Round of 32 · Match 6

Ivory CoastvsNorway

2026-06-30·12:00 local·AT&T Stadium · DallasPredictions finalised

Snapshot · 2026-07-14Model 1.0.0Final prediction · locked 30 Jun, 17:15 UTCIvory Coast·Norway·
Full time · forecast gradedIvory Coast 1 2 NorwayThe 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.

Ivory CoastSignal balanceNorway
12%88%

Norway are strong favourites at 52% vs Ivory Coast's 21%. Most signals point the same way. Ivory Coast will need to outperform their rating.

📊What the Models Say

5 Norway
9%Elo Rating Model69%
StrongStrong

Rates teams by a single strength number updated after every match. Simpler but fast to react. It rates Norway at 69% to win vs Ivory Coast at 9%.

26%Dixon-Coles Model44%
ModerateModerate

Simulates the goal-scoring process using attack and defence strength. The heaviest-weighted model. It rates Norway at 44% to win vs Ivory Coast at 26%.

26%Hierarchical Poisson46%
ModerateModerate

Groups teams by confederation to share information. Helps for teams with fewer matches. It rates Norway at 46% to win vs Ivory Coast at 26%.

21%Final Ensemble52%
StrongStrong

The published probability after calibration and adjustments. This is what the model says. It rates Norway at 52% to win vs Ivory Coast at 21%.

0/3Model Agreement3/3
StrongStrong

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

Tournament Form

1 Ivory Coast3 Norway
6pts (2W 0D 2L)Tournament Record12pts (4W 0D 2L)
StrongStrong

Norway collected 12 points (4W 0D 2L) vs Ivory Coast's 6 (2W 0D 2L). A stronger tournament record.

1.25/matchGoals Scored2.17/match
ModerateModerate

Norway averaged 2.17 goals per match vs Ivory Coast's 1.25. More firepower coming in.

1.0 conceded/matchDefence1.83 conceded/match
ModerateModerate

Ivory Coast conceded just 1.0 goals/match vs Norway's 1.83. Tighter at the back.

+1Goal Difference+2
SlightSlight

Norway's goal difference of +2 is better than Ivory Coast's +1. They outperformed opponents by more.

📈Momentum

1 Ivory Coast1 Norway
+22.8Tournament Rating Change+30.1
SlightSlight

Norway's rating rose +30.1 during the tournament while Ivory Coast's moved +22.8. The tournament has been kinder to Norway.

+0.0029Player Form Trend-0.0001
SlightSlight

Ivory Coast's players improved their form ratings during the tournament (+0.0029) vs Norway (-0.0001). Players trending upward.

🏆Team Quality

3 Norway
1676Overall Strength (Elo)1912
StrongStrong

Norway is rated 1912 vs Ivory Coast's 1676 (gap: 236). That's a very large gap in historical team strength.

0.90 xGExpected Chance Creation1.23 xG
ModerateModerate

The model expects Norway to create 1.23 expected goals vs Ivory Coast's 0.90. More and better chances projected.

0.40Star Power0.63
ModerateModerate

Norway's top 3 starters are harder to replace (avg VORP 0.63) than Ivory Coast's (0.40). More star power in key positions.

0.000Squad Familiarity0.000
Even

Similar levels of squad familiarity from club football.

🌍Match Conditions

1 Ivory Coast1 Norway
9,699kmTravel Distance7,665km
ModerateModerate

Norway traveled 7,665km vs Ivory Coast's 9,699km. A shorter journey means less fatigue.

5h shiftTimezone Shift7h shift
SlightSlight

Ivory Coast face a 5h timezone shift vs Norway's 7h. 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

  • Ivory Coast win
    29.2%
  • Draw
    29.7%
  • Norway win
    41.1%

A 236-point Elo gap frames this as a significant mismatch, yet the model still gives Ivory Coast a 21% probability of a result — enough to make this more than a formality.

