Ghana
- Coach
- Carlos Queiroz
- Elo (model)
- 1,510 world 94th
- Squad value
- €291M
- Power → Reality
- 39th 41st −0.00 pp · neutral draw
§ 01
The forecast
How far Ghana 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
Ghana — stage progression
Ghana is most likely eliminated before the knockout rounds: 36% to clear the group. Champion probability 0.00%.
§ 02
The group & the path
Group L advancement odds, the bracket half Ghana sits in, and the earliest round they could meet each leading side.
| Group L | Confed | Advance (top 2) | Reach R32 | |
|---|---|---|---|---|
| 1 | 🏴England | UEFA | 68.9% | 97.5% |
| 2 | 🇭🇷Croatia | UEFA | 47.0% | 90.3% |
| 3 | 🇬🇭Ghana | CAF | 6.7% | 36.0% |
| 4 | 🇵🇦Panama | CONCACAF | 6.7% | 34.8% |
Source · Oxford Football Forecasting model
Earliest possible meetings
No collision rows recorded for this team.
Collision = the earliest round the bracket wiring could pit Ghana against that side. Full bracket & collision matrix →
§ 03
Match by match
Ghana'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 Ghana. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where Ghana stands against the median of the 48-team field, metric by metric. The dot is Ghana; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
Ghana 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
Ghana on the decoupling axis
g = +0.34 ± 0.11: 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 | Lawrence Ati-Zigi | GK | St. Gallen | Super League −0.07z | 5,870 | 0 | 29 | 0 |
| 2 | Alidu Seidu | DF | Rennes | Ligue 1 +1.70z | 1,407 | 0 | 24 | 1 |
| 3 | Caleb Yirenkyi | MF | Nordsjælland | Superliga −0.53z | 2,614 | 2 | 11 | 1 |
| 4 | Jonas Adjetey | DF | VfL Wolfsburg | Bundesliga +1.84z | 137 | 0 | 10 | 0 |
| 5 | Thomas Partey | MF | Villarreal | La Liga +2.13z | 1,332 | 0 | 57 | 15 |
| 6 | Abdul Mumin | DF | Rayo Vallecano | La Liga +2.13z | 78 | 0 | 5 | 0 |
| 7 | Abdul Fatawu | FW | Leicester City | Championship +2.21z | 3,726 | 9 | 28 | 3 |
| 8 | Kwasi Sibo | MF | Oviedo | La Liga +2.13z | 1,809 | 0 | 8 | 0 |
| 9 | Jordan Ayew (captain) | FW | Leicester City | Championship +2.21z | 2,388 | 6 | 120 | 34 |
| 10 | Brandon Thomas-Asante | FW | Coventry City | Championship +2.21z | 1,991 | 13 | 8 | 1 |
| 11 | Antoine Semenyo | MF | Manchester City | Premier League +2.21z | 2,022 | 11 | 34 | 3 |
| 12 | Joseph Anang | GK | St Patrick's Athletic | — | — no club data | — | 1 | 0 |
| 13 | Christopher Bonsu Baah | FW | Al-Qadsiah | Pro League −0.86z | 2,679 | 3 | 9 | 0 |
| 14 | Gideon Mensah | DF | Auxerre | Ligue 1 +1.70z | 2,423 | 0 | 40 | 0 |
| 15 | Elisha Owusu | MF | Auxerre | Ligue 1 +1.70z | 2,353 | 0 | 20 | 0 |
| 16 | Benjamin Asare | GK | Hearts of Oak | — | — no club data | — | 11 | 0 |
| 17 | Abdul Rahman Baba | DF | PAOK | Super League 1 +0.03z | 2,748 | 3 | 51 | 1 |
| 18 | Jerome Opoku | DF | İstanbul Başakşehir | Süper Lig +0.49z | 2,884 | 1 | 11 | 1 |
| 19 | Iñaki Williams | FW | Athletic Bilbao | La Liga +2.13z | 2,888 | 4 | 26 | 2 |
| 20 | Augustine Boakye | MF | Saint-Étienne | Ligue 2 +1.70z | 2,746 | 5 | 0 | 0 |
| 21 | Kojo Peprah Oppong | DF | Nice | Ligue 1 +1.70z | 3,464 | 1 | 4 | 0 |
| 22 | Kamaldeen Sulemana | FW | Atalanta | Serie A +1.70z | 1,360 | 3 | 28 | 1 |
| 23 | Derrick Luckassen | DF | Pafos | 1. Division −0.31z | 1,350 | 1 | 1 | 0 |
| 24 | Ernest Nuamah | FW | Lyon | Ligue 1 +1.70z | 47 | 0 | 18 | 4 |
| 25 | Prince Kwabena Adu | FW | Viktoria Plzeň | — | — no club data | — | 5 | 0 |
| 26 | Marvin Senaya | DF | Auxerre | Ligue 1 +1.70z | 1,874 | 1 | 2 | 0 |
Source · Official squad announcements · API-Football (global club coverage). 3 of 26 players have no club season matched in API-Football — shown as “— no club data”, not imputed. Form coverage for this squad: 88%.
§ 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
225,756
7.0 per 1,000 of home population
Host-language familiarity
Shared
primary language English · spoken in a host
Climate adaptation gap
−1.0°C
home-vs-venue heat differential
Venue extremes
35°C
peak heat index · altitude up to 83 m
Travel
5h
max time-zone shift · nearest venue 8,035 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
Ghana's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
Ghana — Elo since 1950
Ghana ends the series at 1625 Elo, the world’s 94th-ranked side — below 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 Ghana, 3 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →