predictions with actual World Cup results from 1998 to 2022 show that the eventual winner typically falls within the top 5 teams by pre-tournament win probability. The model correctly identifies the general tier of contenders but cannot predict individual match upsets. Our simulator is best used to understand the range of likely outcomes and to identify which teams have favorable or unfavorable bracket paths — not to predict a single exact bracket.
Can I change which teams are in each group?+
The simulator uses the official 2026 FIFA World Cup group draw completed on December 5, 2025 in Washington D.C. All 12 groups (A through L) with all 48 teams are confirmed. You cannot manually reassign teams between groups in this version, but you can explore different scenarios by using the Bracket Predictor, which lets you manually pick winners for every match.
How does ELO differ from FIFA ranking?+
The ELO system and FIFA World Ranking measure team strength using fundamentally different approaches. FIFA's ranking uses a points-based system where teams accumulate and lose points based on match results, with multipliers for match importance and opponent strength. Points decay over a four-year cycle. ELO, adapted from chess, treats every match as a direct comparison: each team has a single rating number, and after every match, the winner gains points and the loser loses points, with the transfer amount determined by the surprise factor of the result. Beating a much stronger team gains more points than beating a weaker one. In practice, ELO tends to be more responsive to recent form changes and more predictive of future results, while FIFA ranking is more conservative and influenced by the volume of matches played. For the 2026 World Cup, the two systems broadly agree on the top 5 teams but differ significantly in how they rank teams in the 10th-30th range.
How many simulations should I run?+
For casual exploration, 1,000 simulations run in seconds and give you a reasonable rough estimate of win probabilities. For reliable analysis where you want to compare scenarios or detect smaller differences between teams, 10,000 simulations is the sweet spot — it runs in under 10 seconds and produces stable probability estimates (typically within plus or minus 1 percentage point of the true value). For research-grade precision or when you need to distinguish between teams with very similar win probabilities, 100,000 simulations provides maximum accuracy but takes about 30-60 seconds. Beyond 100,000, the marginal improvement in precision is negligible. If you are comparing two scenarios (e.g., ELO vs. FIFA ranking), use the same simulation count for both to ensure a fair comparison.
Is this a betting tool?+
No. This simulator is an educational and entertainment tool designed for football fans, analysts, and bracket challenge participants. It does not provide betting advice, odds, or recommendations. While Monte Carlo simulations are a legitimate analytical technique used in sports analytics, the output of this simulator should not be used as the basis for placing wagers. Tournament outcomes are influenced by countless factors — injuries, tactical decisions, referee calls, weather, player psychology — that no rating-based model can fully capture. Use the simulator to deepen your understanding of the tournament structure, explore what-if scenarios, and have fun with your bracket predictions.