Rank checkFIFA ranks Ivory Coast #42 in the world; the model ranks them #23 in this tournament field, 19 places higher than the FIFA list suggests. All 48 compared →
Likeliest score1–114.0%
First goal0-15'29.8%
Both teams score42.7%
Over 2.5 goals35.7%
Top scorerHaaland11.9%
Expected goals0.9 - 1.2
Loading pitch visualisation...

Goles y marcadores

Likeliest score 1–1 (14.0%) · xG 0.9 - 1.2

Expected goals

Ivory Coast
0.90
Norway
1.23

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

Most likely scorelines

  • 1–1
    14.0%
  • 0–1
    13.9%
  • 0–0
    12.8%
  • 1–0
    9.9%
  • 0–2
    9.0%

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
    35.2%
  • 0–1
    20.6%
  • 1–0
    15.0%
  • 1–1
    10.1%
  • 0–2
    6.5%

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
    87.2%
  • More than 1.5 goals
    63.4%
  • More than 2.5 goals
    35.7%
  • More than 3.5 goals
    16.6%
  • More than 4.5 goals
    6.5%
  • More than 5.5 goals
    2.1%
  • Both teams score
    42.7%

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

  • Ivory Coast clean sheetOpposing team scores zero29.4%
  • Norway clean sheetOpposing team scores zero40.7%

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

  • Ivory Coast by 4+
    0.5%
  • Ivory Coast by 3+
    2.4%
  • Ivory Coast by 2+
    9.2%
  • Ivory Coast by 1+
    26.3%
  • Draw
    30.8%
  • Norway by 1+
    42.9%
  • Norway by 2+
    19.4%
  • Norway by 3+
    6.6%
  • Norway by 4+
    1.8%

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 35.7% · BTTS 42.7%

Game state through the match

0%25%50%75%100%0'15'30'45'60'75'90'
  • Ivory Coast ahead27.1%
  • Level29.2%
  • Norway ahead43.7%

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
    29.8%
  • 15–30
    20.9%
  • 30–45
    14.7%
  • 45–60
    10.3%
  • 60–75
    7.2%
  • 75–90
    5.1%
  • No goal
    12.0%

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 →HIvory Coast winDDrawANorway win
HIvory Coast ahead15.6%4.5%1.6%
DLevel10.2%20.6%15.2%
ANorway ahead1.1%4.5%26.8%

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

  • Ivory Coast trail at HT, avoid defeat at FT
    5.6%
  • Norway trail at HT, avoid defeat at FT
    6.0%

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)
  • Ivory Coast
    60.8%
  • Norway
    39.2%
If Ivory Coast kicks first
  • Ivory Coast
    72.8%
  • Norway
    27.2%
If Norway kicks first
  • Ivory Coast
    49.1%
  • Norway
    50.9%
Expected paired rounds
4.8
Decided in regulation 5 kicks
73.8%

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: Ivory Coast conv 73.3%, save 26.7%Norway conv 72.0%, save 20.0%. Smoothed against the global prior with prior strength 20 — see /docs/methodology/.

Equipos y jugadores

Top scorer: Haaland (11.9%)

Match detail

Ivory Coast

Model-rated key players: Franck Kessié (MF) — P(scores) 8.1%; Simon Adingra (FW) — P(scores) 1.5%; Jérémie Boga (FW) — P(scores) 1.4%.

How they play

Ivory Coast under Emerse Faé play a possession dominant game, holding 58% of the ball — among the highest in the tournament field. They press intensely (PPDA 13.7, 2nd in the field).

What they must execute

To succeed, Ivory Coast must control tempo and territory in midfield — their possession-dominant approach depends on dictating the rhythm of each match.

Storylines
Form trend: Gained 87 international Elo points over the last 12 months — current rating 1795.
Teen starter: Yan Diomande19 at kickoff — 9 caps — projected on the bench, the squad's youngest pick.
Touchline: Emerse FaéFirst World Cup as head coach, appointed 2024.

Norway

Model-rated key players: Erling Haaland (FW) — P(scores) 11.9%; Alexander Sørloth (FW) — P(scores) 4.6%; Erling Braut Haaland (FW) — P(scores) 2.5%.

How they play

Limited recent tournament data is available for Norway's tactical profile. Early indicators suggest a balanced approach.

What they must execute

Norway will need to leverage their strengths while managing the physical demands of a tournament spread across three host countries.

Storylines
Form trend: Gained 88 international Elo points over the last 12 months — current rating 1964.
Scoring form: Averaged 3.36 xG per match across 8 recent internationals — #1 of 35 in the field for attacking output.
Top scorer: Alexander SørlothModel's top anytime-scorer for the team — 35% probability of scoring at least once, rank #1 of all players.
Workload going in

Ivory Coast's predicted XI averages 1,658 club minutes over the 2024-25 season (light load).

Ivory Coast coverage: 60.0% (7/11 XI matched against the FBref Big-5) · Norway: 46.0% (7/11).

Set-piece outlook

Ivory Coast historically converts 16.5% of xG from set-pieces, contributing 0.15 expected set-piece goals in this fixture. Norway converts 13.6% from set-pieces (0.17 expected). Combined, the model expects 0.32 set-piece goals across the 90 minutes.

  • P(Ivory Coast scores set-piece goal) 13.8%
  • P(Norway scores set-piece goal) 15.4%
  • P(set-piece goal in match) 27.1%

Ivory Coast: Nicolas Pépé on corners (13 corners), Ibrahim Sangaré on free kicks (per fbref 2022 23) · Norway: Martin Ødegaard on free kicks (per fbref 2022 23)

Penalty outlook

If a penalty is awarded to Ivory Coast, the model gives 73.3% conversion, 72.0% for Norway. If this match goes to a shootout, the symmetric (coin-toss averaged) win probability is 60.8% Ivory Coast / 39.2% Norway.

Ivory Coast primary PK: Franck Kessié (2/3 in 2021-22, per fbref 2022 23) · Norway primary PK: Erling Haaland (2/2 in 2022-23, 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

Ivory Coast

  1. Oumar DiakitéStrikerCover: Elye Wahi · 0.000.67gap
  2. Ibrahim SangaréDefensive midfieldNo natural backup0.30gap
  3. Ousmane DiomandeCentre-backCover: Emmanuel Agbadou · 0.730.23gap

Norway

  1. Erling HaalandStrikerNo natural backup0.75gap
  2. Alexander SørlothStrikerNo natural backup0.62gap
  3. Martin ØdegaardAttacking midfieldCover: Thelo Aasgaard · 0.310.51gap

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 level168 m
  • Avg temperatureFive-year mean over the tournament window29.4 °C
  • Avg humidity63%
  • Heat stressShade WBGT ~30.8 °CHigh heat stress
  • Pitch surfacetemporary natural grass over artificial turf

Indoor artificial-turf stadium; a temporary natural-grass pitch on a sand root-zone is laid over the turf 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)

Ivory Coast
Norway

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

Ivory Coast

vs Curaçao · avg 7.8

9
Nicolas PepeRW
ATK
DEF
PAS
8
Yahia FofanaGK
ATK
DEF
PAS
8
Amad DialloAM
ATK
DEF
PAS
7
KonanLW
ATK
DEF
PAS
7
PlataRW
ATK
DEF
PAS

Norway

vs France · avg 6.3

8
Erling HaalandST
ATK
DEF
PAS
7
Thelo AasgaardAM
ATK
DEF
PAS
7
Oscar BobbRW
ATK
DEF
PAS
7
Torbjørn HeggemCB
ATK
DEF
PAS
7
Patrick BergCM
ATK
DEF
PAS
6
Jørgen Strand LarsenST
ATK
DEF
PAS
6
Antonio NusaLW
ATK
DEF
PAS
5
Egil SelvikGK
ATK
DEF
PAS
4
Kristian ThorstvedtCM
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.

