Ecuador v Germany · Oxford Football Forecasting

🇪🇨 Ecuador CONMEBOL Elo 1,938 · world 8th

29 / 31 / 40 win · draw · win most likely 1–1

🇩🇪 Germany UEFA Elo 1,932 · world 10th

Group: E
Date: Thursday 25 June 2026
Kick-off: 20:00 UTC
Venue: New York/New Jersey Stadium, East Rutherford

§ 01

The scoreline grid

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

Fig. V7 Ensemble · Group E

Ecuador v Germany — scoreline probabilities

Cells show P(exact scoreline); the right column and bottom row are the marginal totals P(Ecuador scores k) and P(Germany scores k). Grid runs 0–7 goals per side; the 8–10-goal tail holds 0.00% of the mass and is omitted from the cells (not from the totals).

The grid makes Germany favourites at 39.9%, with a 30.7% 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

29.4% 30.7% 39.9%

🇪🇨 Ecuador 29.4% Draw 30.7% 🇩🇪 Germany 39.9%

Rounded values sum to exactly 100%.

Expected goals (λ)

🇪🇨Ecuador 1.02

🇩🇪Germany 1.23

Poisson means feeding the grid; combined expected goals 2.25.

39.1% Over 2.5 goals P(3 or more goals in the match)

60.9% Under 2.5 goals complement of over-2.5

46.3% 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 New York/New Jersey Stadium, East Rutherford — the same environment layer the dossiers' climate exposure draws on.

MetLife East Rutherford, USA

Heat index 31°C apparent temperature (June–July)

Max temperature 28°C June–July daily high

Humidity 70% relative humidity

Altitude 9m 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.

1,938 Elo rating 1,932

1.80 Recent NT form 2.13

€290M Squad value €1114M

0.158 Squad form (global) 0.308

0.710 Fitness readiness 0.815

−0.55 Decoupling g +0.16

The sides are close on Elo (6 points apart). On the decoupling axis, Germany 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 →