Round of 16 · Match 6

United StatesvsBelgium

2026-07-06·17:00 local·Lumen Field · SeattlePredictions finalised

Snapshot · 2026-07-09Model 1.0.0Final prediction · locked 6 Jul, 21:56 UTCUnited States·Belgium·
Full time · forecast gradedUnited States 1 4 BelgiumThe locked pre-match forecast has been graded against this result.See the calibration recap →

Match signals

Factors that favour each side, from statistical models to group stage form and match conditions. Longer bars = stronger advantage.

United StatesSignal balanceBelgium
20%80%

Belgium are dominant at 67% vs United States's 11%. Quality, form, and model estimates all point the same way. An upset here would be a major story.

📊What the Models Say

5 Belgium
20%Elo Rating Model58%
StrongStrong

Rates teams by a single strength number updated after every match. Simpler but fast to react. It rates Belgium at 58% to win vs United States at 20%.

17%Dixon-Coles Model59%
StrongStrong

Simulates the goal-scoring process using attack and defence strength. The heaviest-weighted model. It rates Belgium at 59% to win vs United States at 17%.

16%Hierarchical Poisson61%
StrongStrong

Groups teams by confederation to share information. Helps for teams with fewer matches. It rates Belgium at 61% to win vs United States at 16%.

11%Final Ensemble67%
StrongStrong

The published probability after calibration and adjustments. This is what the model says. It rates Belgium at 67% to win vs United States at 11%.

0/3Model Agreement3/3
StrongStrong

All 3 models agree: Belgium is favoured. When models agree, the signal is stronger.

Tournament Form

4 Belgium
9pts (3W 0D 2L)Tournament Record11pts (3W 2D 0L)
SlightSlight

Belgium collected 11 points (3W 2D 0L) vs United States's 9 (3W 0D 2L). A stronger tournament record.

2.2/matchGoals Scored2.6/match
SlightSlight

Belgium averaged 2.6 goals per match vs United States's 2.2. More firepower coming in.

1.6 conceded/matchDefence1.0 conceded/match
SlightSlight

Belgium conceded just 1.0 goals/match vs United States's 1.6. Tighter at the back.

+3Goal Difference+8
ModerateModerate

Belgium's goal difference of +8 is better than United States's +3. They outperformed opponents by more.

📈Momentum

1 United States1 Belgium
+32.8Tournament Rating Change+25.0
SlightSlight

United States's rating rose +32.8 during the tournament while Belgium's moved +25.0. The tournament has been kinder to United States.

+0.0021Player Form Trend+0.0046
SlightSlight

Belgium's players improved their form ratings during the tournament (+0.0046) vs United States (+0.0021). Players trending upward.

🏆Team Quality

4 Belgium
1721Overall Strength (Elo)1867
ModerateModerate

Belgium is rated 1867 vs United States's 1721 (gap: 146). That's a significant gap in historical team strength.

0.88 xGExpected Chance Creation1.78 xG
StrongStrong

The model expects Belgium to create 1.78 expected goals vs United States's 0.88. More and better chances projected.

0.25Star Power0.37
SlightSlight

Belgium's top 3 starters are harder to replace (avg VORP 0.37) than United States's (0.25). More star power in key positions.

0.009Squad Familiarity0.019
SlightSlight

Belgium's starters play together at club level more often (0.019 cohesion) than United States's (0.009). More shared understanding on the pitch.

🌍Match Conditions

2 United States
2,789kmTravel Distance7,980km
StrongStrong

United States traveled 2,789km vs Belgium's 7,980km. A shorter journey means less fatigue.

3h shiftTimezone Shift9h shift
StrongStrong

United States face a 3h timezone shift vs Belgium's 9h. Less jet lag disruption.

17 signals across 5 categories. Signal strength reflects how large the gap is between the two teams on each factor. Signals are descriptive, not prescriptive.

El pronóstico

Match-outcome probability

  • United States win
    10.5%
  • Draw
    22.4%
  • Belgium win
    67.1%

The model rates Belgium as favourites at 67%, with United States projected at 11% to win.

Rank checkFIFA ranks United States #14 in the world; the model ranks them #27 in this tournament field, 13 places lower than the FIFA list suggests. All 48 compared →
Likeliest score0–111.8%
First goal0-15'35.7%
Both teams score49.1%
Over 2.5 goals49.5%
Top scorerBalogun9.0%
Expected goals0.9 - 1.8
Loading pitch visualisation...

Goles y marcadores

Likeliest score 0–1 (11.8%) · xG 0.9 - 1.8

Expected goals

United States
0.88
Belgium
1.78

Mean of the Dixon-Coles joint goal distribution. Same fit that produces the most-likely-scoreline list below.

Most likely scorelines

  • 0–1
    11.8%
  • 1–1
    11.6%
  • 0–2
    11.1%
  • 1–2
    9.7%
  • 0–0
    7.7%

From the Dixon-Coles joint Poisson with the low-score correction. Scorelines are listed in probability order; this is a description of the model's distribution, not a recommendation.

Most likely half-time scorelines

  • 0–0
    27.2%
  • 0–1
    22.9%
  • 1–0
    11.0%
  • 1–1
    11.0%
  • 0–2
    10.5%

Same Dixon-Coles fit as the full-time list above, with rates halved to a 45-minute window and the low-score correction applied to that 1st-half block. The 0-0 row sits higher here than at full-time because fewer minutes have elapsed.

Goal totals

  • More than 0.5 goals
    92.3%
  • More than 1.5 goals
    74.9%
  • More than 2.5 goals
    49.5%
  • More than 3.5 goals
    27.5%
  • More than 4.5 goals
    13.0%
  • More than 5.5 goals
    5.3%
  • Both teams score
    49.1%

Each row is the probability the match finishes with more than the listed number of goals. Both-teams-to-score is the probability each side scores at least once. All values are marginals of the Dixon-Coles joint goal grid that produces the scoreline list above — not market lines or any other operator construct.

Event-typed probabilities

  • United States clean sheetOpposing team scores zero16.9%
  • Belgium clean sheetOpposing team scores zero41.6%

Derived from the same Dixon-Coles joint distribution as the scoreline list. These are descriptive event probabilities — see CLAUDE.md §3/§4 (formerly COMPLIANCE.md §4.2.7) for the framing the project uses.

Win-margin probability

  • United States by 4+
    0.3%
  • United States by 3+
    1.4%
  • United States by 2+
    5.8%
  • United States by 1+
    17.6%
  • Draw
    24.4%
  • Belgium by 1+
    58.0%
  • Belgium by 2+
    33.5%
  • Belgium by 3+
    15.4%
  • Belgium by 4+
    5.8%

Each row is the probability the match ends with the listed margin or larger in that direction. Marginal of the Dixon-Coles joint goal grid; the “by 1+” rows plus the draw row sum to 1.

Cómo se desarrolla el partido

Over 2.5 goals 49.5% · BTTS 49.1%

Game state through the match

0%25%50%75%100%0'15'30'45'60'75'90'
  • United States ahead18.3%
  • Level23.1%
  • Belgium ahead58.7%

Probability of each game state at minutes 0, 15, 30, 45, 60, 75, 90 — derived from two independent thinned-Poisson processes with the Dixon-Coles per-team rates. The three lines always sum to 1 at each minute. The right column shows the state at the match's closing minute.

When the first goal arrives

  • 0–15
    35.7%
  • 15–30
    23.0%
  • 30–45
    14.8%
  • 45–60
    9.5%
  • 60–75
    6.1%
  • 75–90
    3.9%
  • No goal
    7.0%

Probability the match's first goal arrives in each 15-minute window. Homogeneous Poisson with combined rate λ = λh + λa from the Dixon-Coles fit; the seven rows (six windows + no-goal tail) sum to 1.

Half-time / full-time grid

Joint probability of half-time and full-time results
HT ↓ / FT →HUnited States winDDrawABelgium win
HUnited States ahead10.3%4.2%2.3%
DLevel6.8%14.9%17.5%
ABelgium ahead1.0%4.3%38.8%

Each cell is P(half-time result, full-time result). All nine cells sum to 1. Derived from a halved-λ Dixon-Coles fit for the first half plus an independent-Poisson second-half convolution.

Comeback probability

  • United States trail at HT, avoid defeat at FT
    5.3%
  • Belgium trail at HT, avoid defeat at FT
    6.5%

Joint probability — P(side trailing at half-time AND avoiding defeat at full-time). NOT conditional on trailing at HT. Derived from the same half-time / full-time decomposition that produces the HT/FT grid above; a tied first half is neither a home nor an away comeback opportunity.

PK shootout simulator

If the match ends level after extra time, the model estimates the shootout outcome from each team's Bayesian-smoothed conversion / save rate (Model #15). The bracket simulator uses the symmetric (averaged) ordering; the two what-if scenarios below show how the win probabilities shift when conditioning on which team kicks first.

Symmetric (averaged over both orderings — used by the bracket simulator)
  • United States
    50.0%
  • Belgium
    50.0%
If United States kicks first
  • United States
    61.9%
  • Belgium
    38.1%
If Belgium kicks first
  • United States
    38.1%
  • Belgium
    61.9%
Expected paired rounds
4.8
Decided in regulation 5 kicks
73.2%

First-kicker advantage

The first kicker's per-kick conversion rate is scaled by ×1.050 (about +5.0%), stacked on the Markov chain's structural asymmetry. Real World Cup shootouts use a coin toss for kicker order, so on average the order is 50/50 — the symmetric path above is the relevant number for a single fixture. The ordering-conditioned probabilities are a descriptive what-if scenario.

Literature: first kickers win ≈ 60% historically (Apesteguia & Palacios-Huerta, American Economic Review 2010; Vandebroek et al. 2016).

Per-team posteriors: United States conv 71.4%, save 22.9%Belgium conv 71.4%, save 22.9%. Smoothed against the global prior with prior strength 20 — see /docs/methodology/.

Equipos y jugadores

Top scorer: Balogun (9.0%)

Match detail

United States

Model-rated key players: Folarin Balogun (FW) — P(scores) 9.0%; Diego Luna (FW) — P(scores) 3.0%; Haji Wright (FW) — P(scores) 2.3%.

How they play

United States under Mauricio Pochettino play a balanced game with 50% possession. Their likely shape is a 4-3-3. They sit deeper and pick their moments to press (PPDA 27.7).

What they must execute

United States will need to leverage their strengths while managing the physical demands of a tournament spread across three host countries. Managing minutes for Tim Ream across what could be seven matches will test the coaching staff's rotation planning.

Storylines
Last dance: Tim Ream38 at kickoff with 80 caps — probably his final World Cup.
Top scorer: Folarin BalogunModel's top anytime-scorer for the team — 28% probability of scoring at least once, rank #9 of all players.
Touchline: Mauricio PochettinoFirst World Cup as head coach, appointed 2024.

Belgium

Model-rated key players: Kevin De Bruyne (MF) — P(scores) 6.8%; Loïs Openda (FW) — P(scores) 4.1%; Leandro Trossard (FW) — P(scores) 2.6%.

How they play

Belgium under Rudi Garcia play a balanced game, holding 54% of the ball — among the highest in the tournament field. Their likely shape is a other, though they have also used 4-2-3-1. They apply moderate pressing intensity (PPDA 23.1) and build patiently through midfield with 7.7 passes per attacking sequence.

What they must execute

Belgium will need to leverage their strengths while managing the physical demands of a tournament spread across three host countries. Managing minutes for Axel Witsel across what could be seven matches will test the coaching staff's rotation planning.

Storylines
Strong in goal: Thibaut Courtois#2 starting-GK rating in the field — 0.99 on club-derived save metrics across 48 teams.
Last dance: Axel Witsel37 at kickoff with 136 caps — probably his final World Cup.
Touchline: Rudi GarciaFirst World Cup as head coach, appointed 2025.
Set-piece outlook

United States historically converts 5.2% of xG from set-pieces, contributing 0.04 expected set-piece goals in this fixture. Belgium converts 14.6% from set-pieces (0.26 expected). Combined, the model expects 0.30 set-piece goals across the 90 minutes.

  • P(United States scores set-piece goal) 4.4%
  • P(Belgium scores set-piece goal) 22.9%
  • P(set-piece goal in match) 26.3%

United States: Timothy Tillman on corners (42 corners), Gianluca Busio on free kicks (per fbref 2021 22) · Belgium: Kevin De Bruyne on corners (25 corners), Axel Witsel on free kicks (per fbref 2022 23)

Penalty outlook

If a penalty is awarded to United States, the model gives 71.4% conversion, 71.4% for Belgium. If this match goes to a shootout, the symmetric (coin-toss averaged) win probability is 50.0% United States / 50.0% Belgium.

United States primary PK: Folarin Balogun (2/2 in 2022-23, per fbref 2021 22) · Belgium primary PK: Kevin De Bruyne (2/3 in 2020-21, per fbref 2022 23).

Derived from the model's per-fixture forecast joint and supporting reference data (predicted squads, set-piece xG share, PK posteriors, club minutes). See /docs/methodology/ for the full methodology.

Squad depth

Most irreplaceable starters

United States

  1. Christian PulisicWingerCover: Alejandro Zendejas · 0.570.27gap
  2. Tyler AdamsDefensive midfieldNo natural backup0.26gap
  3. Antonee RobinsonFull-backCover: Joe Scally · 0.770.22gap

Belgium

  1. Youri TielemansCentral midfieldNo natural backup0.41gap
  2. Romelu LukakuStrikerNo natural backup0.37gap
  3. Zeno DebastCentre-backCover: Brandon Mechele · 0.560.32gap

Gap = how far a side's rating at the position falls from the starter to his likely in-squad replacement (named under each name). Larger = harder to replace. Descriptive metric, does not feed the published probabilities. Methodology →

Match conditions

  • AltitudeNear sea level16 m
  • Avg temperatureFive-year mean over the tournament window18.0 °C
  • Avg humidity68%
  • Heat stressShade WBGT ~19.6 °CLow heat stress
  • Pitch surfacetemporary natural grass over artificial turf

Artificial-turf NFL stadium laying a temporary natural-grass pitch for the tournament.

Heat stress is a shade Wet-Bulb Globe Temperature proxy from the venue's climatology mean temperature and humidity; FIFA mandates cooling breaks at WBGT 32 °C. Evening kickoff (local time). These are long-window averages, not a match-day forecast, and they are not inputs to the forecast.

Top scorers · P(scores in this match)

United States
Belgium

Per-player scoring rate from Model #5 (`p_score_per_match`). Reflects each player's npxG/90, expected minutes, team xG share, and the average opposing-team defence. See /docs/methodology/.

Recent match form

Last match player ratings

United States

vs Bosnia and Herzegovina · avg 5.5

7
Sergiño DestRB
ATK
DEF
PAS
4
Folarin BalogunST
ATK
DEF
PAS

Worked well: Their offensive movement and ability to create chances, particularly from wide areas and set pieces, proved effective. They maintained their attacking threat even after a player was dismissed.

Struggled: The team struggled with offside calls, indicating issues with timing runs. A red card also highlighted a lapse in discipline.

