WC 2026 · Forecasting Oxford Football Forecasting

Interactive · the forecast in your hands

Explore the field

Two instruments, one locked forecast. Put any two of the 48 teams head-to-head on a neutral field, or pull a single slider to watch the draw reshape the title race. Every number here was computed once, in the locked pipeline, and is read back exactly — nothing on this page re-runs the simulation.

Fig. X1 Neutral venue · locked ensemble

Head-to-head, on a neutral field

Win / draw / win, expected goals, the most-likely scorelines, the goal markets, a side-by-side strength read, and the soonest the bracket could put these two together. Change either side to recompute.

Argentina CONMEBOL · Group J · Power #1
Spain UEFA · Group H · Power #2

Neutral-venue result

34.7% Argentina 32% draw 33.3% Spain

Most likely scoreline 1–1 (14.6%), Argentina first.

Expected goals & goal markets

1.07 Argentina xG
1.05 Spain xG
36% over 2.5 goals 44% both teams score 100% of max uncertainty

Most-likely scorelines

1–1 14.6%
0–0 13.1%
1–0 11.8%
0–1 11.5%
2–1 7.2%

Top five exact scorelines from the neutral 11×11 grid. Bars shaded by result: Argentina win · draw · Spain win.

Strength profile, side by side

2114 Elo rating 2155
2.47 Form · last 15 (ppg) 2.20
€946M Squad value €1580M
0.330 Squad club form 0.309
0.785 Squad fitness 0.841
0.057 Familiarity 0.114
35 Mean caps 25
+0.21 History vs squad · g+ = squad valued above record −0.18

Bars are each metric scaled to the larger of the two sides; raw values are labelled. Source · Oxford Football Forecasting model — per-team dossiers.

Where the draw could pit them together

R32

The earliest the bracket can pit Argentina against Spain is the Round of 32 — and only if the draw breaks that way. This is the soonest their two possible paths can cross, not a prediction that they will.

1st(1J) vs 2nd(2H) (R32 tie 13: 1J vs 2H)

A neutral-venue meeting strips out home advantage — it is the cleanest 'who is better, right now' question, and the same neutral grid the simulator uses for every knockout tie.

Source · Oxford Football Forecasting model — log-opinion pool of Dixon-Coles, the global gradient booster and the Bayesian hierarchical model, fit on international results 1872→2026.
What this comparison is — and what it is not

Each cell is the locked ensemble's forecast for that one pairing at a neutral venue: the per-cell log-opinion pool of the Dixon-Coles bivariate-Poisson model, the global LightGBM-Poisson and the Bayesian hierarchical model, marginalised from the same 11×11 scoreline grid the tournament simulator consumes. Because it is neutral, it deliberately drops host advantage — so for a group game a host actually plays at home, the live fixture card will differ by exactly that bump. The strength rows are read straight from each nation's dossier; “where they could meet” is pure bracket geometry — the earliest stage the actual draw allows these two to face off, taken over every way each side can qualify (1st, 2nd or one of the eight best thirds). It is a possibility, not a probability. For the realised odds of reaching a round, see the team’s own forecast funnel.

This is an illustration, not a re-simulation. The two endpoints are real, locked outputs; the in-between is a straight interpolation, p(w) = (1−w)·Power + w·Reality, renormalised to sum to 100%. It shows how far the draw moves each team — it does not re-run the 1.1M tournaments, and no blend other than the two endpoints is a model output.

Fig. X2 Champion odds · interpolated between two locked rankings

From Power to Reality

At the far left, the field as raw strength alone would seed it. At the far right, the same field after the actual draw — softer or harder paths, balanced or stacked halves. The arrows mark each team's rank move between the two.

100% Reality / 0% Powerpure fixture-aware Reality (the locked forecast)

1 Argentina 16.5%
2 Spain 16.0%
3 Brazil 9.0%
4 England ▲1 9.0%
5 France ▼1 8.9%
6 Portugal 6.2%
7 Netherlands 4.9%
8 Colombia 4.1%
9 Germany 3.9%
10 Belgium ▲1 2.5%
11 Norway ▼1 2.4%
12 Morocco ▲1 2.0%
13 Ecuador ▼1 1.9%
14 Croatia ▲1 1.8%
15 Switzerland ▲1 1.7%
16 Japan ▼2 1.6%

Showing the top 16 of 48; the long tail is at or near zero either way. Arrows compare each team's Reality rank with its Power rank.

The draw is close to fair, so most teams barely move — but it is not perfectly fair: England climbs 1 place on a kinder path while France slips 1. That reshuffle is the whole point of keeping two rankings, not one.

Source · Oxford Football Forecasting model — Power (pre-draw) and Reality (post-draw) champion odds, each summing to 100% across the 48 teams; draw-luck is the gap.
Why two rankings, and why only interpolate them

Power is the champion probability from simulating the bracket with every team in its own group but the draw re-randomised a million times — strength with the luck of the draw averaged out. Reality is the locked forecast: the actual 2026 draw, simulated as it stands. The gap between them is draw-luck — positive for a team the bracket favours, negative for one it punishes. Interpolating between the two is a faithful way to see that gap grow from zero; it is not a third model, and the page never presents the midpoint as a forecast — only the two endpoints are model outputs. The real re-draw experiment — a genuine million-simulation resampling — already happened in the pipeline and is what produces the Power column you are sliding to.