Round of 32 · Match 8

EnglandvsDR Congo

2026-07-01·12:00 local·Mercedes-Benz Stadium · AtlantaPredictions finalised

Snapshot · 2026-07-14Model 1.0.0Final prediction · locked 1 Jul, 19:13 UTCEngland·DR Congo·
Full time · forecast gradedEngland 2 1 DR CongoThe 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.

EnglandSignal balanceDR Congo
92%8%

England are dominant at 72% vs DR Congo's 4%. Quality, form, and model estimates all point the same way. An upset here would be a major story.

📊What the Models Say

5 England
78%Elo Rating Model0%
StrongStrong

Rates teams by a single strength number updated after every match. Simpler but fast to react. It rates England at 78% to win vs DR Congo at 0%.

67%Dixon-Coles Model9%
StrongStrong

Simulates the goal-scoring process using attack and defence strength. The heaviest-weighted model. It rates England at 67% to win vs DR Congo at 9%.

67%Hierarchical Poisson9%
StrongStrong

Groups teams by confederation to share information. Helps for teams with fewer matches. It rates England at 67% to win vs DR Congo at 9%.

72%Final Ensemble4%
StrongStrong

The published probability after calibration and adjustments. This is what the model says. It rates England at 72% to win vs DR Congo at 4%.

3/3Model Agreement0/3
StrongStrong

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

Tournament Form

3 England
16pts (5W 1D 0L)Tournament Record4pts (1W 1D 2L)
StrongStrong

England collected 16 points (5W 1D 0L) vs DR Congo's 4 (1W 1D 2L). A stronger tournament record.

2.17/matchGoals Scored1.25/match
ModerateModerate

England averaged 2.17 goals per match vs DR Congo's 1.25. More firepower coming in.

1.0 conceded/matchDefence1.25 conceded/match
Even

Similar defensive records: England 1.0, DR Congo 1.25 goals conceded per match.

+7Goal Difference+0
StrongStrong

England's goal difference of +7 is better than DR Congo's +0. They outperformed opponents by more.

📈Momentum

1 England1 DR Congo
+33.4Tournament Rating Change+27.4
SlightSlight

England's rating rose +33.4 during the tournament while DR Congo's moved +27.4. The tournament has been kinder to England.

-0.0068Player Form Trend+0.0060
StrongStrong

DR Congo's players improved their form ratings during the tournament (+0.0060) vs England (-0.0068). Players trending upward.

🏆Team Quality

4 England
2020Overall Strength (Elo)1655
StrongStrong

England is rated 2020 vs DR Congo's 1655 (gap: 365). That's a very large gap in historical team strength.

1.60 xGExpected Chance Creation0.41 xG
StrongStrong

The model expects England to create 1.60 expected goals vs DR Congo's 0.41. More and better chances projected.

0.26Star Power0.17
SlightSlight

England's top 3 starters are harder to replace (avg VORP 0.26) than DR Congo's (0.17). More star power in key positions.

0.049Squad Familiarity0.000
ModerateModerate

England's starters play together at club level more often (0.049 cohesion) than DR Congo's (0.000). More shared understanding on the pitch.

🌍Match Conditions

1 England
6,673kmTravel Distance11,749km
StrongStrong

England traveled 6,673km vs DR Congo's 11,749km. A shorter journey means less fatigue.

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

La prévision

Match-outcome probability

  • England win
    58.2%
  • Draw
    30.3%
  • DR Congo win
    11.5%

A clash of identities: England's balanced approach meets DR Congo's counter-attacker style in a fixture the model gives to England at 72%.

Likeliest score1–020.9%
First goal0-15'28.4%
Both teams score27.3%
Over 2.5 goals32.5%
Top scorerWissa8.0%
Expected goals1.6 - 0.4
Loading pitch visualisation...

Buts et scores

Likeliest score 1–0 (20.9%) · xG 1.6 - 0.4

Expected goals

England
1.60
DR Congo
0.41

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

Most likely scorelines

  • 1–0
    20.9%
  • 2–0
    17.2%
  • 0–0
    14.0%
  • 1–1
    9.3%
  • 3–0
    9.1%

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
    37.0%
  • 1–0
    28.9%
  • 2–0
    11.7%
  • 0–1
    7.1%
  • 1–1
    6.3%

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
    86.0%
  • More than 1.5 goals
    60.1%
  • More than 2.5 goals
    32.5%
  • More than 3.5 goals
    14.4%
  • More than 4.5 goals
    5.3%
  • More than 5.5 goals
    1.7%
  • Both teams score
    27.3%

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

  • England clean sheetOpposing team scores zero66.4%
  • DR Congo clean sheetOpposing team scores zero20.3%

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

  • England by 4+
    5.9%
  • England by 3+
    16.6%
  • England by 2+
    37.8%
  • England by 1+
    66.6%
  • Draw
    24.9%
  • DR Congo by 1+
    8.6%
  • DR Congo by 2+
    1.6%
  • DR Congo by 3+
    0.2%
  • DR Congo by 4+
    <0.1%

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.