Belgium

vs Senegal · avg 8.0

8
Thibaut CourtoisGK
ATK
DEF
PAS
8
Romelu LukakuST
ATK
DEF
PAS
8
Dodi LukébakioRW
ATK
DEF
PAS

Player scores from official highlight analysis of each team's most recent match. Observational, not a model input. Methodology →

Entre bastidores

Model-by-model comparison

United States vs Belgium

Consensus (3.7%)
ModelWeightHomeDrawAway
EloRating-based strength estimate32%
20.0%
22.0%
58.0%
Dixon-ColesGoal-process model with low-score correction63%
17.0%
23.9%
59.0%
Hierarchical PoissonBayesian model with confederation pooling6%
16.3%
22.7%
61.0%
Bayesian stackingLearned-weight combination
8.5%
22.0%
69.5%
Ensemble (published)Uniform average + isotonic calibration
10.8%
22.4%
66.8%
Home spread: 3.7%
Draw spread: 1.9%
Away spread: 3.0%
How each model works
Elo
Each team carries a single strength rating updated after every match by a margin-aware K-factor. Match probabilities come from the logistic function of the rating gap. Elo is fast-adapting but coarse — it sees only who won and by how much, not how the goals were scored.
Dixon-Coles
A Poisson regression on team-level attack and defence parameters, fitted via maximum likelihood with an exponential time-decay weighting. The Dixon-Coles correction adjusts the four low-score cells (0-0, 1-0, 0-1, 1-1) where independent Poisson underestimates dependence. Produces full scoreline distributions, not just H/D/A.
Hierarchical Poisson
A Bayesian Poisson model fitted via MCMC (PyMC) with hierarchical priors that pool attack and defence parameters within confederations. Shrinks small-sample teams toward their confederation mean — helpful for nations with few recent competitive fixtures. Slower to fit but better-calibrated on the tails.
Bayesian stacking
Optimises simplex weights (w_elo, w_dc, w_hp) to maximise the leave-one-out log-score across a walk-forward backtest (Yao et al. 2018). The result is a weighted average of the three component models' probabilities, then isotonic-calibrated. Adds no extra features — just learns which component to trust more from historical accuracy.
Ensemble (published)
Equal-weight average of all three component models, followed by per-class isotonic regression calibration fitted on 24 months of walk-forward out-of-fold predictions. This is the probability published on the site. The uniform mean is deliberately simple — it avoids overfitting to the stacking weights' training window.

Three independent component models feed two combination strategies. The uniform ensemble is the published probability; Bayesian stacking uses learned weights. Amber bars flag >5pp divergence from the published number. Full methodology

Latest news & match context

Match conditions
Stage:
Round of 16 · Match 6
Date:
6 Jul
Venue:
Lumen Field, Seattle
Beyond the model

Ranked by likely importance. None of these feed the forecast: the probabilities rest on team strength, venue conditions and the style matchup.

  1. 1.Squad availability: 1 carrying a fitness doubt across the two squads, 1 of them projected starters. The forecast does not adjust for who is missing: its lineup channel currently contributes zero, so this is context the probabilities do not include.
  2. 2.Elimination stakes: A one-off elimination tie. Motivation, risk appetite and game management under tournament pressure are not model inputs; the forecast rests on team strength and the style matchup.
  3. 3.Rest differential: Belgium have had 5 days since their previous match versus 4 for United States. Rest and recovery are not model inputs.
Availability

United States

United States: 1 carrying a fitness doubt.

  • DoubtChristian Pulisic, the first-choice forward, is recovering from Calf injury and is a fitness watch item; if unavailable the projected XI shifts.

Belgium

Belgium come in at close to full strength.

What it means

Availability runs in Belgium's favour here: United States are managing a fitness concern over Christian Pulisic, while Belgium's projected XI looks intact.

Availability from the predicted squads and injury feed; forecast adjustments from the model's own decomposition. See /docs/methodology/.

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