Japan v Sweden · Oxford Football Forecasting

🇯🇵 Japan AFC Elo 1,906 · world 11th

48 / 29 / 23 win · draw · win most likely 1–1

🇸🇪 Sweden UEFA Elo 1,712 · world 53rd

Group: F
Date: Thursday 25 June 2026
Kick-off: 23:00 UTC
Venue: Dallas Stadium, Arlington

§ 01

The scoreline grid

The ensemble's full distribution over exact scorelines — Japan goals down the side, Sweden goals across the top. This is the same 11×11 grid the tournament simulator samples.

Fig. V7 Ensemble · Group F

Japan v Sweden — scoreline probabilities

Cells show P(exact scoreline); the right column and bottom row are the marginal totals P(Japan scores k) and P(Sweden scores k). Grid runs 0–7 goals per side; the 8–10-goal tail holds 0.01% of the mass and is omitted from the cells (not from the totals).

The grid makes Japan favourites at 48.0%, with a 29.2% draw. The single most-likely scoreline is 1–1 (13.6%), but no exact score clears 14% — the distribution is broad, as it should be.

Source · Oxford Football Forecasting model

§ 02

Result, goals & totals

The grid marginalised into the outcome split, expected goals each side, and the goal-total markets — every figure read straight off the same distribution.

Win · draw · loss

48% 29.2% 22.8%

🇯🇵 Japan 48% Draw 29.2% 🇸🇪 Sweden 22.8%

Rounded values sum to exactly 100%.

Expected goals (λ)

🇯🇵Japan 1.40

🇸🇪Sweden 0.89

Poisson means feeding the grid; combined expected goals 2.30.

40.3% Over 2.5 goals P(3 or more goals in the match)

59.7% Under 2.5 goals complement of over-2.5

45.5% Both teams to score P(each side scores ≥ 1)

1–1 Most-likely scoreline modal exact score · 13.6%

§ 03

Venue context

The conditions at Dallas Stadium, Arlington — the same environment layer the dossiers' climate exposure draws on.

AT&T Arlington, USA

Heat index 45°C apparent temperature (June–July)

Max temperature 35°C June–July daily high

Humidity 62% relative humidity

Altitude 177m above sea level

Source · Open-Meteo & venue records. Travel and time-zone exposure are per-team — see each side's dossier.

§ 04

Why the model leans this way

The inputs behind the grid — each side's strength signals laid side by side. The forecast is the ensemble's, not a hand-weighting of these; this panel is the descriptive read.

1,906 Elo rating 1,712

2.20 Recent NT form 1.40

€384M Squad value €414M

0.208 Squad form (global) 0.204

0.753 Fitness readiness 0.741

−0.19 Decoupling g +0.41

Japan carry the Elo edge (194 points). On the decoupling axis, Sweden is the side whose squad is valued higher relative to its record.

How a single-match forecast is built

The pairing is scored by the ensemble — Dixon-Coles bivariate-Poisson, the Bayesian hierarchical model and the global LightGBM-Poisson, log-pooled — yielding the 11×11 scoreline grid above. Win/draw/loss, expected goals (λ), over-2.5 and both-teams-to-score are all marginals of that one grid, so they are mutually consistent by construction. The strength inputs shown here feed the models; the forecast is their pooled output, not a manual weighting of these rows. The model matches the market out-of-sample (RPS 0.1891 vs 0.1905); it does not significantly beat it at n = 3. The ensemble, in full →