Comment le match se déroule

Over 2.5 goals 32.5% · BTTS 27.3%

Game state through the match

0%25%50%75%100%0'15'30'45'60'75'90'
  • England ahead67.1%
  • Level23.8%
  • DR Congo ahead9.1%

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
    28.4%
  • 15–30
    20.3%
  • 30–45
    14.6%
  • 45–60
    10.4%
  • 60–75
    7.5%
  • 75–90
    5.3%
  • No goal
    13.5%

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 →HEngland winDDrawADR Congo win
HEngland ahead44.8%2.6%0.3%
DLevel21.0%18.7%3.9%
ADR Congo ahead1.3%2.6%4.8%

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

  • England trail at HT, avoid defeat at FT
    3.9%
  • DR Congo trail at HT, avoid defeat at FT
    2.9%

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)
  • England
    42.7%
  • DR Congo
    57.3%
If England kicks first
  • England
    54.0%
  • DR Congo
    46.0%
If DR Congo kicks first
  • England
    31.1%
  • DR Congo
    68.9%
Expected paired rounds
4.8
Decided in regulation 5 kicks
73.7%

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: England conv 68.6%, save 22.9%DR Congo conv 73.3%, save 23.3%. Smoothed against the global prior with prior strength 20 — see /docs/methodology/.

Équipes et joueurs

Top scorer: Wissa (8.0%)

Match detail

England

Model-rated key players: Harry Kane (FW) — P(scores) 4.9%; Marcus Rashford (FW) — P(scores) 6.3%; Ollie Watkins (FW) — P(scores) 2.4%.

How they play

England under Thomas Tuchel play a balanced game, holding 55% of the ball — among the highest in the tournament field. Their likely shape is a 4-1-4-1, though they have also used 4-3-3. They apply moderate pressing intensity (PPDA 23.5) and build patiently through midfield with 8.5 passes per attacking sequence. They favour high-quality chances (xG/shot 0.142, among the best in the field).

What they must execute

England will need to leverage their strengths while managing the physical demands of a tournament spread across three host countries. Managing the fitness of Tino Livramento could prove decisive — their availability transforms the team's ceiling.

Storylines
Out injured: Tino LivramentoThigh problems, no expected return. Composite 0.94 — would have been a likely starter.
Defensive form: Conceded only 0.44 xG per match across 11 recent internationals — #2 of 35 in the field for defensive solidity.
Top scorer: Harry KaneModel's top anytime-scorer for the team — 32% probability of scoring at least once, rank #2 of all players.

DR Congo

Model-rated key players: Yoane Wissa (FW) — P(scores) 8.0%; Cédric Bakambu (FW) — P(scores) 2.4%; Jackson Muleka (FW) — P(scores) 1.4%.

How they play

DR Congo under Sébastien Desabre play a counter attacker game with 46% possession. They apply moderate pressing intensity (PPDA 20.9) and move the ball forward quickly at 4.9 passes per attack. They favour high-quality chances (xG/shot 0.200, among the best in the field) and rely heavily on set pieces (20% of their xG).

What they must execute

DR Congo rely on defensive discipline and quick transitions — absorbing pressure and converting turnovers into attacking chances. Concentration and defensive organisation for full 90-minute stretches will determine whether the approach holds against top opposition.

Storylines
Form trend: Gained 87 international Elo points over the last 12 months — current rating 1767.
Long-haul: Travels 38,411 km across 3 venues in the group stage — one of the longest itineraries in the field.
Touchline: Sébastien DesabreFirst World Cup as head coach, appointed 2022.
Workload going in

England's predicted XI averages 2,119 club minutes over the 2024-25 season (moderate load).

England coverage: 79.0% (11/11 XI matched against the FBref Big-5) · DR Congo: 58.0% (8/11).

Set-piece outlook

England historically converts 15.2% of xG from set-pieces, contributing 0.24 expected set-piece goals in this fixture. DR Congo converts 20.5% from set-pieces (0.08 expected). Combined, the model expects 0.33 set-piece goals across the 90 minutes.

  • P(England scores set-piece goal) 21.6%
  • P(DR Congo scores set-piece goal) 8.1%
  • P(set-piece goal in match) 27.9%

England: Trent Alexander-Arnold on corners (32 corners), Eberechi Eze on free kicks (per fbref 2022 23)

Penalty outlook

If a penalty is awarded to England, the model gives 68.6% conversion, 73.3% for DR Congo. If this match goes to a shootout, the symmetric (coin-toss averaged) win probability is 42.7% England / 57.3% DR Congo.

England primary PK: Marcus Rashford (6/8 in 2019-20, per fbref 2022 23) · DR Congo primary PK: Yoane Wissa (4/5 in 2020-21, per fbref 2020 21).

