USA
- Coach
- Mauricio Pochettino foreign · Argentine
- Elo (model)
- 1,726
- Squad value
- €452M
- Power → Reality
- 31st 31st +0.01 pp · neutral draw
§ 01
The forecast
How far USA 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
USA — stage progression
On the central forecast, USA more likely than not reaches the Round of 32 (67%). Champion probability is 0.2% ± 0.01 pts.
§ 02
The group & the path
Group D advancement odds, the bracket half USA sits in, and the earliest round they could meet each leading side.
| Group D | Confed | Advance (top 2) | Reach R32 | |
|---|---|---|---|---|
| 1 | 🇹🇷Türkiye | UEFA | 43.7% | 76.7% |
| 2 | 🇵🇾Paraguay | CONMEBOL | 35.6% | 69.2% |
| 3 | 🇺🇸USA | CONCACAF | 29.4% | 67.2% |
| 4 | 🇦🇺Australia | AFC | 28.6% | 61.3% |
Source · Oxford Football Forecasting model
Earliest possible meetings
No collision rows recorded for this team.
Collision = the earliest round the bracket wiring could pit USA against that side. Full bracket & collision matrix →
§ 03
Match by match
USA'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 USA. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where USA stands against the median of the 48-team field, metric by metric. The dot is USA; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
USA 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
USA on the decoupling axis
g = +0.43 ± 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 | Matt Turner | GK | New England Revolution | Major League Soccer −0.71z | 900 | 0 | 54 | 0 |
| 2 | Sergiño Dest | DF | PSV Eindhoven | Eredivisie +0.74z | 2,919 | 1 | 39 | 3 |
| 3 | Chris Richards | DF | Crystal Palace | Premier League +2.21z | 4,227 | 2 | 36 | 3 |
| 4 | Tyler Adams | MF | Bournemouth | Premier League +2.21z | 2,069 | 2 | 54 | 2 |
| 5 | Antonee Robinson | DF | Fulham | Premier League +2.21z | 1,796 | 1 | 54 | 5 |
| 6 | Auston Trusty | DF | Celtic | League Cup −0.28z | 5,426 | 2 | 8 | 0 |
| 7 | Giovanni Reyna | MF | Borussia Mönchengladbach | Bundesliga +1.84z | 594 | 1 | 38 | 9 |
| 8 | Weston McKennie | MF | Juventus | Serie A +1.70z | 4,154 | 9 | 66 | 12 |
| 9 | Ricardo Pepi | FW | PSV Eindhoven | Eredivisie +0.74z | 1,775 | 19 | 37 | 13 |
| 10 | Christian Pulisic | FW | Milan | — | — no club data | — | 86 | 33 |
| 11 | Brenden Aaronson | FW | Leeds United | Premier League +2.21z | 2,754 | 4 | 58 | 9 |
| 12 | Miles Robinson | DF | FC Cincinnati | Major League Soccer −0.71z | 1,596 | 1 | 40 | 3 |
| 13 | Tim Ream (captain) | DF | Charlotte FC | Major League Soccer −0.71z | 4,081 | 1 | 82 | 1 |
| 14 | Sebastian Berhalter | MF | Vancouver Whitecaps FC | Major League Soccer −0.71z | 3,487 | 7 | 13 | 1 |
| 15 | Cristian Roldan | MF | Seattle Sounders FC | Major League Soccer −0.71z | 3,168 | 1 | 47 | 0 |
| 16 | Alex Freeman | DF | Villarreal | La Liga +2.13z | 356 | 0 | 17 | 2 |
| 17 | Malik Tillman | MF | Bayer Leverkusen | Bundesliga +1.84z | 2,402 | 8 | 30 | 3 |
| 18 | Max Arfsten | DF | Columbus Crew | Major League Soccer −0.71z | 3,245 | 7 | 20 | 1 |
| 19 | Haji Wright | FW | Coventry City | Championship +2.21z | 2,755 | 18 | 20 | 7 |
| 20 | Folarin Balogun | FW | Monaco | Ligue 1 +1.70z | 3,314 | 19 | 27 | 9 |
| 21 | Timothy Weah | FW | Marseille | Ligue 1 +1.70z | 3,139 | 3 | 51 | 7 |
| 22 | Mark McKenzie | DF | Toulouse | Ligue 1 +1.70z | 2,782 | 0 | 29 | 0 |
| 23 | Joe Scally | DF | Borussia Mönchengladbach | Bundesliga +1.84z | 2,792 | 2 | 26 | 0 |
| 24 | Matt Freese | GK | New York City FC | Major League Soccer −0.71z | 3,416 | 0 | 15 | 0 |
| 25 | Chris Brady | GK | Chicago Fire FC | Major League Soccer −0.71z | 2,655 | 0 | 1 | 0 |
| 26 | Alejandro Zendejas | FW | América | Liga MX +0.22z | 2,819 | 14 | 14 | 2 |
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
1,072,474
3.0 per 1,000 of home population
Host-language familiarity
Shared
primary language English · spoken in a host
Climate adaptation gap
−1.2°C
home-vs-venue heat differential
Venue extremes
29°C
peak heat index · altitude up to 45 m
Travel
3h
max time-zone shift · nearest venue 197 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
USA's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
USA — Elo since 1950
USA ends the series at 1827 Elo, the world’s 36th-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 USA, 1 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →