Norway
- Coach
- Ståle Solbakken home · Norwegian
- Elo (model)
- 1,914 world 15th
- Squad value
- €580M
- Power → Reality
- 10th 11th −0.11 pp · neutral draw
§ 01
The forecast
How far Norway goes — the survival probability at each stage of the bracket, from the tournament Monte-Carlo simulation. Each bar carries its ±1.96·MC-SE interval.
Fig. D1 Fixture-aware · 100k sims
Norway — stage progression
On the central forecast, Norway more likely than not reaches the Round of 16 (51%). Champion probability is 2.4% ± 0.05 pts.
§ 02
The group & the path
Group I advancement odds, the bracket half Norway sits in, and the earliest round they could meet each leading side.
| Group I | Confed | Advance (top 2) | Reach R32 | |
|---|---|---|---|---|
| 1 | 🇫🇷France | UEFA | 68.1% | 95.2% |
| 2 | 🇳🇴Norway | UEFA | 50.8% | 87.7% |
| 3 | 🇸🇳Senegal | CAF | 30.1% | 69.3% |
| 4 | 🇮🇶Iraq | AFC | 3.6% | 17.6% |
Source · Oxford Football Forecasting model
Earliest possible meetings
No collision rows recorded for this team.
Collision = the earliest round the bracket wiring could pit Norway against that side. Full bracket & collision matrix →
§ 03
Match by match
Norway's three group fixtures, each with the predicted win / draw / loss split and the single most-likely scoreline. Probabilities are this team's own orientation; they sum to 100%.
How a match forecast is built
Each pairing is scored by the ensemble (Dixon-Coles bivariate-Poisson, the Bayesian hierarchical model and the global LightGBM-Poisson, log-pooled), producing an 11×11 scoreline grid that is marginalised into win/draw/loss, expected goals (λ), over/under 2.5 and both-teams-to-score. These are the same distributions the tournament simulator consumes, oriented here to Norway. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where Norway stands against the median of the 48-team field, metric by metric. The dot is Norway; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
Norway vs the field
Read each row as a multiple of the field median: dots to the right of the dashed line are above-field, to the left below. Raw values are labelled on the right so the comparison is transparent.
§ 05
History vs squad
The decoupling residual g — whether the squad’s market value sits above, or below, what the team’s record predicts.
Fig. D3 Bayesian projection residual g
Norway on the decoupling axis
g = +0.24 ± 0.08: the squad is valued above its record — the transfer market rates this side above what its results have earned.
What g means — and its limits
g is the residual from regressing a team’s current squad market value on its
history-based strength in the Bayesian hierarchical model. Positive g
means the squad is valued above what the team’s record predicts; negative means the
record outruns the squad’s price (the side achieves more than its market value implies).
Regressed on out-of-sample success the slope is positive — squad-rich sides go a touch
further — but not statistically significant at n = 3 tournaments, so treat
a single team’s g as a descriptive read, not a hard prediction.
The full decoupling essay →
§ 06
The squad
All 26 selected players — club, league (with relative strength), club-season minutes and goals, caps. Sort any column.
| # | Player | Pos | Club | League | Club min | Gls | Caps | NT gls |
|---|---|---|---|---|---|---|---|---|
| 1 | Ørjan Nyland | GK | Sevilla | La Liga +2.13z | 540 | 0 | 71 | 0 |
| 2 | Morten Thorsby | MF | Cremonese | Serie A +1.70z | 644 | 1 | 31 | 0 |
| 3 | Kristoffer Ajer | DF | Brentford | Premier League +2.21z | 2,155 | 0 | 52 | 2 |
| 4 | Leo Østigård | DF | Genoa | Serie A +1.70z | 2,644 | 5 | 38 | 1 |
| 5 | David Møller Wolfe | DF | Wolverhampton Wanderers | — | — no club data | — | 22 | 1 |
| 6 | Patrick Berg | MF | Bodø/Glimt | Eliteserien −0.13z | 3,591 | 5 | 43 | 0 |
| 7 | Alexander Sørloth | FW | Atlético Madrid | La Liga +2.13z | 2,919 | 20 | 72 | 26 |
| 8 | Sander Berge | MF | Fulham | Premier League +2.21z | 3,028 | 0 | 66 | 1 |
| 9 | Erling Haaland | FW | Manchester City | Premier League +2.21z | 4,473 | 42 | 50 | 55 |
| 10 | Martin Ødegaard (captain) | MF | Arsenal | Premier League +2.21z | 2,315 | 1 | 68 | 5 |
| 11 | Jørgen Strand Larsen | FW | Crystal Palace | Premier League +2.21z | 1,376 | 4 | 28 | 6 |
| 12 | Sander Tangvik | GK | Hamburger SV | Bundesliga +1.84z | 90 | 0 | 0 | 0 |
| 13 | Egil Selvik | GK | Watford | Championship +2.21z | 3,645 | 0 | 7 | 0 |
| 14 | Fredrik Aursnes | MF | Benfica | Primeira Liga +1.14z | 4,425 | 4 | 22 | 1 |
| 15 | Fredrik André Bjørkan | DF | Bodø/Glimt | Eliteserien −0.13z | 3,474 | 3 | 21 | 1 |
| 16 | Marcus Holmgren Pedersen | DF | Torino | Serie A +1.70z | 2,341 | 1 | 32 | 0 |
| 17 | Torbjørn Heggem | DF | Bologna | Serie A +1.70z | 2,885 | 0 | 15 | 0 |
| 18 | Kristian Thorstvedt | MF | Sassuolo | Serie A +1.70z | 2,480 | 4 | 37 | 4 |
| 19 | Thelo Aasgaard | MF | Rangers | Premiership −0.28z | 2,351 | 7 | 8 | 5 |
| 20 | Antonio Nusa | FW | RB Leipzig | Bundesliga +1.84z | 2,320 | 5 | 24 | 8 |
| 21 | Andreas Schjelderup | MF | Benfica | Primeira Liga +1.14z | 2,575 | 11 | 12 | 1 |
| 22 | Oscar Bobb | MF | Fulham | Premier League +2.21z | 754 | 0 | 20 | 2 |
| 23 | Jens Petter Hauge | MF | Bodø/Glimt | Eliteserien −0.13z | 3,392 | 14 | 15 | 1 |
| 24 | Sondre Langås | DF | Derby County | Championship +2.21z | 2,058 | 3 | 3 | 0 |
| 25 | Henrik Falchener | DF | Viking | Eliteserien −0.13z | 2,926 | 6 | 1 | 0 |
| 26 | Julian Ryerson | FW | Borussia Dortmund | Bundesliga +1.84z | 3,806 | 0 | 43 | 1 |
Source · Official squad announcements · API-Football (global club coverage). 1 of 26 players have no club season matched in API-Football — shown as “— no club data”, not imputed. Form coverage for this squad: 96%.
§ 07
Tournament context
The host-nation environment this team meets — diaspora support, climate and altitude exposure at their venues, language familiarity.
Diaspora in the hosts
22,433
4.0 per 1,000 of home population
Host-language familiarity
Foreign
primary language Norwegian Nynorsk
Climate adaptation gap
+1.2°C
home-vs-venue heat differential
Venue extremes
31°C
peak heat index · altitude up to 83 m
Travel
6h
max time-zone shift · nearest venue 5,651 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
Norway's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
Norway — Elo since 1950
Norway ends the series at 1971 Elo, the world’s 15th-ranked side — above the qualified-field median.
Which Elo is this?
This line is the public eloratings.net series (year-end ratings), which terminates exactly at the current rating and world rank shown on the marker. It is a different number from the Elo shown in the header band (a panel-normalised rating used inside the forecast); the two are ~0.99 correlated but on different scales. We keep them distinct rather than blend them.
§ 09
Data coverage
Validated on n=3 held-out tournaments; coverage below 1.0 means part of this squad's club-form/fitness is imputed (the global de-biasing layer). For Norway, 1 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →