England
- Coach
- Thomas Tuchel foreign · German
- Elo (model)
- 2,021 world 4th
- Squad value
- €1878M
- Power → Reality
- 5th 4th +0.23 pp · soft draw
§ 01
The forecast
How far England 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
England — stage progression
On the central forecast, England more likely than not reaches the Round of 16 (69%). Champion probability is 9.0% ± 0.09 pts.
§ 02
The group & the path
Group L advancement odds, the bracket half England 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
Collision = the earliest round the bracket wiring could pit England against that side. Full bracket & collision matrix →
§ 03
Match by match
England'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 England. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where England stands against the median of the 48-team field, metric by metric. The dot is England; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
England 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
England on the decoupling axis
g = −0.01 ± 0.10: squad market value and recent record are closely aligned.
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 | Jordan Pickford | GK | Everton | Premier League +2.21z | 4,452 | 0 | 83 | 0 |
| 2 | Ezri Konsa | DF | Aston Villa | Premier League +2.21z | 4,557 | 2 | 19 | 1 |
| 3 | Nico O'Reilly | DF | Manchester City | Premier League +2.21z | 4,148 | 9 | 4 | 0 |
| 4 | Declan Rice | MF | Arsenal | Premier League +2.21z | 4,648 | 5 | 72 | 6 |
| 5 | John Stones | DF | Manchester City | Premier League +2.21z | 1,154 | 0 | 88 | 3 |
| 6 | Marc Guéhi | DF | Manchester City | Premier League +2.21z | 1,690 | 2 | 28 | 1 |
| 7 | Bukayo Saka | FW | Arsenal | Premier League +2.21z | 3,493 | 11 | 48 | 14 |
| 8 | Elliot Anderson | MF | Nottingham Forest | Premier League +2.21z | 4,170 | 4 | 8 | 0 |
| 9 | Harry Kane (captain) | FW | Bayern Munich | Bundesliga +1.84z | 4,407 | 64 | 113 | 79 |
| 10 | Jude Bellingham | MF | Real Madrid | La Liga +2.13z | 3,164 | 9 | 47 | 6 |
| 11 | Marcus Rashford | FW | Barcelona | La Liga +2.13z | 2,636 | 14 | 71 | 18 |
| 12 | Tino Livramento | DF | Newcastle United | Premier League +2.21z | 1,907 | 0 | 6 | 0 |
| 13 | Dean Henderson | GK | Crystal Palace | Premier League +2.21z | 4,686 | 0 | 4 | 0 |
| 14 | Jordan Henderson | MF | Brentford | Premier League +2.21z | 2,094 | 1 | 90 | 3 |
| 15 | Dan Burn | DF | Newcastle United | Premier League +2.21z | 3,561 | 2 | 7 | 0 |
| 16 | Kobbie Mainoo | MF | Manchester United | Premier League +2.21z | 1,942 | 1 | 13 | 0 |
| 17 | Morgan Rogers | MF | Aston Villa | Premier League +2.21z | 4,902 | 16 | 14 | 1 |
| 18 | Anthony Gordon | FW | Newcastle United | Premier League +2.21z | 2,969 | 18 | 18 | 2 |
| 19 | Ollie Watkins | FW | Aston Villa | Premier League +2.21z | 4,120 | 21 | 21 | 6 |
| 20 | Noni Madueke | FW | Arsenal | Premier League +2.21z | 2,552 | 7 | 10 | 1 |
| 21 | Eberechi Eze | MF | Arsenal | — | — no club data | — | 16 | 3 |
| 22 | Ivan Toney | FW | Al-Ahli | Pro League −0.86z | 3,558 | 34 | 8 | 1 |
| 23 | James Trafford | GK | Manchester City | League Cup +2.21z | 1,542 | 0 | 2 | 0 |
| 24 | Reece James | DF | Chelsea | Premier League +2.21z | 3,256 | 4 | 23 | 1 |
| 25 | Djed Spence | DF | Tottenham Hotspur | Premier League +2.21z | 3,071 | 0 | 5 | 0 |
| 26 | Jarell Quansah | DF | Bayer Leverkusen | Bundesliga +1.84z | 3,802 | 5 | 2 | 0 |
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
1,215,048
18.0 per 1,000 of home population
Host-language familiarity
Shared
primary language English · spoken in a host
Climate adaptation gap
+6.7°C
home-vs-venue heat differential
Venue extremes
45°C
peak heat index · altitude up to 177 m
Travel
6h
max time-zone shift · nearest venue 5,299 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
England's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
England — Elo since 1950
England ends the series at 2086 Elo, the world’s 4th-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 England, 1 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →