Portugal
- Coach
- Roberto Martínez
- Elo (model)
- 1,986 world 7th
- Squad value
- €1122M
- Power → Reality
- 6th 6th +0.14 pp · neutral draw
§ 01
The forecast
How far Portugal 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
Portugal — stage progression
On the central forecast, Portugal more likely than not reaches the Round of 16 (64%). Champion probability is 6.2% ± 0.08 pts.
§ 02
The group & the path
Group K advancement odds, the bracket half Portugal sits in, and the earliest round they could meet each leading side.
| Group K | Confed | Advance (top 2) | Reach R32 | |
|---|---|---|---|---|
| 1 | 🇵🇹Portugal | UEFA | 64.4% | 93.8% |
| 2 | 🇨🇴Colombia | CONMEBOL | 57.9% | 91.4% |
| 3 | 🇨🇩Congo DR | CAF | 10.8% | 40.2% |
| 4 | 🇺🇿Uzbekistan | AFC | 8.4% | 36.4% |
Source · Oxford Football Forecasting model
Earliest possible meetings
Collision = the earliest round the bracket wiring could pit Portugal against that side. Full bracket & collision matrix →
§ 03
Match by match
Portugal'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 Portugal. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where Portugal stands against the median of the 48-team field, metric by metric. The dot is Portugal; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
Portugal 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
Portugal on the decoupling axis
g = +0.75 ± 0.07: 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 | Diogo Costa | GK | Porto | Primeira Liga +1.14z | 7,160 | 0 | 42 | 0 |
| 2 | Nélson Semedo | DF | Fenerbahçe | Süper Lig +0.49z | 3,021 | 1 | 49 | 0 |
| 3 | Rúben Dias | DF | Manchester City | Premier League +2.21z | 3,087 | 2 | 75 | 3 |
| 4 | Tomás Araújo | DF | Benfica | Primeira Liga +1.14z | 2,618 | 1 | 4 | 0 |
| 5 | Diogo Dalot | DF | Manchester United | Premier League +2.21z | 2,797 | 1 | 34 | 3 |
| 6 | Matheus Nunes | MF | Manchester City | Premier League +2.21z | 4,303 | 1 | 19 | 2 |
| 7 | Cristiano Ronaldo (captain) | FW | Al-Nassr | Pro League −0.86z | 4,744 | 50 | 227 | 143 |
| 8 | Bruno Fernandes | MF | Manchester United | Premier League +2.21z | 4,101 | 13 | 88 | 29 |
| 9 | Gonçalo Ramos | FW | Paris Saint-Germain | Ligue 1 +1.70z | 1,730 | 12 | 24 | 10 |
| 10 | Bernardo Silva | MF | Manchester City | Premier League +2.21z | 4,254 | 5 | 108 | 14 |
| 11 | João Félix | FW | Al-Nassr | Pro League −0.86z | 3,274 | 24 | 53 | 12 |
| 12 | José Sá | GK | Wolverhampton Wanderers | — | — no club data | — | 5 | 0 |
| 13 | Renato Veiga | DF | Villarreal | La Liga +2.13z | 3,359 | 1 | 12 | 1 |
| 14 | Gonçalo Inácio | DF | Sporting CP | Primeira Liga +1.14z | 3,802 | 3 | 21 | 2 |
| 15 | João Neves | MF | Paris Saint-Germain | Ligue 1 +1.70z | 3,128 | 9 | 21 | 3 |
| 16 | Francisco Trincão | FW | Sporting CP | Primeira Liga +1.14z | 4,167 | 11 | 17 | 3 |
| 17 | Rafael Leão | FW | Milan | — | — no club data | — | 44 | 5 |
| 18 | Pedro Neto | FW | Chelsea | Premier League +2.21z | 4,837 | 16 | 24 | 2 |
| 19 | Gonçalo Guedes | FW | Real Sociedad | La Liga +2.13z | 2,321 | 9 | 34 | 8 |
| 20 | João Cancelo | DF | Barcelona | La Liga +2.13z | 1,448 | 2 | 67 | 12 |
| 21 | Rúben Neves | MF | Al-Hilal | Pro League −0.86z | 6,590 | 15 | 66 | 1 |
| 22 | Rui Silva | GK | Sporting CP | Primeira Liga +1.14z | 4,215 | 0 | 3 | 0 |
| 23 | Vitinha | MF | Paris Saint-Germain | Ligue 1 +1.70z | 4,512 | 7 | 37 | 0 |
| 24 | Samú Costa | DF | Mallorca | La Liga +2.13z | 2,808 | 7 | 5 | 0 |
| 25 | Nuno Mendes | DF | Paris Saint-Germain | Ligue 1 +1.70z | 2,994 | 6 | 43 | 1 |
| 26 | Francisco Conceição | FW | Juventus | Serie A +1.70z | 2,694 | 4 | 16 | 3 |
Source · Official squad announcements · API-Football (global club coverage). 2 of 26 players have no club season matched in API-Football — shown as “— no club data”, not imputed. Form coverage for this squad: 92%.
§ 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
342,103
32.0 per 1,000 of home population
Host-language familiarity
Foreign
primary language Portuguese
Climate adaptation gap
+4.9°C
home-vs-venue heat differential
Venue extremes
47°C
peak heat index · altitude up to 15 m
Travel
5h
max time-zone shift · nearest venue 5,157 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
Portugal's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
Portugal — Elo since 1950
Portugal ends the series at 2042 Elo, the world’s 7th-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 Portugal, 2 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →