Belgium
- Coach
- Rudi Garcia foreign · French
- Elo (model)
- 1,893 world 18th
- Squad value
- €613M
- Power → Reality
- 11th 10th +0.41 pp · soft draw
§ 01
The forecast
How far Belgium 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
Belgium — stage progression
On the central forecast, Belgium more likely than not reaches the Round of 16 (62%). Champion probability is 2.5% ± 0.05 pts.
§ 02
The group & the path
Group G advancement odds, the bracket half Belgium sits in, and the earliest round they could meet each leading side.
| Group G | Confed | Advance (top 2) | Reach R32 | |
|---|---|---|---|---|
| 1 | 🇧🇪Belgium | UEFA | 61.9% | 93.9% |
| 2 | 🇮🇷IR Iran | AFC | 39.5% | 79.4% |
| 3 | 🇪🇬Egypt | CAF | 28.1% | 67.6% |
| 4 | 🇳🇿New Zealand | OFC | 6.0% | 27.6% |
Source · Oxford Football Forecasting model
Earliest possible meetings
No collision rows recorded for this team.
Collision = the earliest round the bracket wiring could pit Belgium against that side. Full bracket & collision matrix →
§ 03
Match by match
Belgium'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 Belgium. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where Belgium stands against the median of the 48-team field, metric by metric. The dot is Belgium; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
Belgium 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
Belgium on the decoupling axis
g = +0.29 ± 0.06: 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 | Thibaut Courtois | GK | Real Madrid | La Liga +2.13z | 4,545 | 0 | 109 | 0 |
| 2 | Zeno Debast | DF | Sporting CP | Primeira Liga +1.14z | 1,451 | 0 | 26 | 1 |
| 3 | Arthur Theate | DF | Eintracht Frankfurt | Bundesliga +1.84z | 2,983 | 1 | 33 | 1 |
| 4 | Brandon Mechele | DF | Club Brugge | Jupiler Pro League −0.07z | 4,700 | 7 | 9 | 1 |
| 5 | Maxim De Cuyper | DF | Brighton & Hove Albion | Premier League +2.21z | 1,510 | 2 | 19 | 4 |
| 6 | Axel Witsel | MF | Girona | La Liga +2.13z | 2,533 | 1 | 138 | 12 |
| 7 | Kevin De Bruyne | MF | Napoli | Serie A +1.70z | 1,360 | 5 | 119 | 37 |
| 8 | Youri Tielemans (captain) | MF | Aston Villa | Premier League +2.21z | 3,029 | 2 | 85 | 13 |
| 9 | Romelu Lukaku | FW | Napoli | Serie A +1.70z | 74 | 1 | 126 | 90 |
| 10 | Leandro Trossard | FW | Arsenal | Premier League +2.21z | 2,976 | 10 | 51 | 12 |
| 11 | Jérémy Doku | FW | Manchester City | Premier League +2.21z | 3,464 | 12 | 43 | 7 |
| 12 | Senne Lammens | GK | Manchester United | Premier League +2.21z | 2,970 | 0 | 2 | 0 |
| 13 | Mike Penders | GK | Strasbourg | Ligue 1 +1.70z | 4,639 | 0 | 0 | 0 |
| 14 | Dodi Lukébakio | FW | Benfica | Primeira Liga +1.14z | 1,087 | 0 | 30 | 6 |
| 15 | Thomas Meunier | DF | Lille | Ligue 1 +1.70z | 2,734 | 2 | 80 | 10 |
| 16 | Koni De Winter | DF | Milan | — | — no club data | — | 8 | 0 |
| 17 | Charles De Ketelaere | FW | Atalanta | Serie A +1.70z | 3,036 | 5 | 30 | 6 |
| 18 | Joaquin Seys | DF | Club Brugge | Jupiler Pro League −0.07z | 5,671 | 6 | 5 | 0 |
| 19 | Diego Moreira | MF | Strasbourg | Ligue 1 +1.70z | 5,509 | 7 | 3 | 0 |
| 20 | Hans Vanaken | MF | Club Brugge | Jupiler Pro League −0.07z | 8,207 | 25 | 34 | 7 |
| 21 | Timothy Castagne | DF | Fulham | Premier League +2.21z | 2,401 | 0 | 63 | 2 |
| 22 | Alexis Saelemaekers | MF | Milan | — | — no club data | — | 24 | 2 |
| 23 | Nicolas Raskin | MF | Rangers | Premiership −0.28z | 5,161 | 6 | 13 | 2 |
| 24 | Amadou Onana | MF | Aston Villa | Premier League +2.21z | 2,723 | 2 | 29 | 1 |
| 25 | Nathan Ngoy | DF | Lille | Ligue 1 +1.70z | 3,476 | 3 | 4 | 0 |
| 26 | Matias Fernandez-Pardo | FW | Lille | Ligue 1 +1.70z | 3,106 | 8 | 2 | 0 |
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
52,097
4.0 per 1,000 of home population
Host-language familiarity
Shared
primary language German · spoken in a host
Climate adaptation gap
−2.7°C
home-vs-venue heat differential
Venue extremes
29°C
peak heat index · altitude up to 45 m
Travel
8h
max time-zone shift · nearest venue 5,614 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
Belgium's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
Belgium — Elo since 1950
Belgium ends the series at 1956 Elo, the world’s 18th-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 Belgium, 2 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →