Korea Republic v Czechia · Oxford Football Forecasting

🇰🇷 Korea Republic AFC Elo 1,758

33 / 31 / 36 win · draw · win most likely 1–1

🇨🇿 Czechia UEFA Elo 1,740

Group: A
Date: Friday 12 June 2026
Kick-off: 02:00 UTC
Venue: Guadalajara Stadium, Guadalajara

§ 01

The scoreline grid

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

Fig. V7 Ensemble · Group A

Korea Republic v Czechia — scoreline probabilities

Cells show P(exact scoreline); the right column and bottom row are the marginal totals P(Korea Republic scores k) and P(Czechia 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 Czechia favourites at 35.9%, with a 30.6% draw. The single most-likely scoreline is 1–1 (14.3%), 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

33.5% 30.6% 35.9%

🇰🇷 Korea Republic 33.5% Draw 30.6% 🇨🇿 Czechia 35.9%

Rounded values sum to exactly 100%.

Expected goals (λ)

🇰🇷Korea Republic 1.12

🇨🇿Czechia 1.17

Poisson means feeding the grid; combined expected goals 2.29.

40.2% Over 2.5 goals P(3 or more goals in the match)

59.8% Under 2.5 goals complement of over-2.5

47.5% Both teams to score P(each side scores ≥ 1)

1–1 Most-likely scoreline modal exact score · 14.3%

§ 03

Venue context

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

Akron Guadalajara, Mexico

Heat index 30°C apparent temperature (June–July)

Max temperature 28°C June–July daily high

Humidity 71% relative humidity

Altitude 1,671m high-altitude venue

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.

1,758 Elo rating 1,740

1.87 Recent NT form 2.07

€202M Squad value €225M

0.160 Squad form (global) 0.268

0.701 Fitness readiness 0.779

−0.23 Decoupling g +0.06

The sides are close on Elo (18 points apart). On the decoupling axis, Czechia 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 →