Ivory Coast
8
Amad Diallo60'–110'

Came on as a substitute and scored a brilliant solo equalizer, completely changing the dynamic of the match.

2goals

Match timeline

60'Came on as a substitute in the 60th minute
74'Amad Diallo scores the equaliser for Ivory Coast, making it 1-1.
110'Ivory Coast scores, goal by Diallo
7
Yahia Fofana6'–128'

Made numerous important saves throughout the match, denying Norway on multiple occasions despite conceding two goals.

6saves

Match timeline

6'Ivory Coast goalkeeper makes a save from a close-range shot
11'Ivory Coast goalkeeper makes another save from a shot inside the box
24'Ivory Coast goalkeeper makes a diving save to deny Norway
41'Ivory Coast goalkeeper makes a save from a powerful free-kick
58'denying Haaland a clear chance in the 58th minute.
128'Ivory Coast goalkeeper makes a save from a Norway attack
Norway
8
Erling Haaland58'–132'

Scored the decisive winning goal for Norway with a clinical finish, securing their victory despite being isolated for much of the first half.

2goals2shots1on target

Match timeline

58'clear chance denied by Yahia Fofana
86'Erling Haaland scores the winning goal for Norway, making it 2-1.
132'Norway scores, goal by Haaland
8
Norway Goalkeeper51'–142'

Made several important saves throughout the match, including a crucial one in added time to preserve the lead.

3saves

Match timeline

51'Norway goalkeeper makes a save from an Ivory Coast shot
90'Norway goalkeeper makes a crucial save in added time.
142'Norway goalkeeper makes a save from an Ivory Coast free-kick
7
Torbjørn Heggem57'–57'

Made a vital goal-line block that prevented Ivory Coast from scoring, preserving Norway's lead.

1blocks

Match timeline

57'Norway defender blocks a shot on the goal line after an Ivory Coast corner
7
Martin Ødegaard39'–39'

Provided the assist for Norway's opening goal, demonstrating his playmaking ability.

Match timeline

39'Provided an assist for Antonio Nuca's opening goal.
7
Oscar Bobb86'–86'

Delivered a crucial pass that directly led to Haaland's winning goal, showcasing his impact from the bench.

Match timeline

86'Provided a crucial pass that led to Erling Haaland's winning goal.

Match observations

  • The match was an exciting, end-to-end contest with both teams creating numerous scoring opportunities.
  • Norway took an early lead, but Ivory Coast fought back with a moment of individual brilliance to equalize.
  • Both goalkeepers were called upon to make several important stops throughout the game.

Entre bastidores

Model-by-model comparison

Ivory Coast vs Norway

High disagreement (25.4%)
ModelWeightHomeDrawAway
EloRating-based strength estimate32%
8.7%
22.0%
69.3%
Dixon-ColesGoal-process model with low-score correction63%
26.4%
29.7%
43.9%
Hierarchical PoissonBayesian model with confederation pooling6%
25.7%
28.3%
46.0%
Bayesian stackingLearned-weight combination
15.3%
27.4%
57.3%
Ensemble (published)Uniform average + isotonic calibration
21.4%
26.5%
52.1%
Home spread: 17.7%
Draw spread: 7.7%
Away spread: 25.4%
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 6
Date:
30 Jun
Venue:
AT&T Stadium, Dallas

a 29°C kickoff modestly suppresses expected scoring at this venue.

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.Rest differential: Ivory Coast have had 5 days since their previous match versus 4 for Norway. Rest and recovery are not model inputs.
Availability

Ivory Coast

Ivory Coast come in at close to full strength.

Norway

Norway come in at close to full strength.

What it means

Ivory Coast and Norway both come in at close to full strength, so the forecast rests on baseline team strength rather than late team-news swings.

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

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