Live-Prognose

Snapshot · 2026-06-10Model 1.0.0

Die vollständige WM-2026-Prognose

Alle Übersichten, die das Modell erstellt: voraussichtliche Aufstellungen, Gruppensieg-Wahrscheinlichkeiten, der K.-o.-Ausblick und die Turniersieg-Tabelle.

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Aktuelle Beiträge und grundlegende Methodik-Dokumente.

Erling Haaland during a Champions League match, the consensus favourite to top the scorer charts
Post11 Jun 2026

Five places the model disagrees with the consensus

Models don't know narratives. They read results, schedules, and xG rates. Here are five places ours diverges most from the consensus, from Ecuador over Germany to Raphinha as the #1 anytime scorer, Iran at 81%, Spain and Argentina pulling away, and the USA as the underdog in every group match at home.

Argentina's Julián Álvarez celebrates while Lionel Messi runs toward the goal after scoring against Mexico at the 2022 FIFA World Cup in Qatar. Mexico's Héctor Moreno watches as the goalkeeper lies beaten.
Post11 Jun 2026

Argentina and Spain: 0.6 points apart, nothing else in common

The model's two most likely World Cup winners sit at 17.5% and 16.9%, a gap well inside simulation noise. They get there via opposite paths. Argentina runs through the best defensive rating in the field and a penalty advantage worth 5 percentage points on its own; Spain runs through attacking volume and a Barcelona spine. Both teams' nearest historical analogues exited earlier than expected.

Aerial view of Estadio Azteca in Mexico City, venue for the 2026 World Cup opening match
Post11 Jun 2026

Why prediction markets keep underrating World Cup draws

Prediction markets, including Polymarket, consistently compress draw probabilities in World Cup openers. The model disagrees. Here's why the structure of prediction markets makes draws hard to price correctly, and what the numbers say about today's two Group A matches.

Post10 Jun 2026

The model never stops predicting. Here's the number we grade ourselves on

The model retrains nightly and its published probabilities move by the hour. The rows it gets graded on do not. Every group-stage forecast froze this morning, at least 24 hours before kickoff; a second freeze pins the published number three hours before each match; both land in public JSON files; and the Internet Archive holds receipts that the numbers came first.

Post9 Jun 2026

Brazil vs Morocco is a coin-flip. The model has it 50–30–20.

Our model gives Brazil a 50.1% probability of winning their Group C opener against Morocco — essentially a coin-flip between Brazil winning and not-winning. Morocco, the first African nation to reach a World Cup semifinal, is rated far closer to Brazil than most people expect. The group picture tells the rest of the story.

Luka Modrić wearing Croatia's dark-check away kit during the 2018 FIFA World Cup
Post8 Jun 2026

Luka Modrić was six years old when his grandfather was killed and his family fled. He's 40 now. This is his last World Cup.

In 1991, six-year-old Luka Modrić became a refugee. In 2018, he dragged a nation of four million to the World Cup final and won the Ballon d'Or. In 2026, at 40, he will captain Croatia one last time — opening against England, the team he beat in that 2018 semifinal. The arc of a career that started in a hotel parking lot in Zadar.

Research

How match previews work

Every fixture page on the site opens with a detailed match preview — predicted formations, key players, strategic factors, and expected scorelines. Here's how we generate them and what data feeds into

Research

How our 2026 World Cup prediction model works

Our 2026 FIFA World Cup forecasts come from a statistical prediction model that blends three approaches — an Elo rating system, a Dixon-Coles Poisson goals model, and a hierarchical Poisson model — in

Research

How We Rate Team Strength

How do we figure out which teams are strongest and most likely to win any given match? Our model considers two main approaches. **Goal-based models** simulate how many goals each side will score, then

Alle Beiträge →Alle Methodikdokumente →

Voraussichtliche Aufstellungen

Die 8 Nationen, denen das Modell die höchste Turniersieg-Wahrscheinlichkeit gibt. Klicken Sie auf eine Karte für den vollständigen Kader.

Alle 48 Nationen ansehen →Alle Spieler durchsuchen →

Erzählstränge im Blick

Drei erzählerische Blickwinkel pro Top-Team: Verletzungen, prognostizierte Torschützen, Kadererfahrung.

Spain16.9%
Club core

8 of 26 predicted-squad players play their club football for Barcelona — a single-club spine on the international side.

Club xG

Squad averages 1.85 xG per match across club football last season — #3 of 20 in the field for attacking pedigree from each player's domestic side (23 of 26 players matched to a known club).

Argentina16.8%
TouchlineLionel Scaloni

Defending champion — Winner 2022.

Last danceLionel Messi

38 at kickoff with 198 caps — probably his final World Cup.

Brazil9.7%
Top scorerGabriel Jesus

Model's top anytime-scorer for the team — 32% probability of scoring at least once, rank #4 of all players.

Teen starterEndrick

19 at kickoff — 15 caps — projected on the bench, the squad's youngest pick.

France9.1%
Out injuredKylian Mbappé

Torn muscle fiber, no expected return. Composite 0.99 — would have been a likely starter.

TouchlineDidier Deschamps

Defending champion — Winner 2022.

Portugal7.2%

41 at kickoff with 226 caps — probably his final World Cup.

Top scorerGonçalo Ramos

Model's top anytime-scorer for the team — 30% probability of scoring at least once, rank #6 of all players.

England6.5%
Out injuredTino Livramento

Thigh problems, no expected return. Composite 0.94 — would have been a likely starter.

Defensive form

Conceded only 0.44 xG per match across 11 recent internationals — #2 of 35 in the field for defensive solidity.

Colombia4.4%
Strong in goalDavid Ospina

#1 starting-GK rating in the field — 1.00 on club-derived save metrics across 48 teams.

Takes corners, free kicks, and penalties — the team's dead-ball threat.

Group D is the tightest race — Turkey at 31%, United States at 28%

Wahrscheinlichkeit, dass jedes Team seine Gruppe gewinnt.

UEFACONMEBOLCONCACAFAFCCAFOFC★ host nation

Bars are sized relative to each group's leader.

Argentina leads the field at 17.5%, narrowly ahead of Spain (16.9%)

Runde für Runde die Favoriten und die Turniersieg-Wahrscheinlichkeiten des Modells.

Per-round Monte Carlo reach-probabilities are a follow-up — the figures above are the model's tournament-winner and group-winner probabilities used as a proxy ordering.

Who wins the 2026 World Cup?

Top 12 · model probability
Argentina#1
17.5%
Spain#2
16.9%
Brazil#3
9.7%
France#4
9.0%
Portugal#5
7.5%
England#6
6.3%
Germany#7
5.1%
Colombia#8
4.4%
Belgium#10
3.0%
Croatia#11
2.6%
Uruguay#12
2.4%
Probabilities are statistical model outputs. See methodology for how the is fit, calibrated, and back-tested.
Die vollständige WM-2026-Prognose: Gruppen, K.-o.-Runde & Aufstellungen · onthepitch