Switzerland v Bosnia and Herzegovina · Oxford Football Forecasting

🇨🇭 Switzerland UEFA Elo 1,891 · world 19th

62 / 24 / 14 win · draw · win most likely 1–0

🇧🇦 Bosnia and Herzegovina UEFA Elo 1,595 · world 86th

Group: B
Date: Thursday 18 June 2026
Kick-off: 19:00 UTC
Venue: Los Angeles Stadium, Inglewood

§ 01

The scoreline grid

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

Fig. V7 Ensemble · Group B

Switzerland v Bosnia and Herzegovina — scoreline probabilities

Cells show P(exact scoreline); the right column and bottom row are the marginal totals P(Switzerland scores k) and P(Bosnia and Herzegovina scores k). Grid runs 0–7 goals per side; the 8–10-goal tail holds 0.05% of the mass and is omitted from the cells (not from the totals).

The grid makes Switzerland favourites at 62.2%, with a 24.2% draw. The single most-likely scoreline is 1–0 (13.9%), 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

62.2% 24.2% 13.6%

🇨🇭 Switzerland 62.2% Draw 24.2% 🇧🇦 Bosnia and Herzegovina 13.6%

Rounded values sum to exactly 100%.

Expected goals (λ)

🇨🇭Switzerland 1.78

🇧🇦Bosnia and Herzegovina 0.71

Poisson means feeding the grid; combined expected goals 2.49.

45.4% Over 2.5 goals P(3 or more goals in the match)

54.6% Under 2.5 goals complement of over-2.5

43.1% Both teams to score P(each side scores ≥ 1)

1–0 Most-likely scoreline modal exact score · 13.9%

§ 03

Venue context

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

SoFi Inglewood, USA

Heat index 29°C apparent temperature (June–July)

Max temperature 27°C June–July daily high

Humidity 71% relative humidity

Altitude 45m 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.

1,891 Elo rating 1,595

1.93 Recent NT form 1.67

€336M Squad value €118M

0.210 Squad form (global) 0.219

0.804 Fitness readiness 0.732

+0.21 Decoupling g −0.15

Switzerland carry the Elo edge (296 points). On the decoupling axis, Switzerland 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 →