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

England

  1. Marc GuéhiCentre-backCover: Jarell Quansah · 0.650.32gap
  2. Jude BellinghamAttacking midfieldCover: Morgan Rogers · 0.720.27gap
  3. Marcus RashfordWingerCover: Anthony Gordon · 0.620.19gap

DR Congo

  1. Meschak EliaAttacking midfieldNo natural backup0.20gap
  2. Gaël KakutaAttacking midfieldNo natural backup0.16gap
  3. Yoane WissaStrikerCover: Simon Banza · 0.750.14gap

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 level320 m
  • Avg temperatureFive-year mean over the tournament window25.7 °C
  • Avg humidity73%
  • Heat stressShade WBGT ~27.9 °CLow heat stress
  • Pitch surfacetemporary natural grass over artificial turf

Indoor artificial-turf stadium converting to 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. Afternoon 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)

England
DR Congo

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

England

vs Panama · avg 6.4

9
Jude BellinghamCM
ATK
DEF
PAS
8
Harry KaneST
ATK
DEF
PAS
7
Marcus RashfordLW
ATK
DEF
PAS
7
Jordan PickfordGK
ATK
DEF
PAS
6
Elliot AndersonCM
ATK
DEF
PAS
6
Declan RiceDM
ATK
DEF
PAS
6
MagwayLW
ATK
DEF
PAS
5
Noni MaduekeRW
ATK
DEF
PAS
5
Bukayo SakaRW
ATK
DEF
PAS
5
Anthony GordonLW
ATK
DEF
PAS

DR Congo

vs Uzbekistan · avg 8.0

8
Cédric BakambuST
ATK
DEF
PAS
8
Lionel MpasiGK
ATK
DEF
PAS

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

Video analysis: player performance

Per-player ratings and event breakdowns from official highlights analysis. Tap a player to see their full match timeline.

England
9
Harry Kane1'–1'

Scored both crucial goals for England, including the winner, showcasing clinical finishing and leadership when his team needed it most.

2goals1shots1on target1headers

Match timeline

1'Harry Kane scores his second goal, putting England in the lead.
1'Congo DR goalkeeper saves a header from Kane.
1'Congo DR goalkeeper saves a header from Kane.
9
Noni Madueke

Scored two goals with clinical finishing, establishing himself as a key attacking threat for England.

2goals

Match timeline

8
Anthony Gordon

Scored a goal, demonstrating good positioning and clinical finishing within the penalty area.

1goals

Match timeline

8
England GK

Made two significant saves, showcasing strong reflexes and positioning to prevent further goals for the opposition.

7
Jude Bellingham

Tested the opposition goalkeeper with a powerful shot, showcasing his offensive capabilities from midfield.

1shots1on target

Match timeline

7
Bukayo Saka

Forced a save from the opposition goalkeeper with a shot on target, contributing to England's offensive pressure.

1shots1on target

Match timeline

6
Marcus Rashford1'–1'

Created several attacking opportunities with shots on goal but lacked the clinical finish to convert them.

2shots1on target

Match timeline

1'Rashford's shot goes wide, hitting the side netting.
6
Ezri Konsa

Showed good attacking intent by hitting the post from inside the box, despite being a defender.

1shots

Match timeline

DR Congo
9
Congo DR GK #1

Delivered an exceptional goalkeeping performance, making numerous crucial saves that kept his team competitive throughout the match.

8
Sapanga0'–0'

Scored a crucial opening goal for Congo DR with a clinical finish, giving his team an early lead.

1goals

Match timeline

0'Sapanga scores for Congo DR, giving them an early lead.
6
Chancel Mbemba

Made an attacking effort that forced a save from the England goalkeeper, showing offensive intent from defense.

1shots1on target

Match timeline

Match observations

  • England then mounted sustained pressure, creating numerous chances that were repeatedly denied by an outstanding goalkeeping performance.
  • Despite the resilience of Congo DR, England eventually found their rhythm and secured a late victory through their captain.
  • The atmosphere in the stadium was electric, with fans reacting passionately to every significant moment.

Sous le capot

Model-by-model comparison

England vs DR Congo

High disagreement (11.5%)
ModelWeightHomeDrawAway
EloRating-based strength estimate32%
78.4%
21.6%
0.0%
Dixon-ColesGoal-process model with low-score correction63%
66.9%
24.4%
8.6%
Hierarchical PoissonBayesian model with confederation pooling6%
67.3%
23.4%
9.3%
Bayesian stackingLearned-weight combination
78.4%
21.6%
0.0%
Ensemble (published)Uniform average + isotonic calibration
72.0%
23.9%
4.0%
Home spread: 11.5%
Draw spread: 2.8%
Away spread: 9.3%
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 32 · Match 8
Date:
1 Jul
Venue:
Mercedes-Benz Stadium, Atlanta
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.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.
  2. 2.Squad availability: 1 carrying a fitness doubt across the two squads. The forecast does not adjust for who is missing: its lineup channel currently contributes zero, so this is context the probabilities do not include.
Availability

England

England: 1 carrying a fitness doubt.

  • DoubtTino Livramento (defender) is carrying Knee injury — a depth-level fitness watch item.

DR Congo

DR Congo come in at close to full strength.

What it means

Both projected XIs look intact; the fitness concerns are at squad-depth level rather than among first-choice starters.

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

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