Group H · Matchday 3

SpainvsUruguay

2026-06-26·18:00 localPredictions finalised

Snapshot · 2026-07-14Model 1.0.0Final prediction · locked 26 Jun, 21:07 UTCSpain·Uruguay·Head-to-head →·
Full time · forecast gradedSpain 1 0 UruguayThe locked pre-match forecast has been graded against this result.See the calibration recap →

The forecast

Match-outcome probability

  • Spain win
    49.1%
  • Draw
    29.1%
  • Uruguay win
    21.8%

A 273-point Elo gap frames this as a significant mismatch, yet the model still gives Uruguay a 12% probability of a result — enough to make this more than a formality.

Likeliest score1–016.9%
First goal0-15'29.3%
Both teams score37.7%
Over 2.5 goals34.4%
Top scorerOyarzabal9.9%
Expected goals1.4 - 0.7
Loading pitch visualisation...

Why the model says this

Favoring Spain

  • ·Spain holds a significant ELO rating advantage of 273 points over Uruguay.
  • ·Spain is ranked 1st in FIFA, while Uruguay is 16th, indicating a substantial difference in perceived strength.
  • ·Spain has never lost to Uruguay in 10 head-to-head encounters, recording 5 wins and 5 draws.
  • ·The expected goals model predicts Spain to score 1.52 goals compared to Uruguay's 0.88 goals.

Favoring Uruguay

  • ·The ensemble model's home win probability of 52.4% is considerably lower than the ELO model's 71.8%, suggesting other underlying model components see less of a home advantage.
  • ·Uruguay has secured draws in 3 of their last 6 matches, demonstrating a capacity to avoid defeat.

What the model can't fully price

  • ·Seven players across both squads are carrying fitness doubts, including three projected starters, which the model's current lineup channel does not account for.
  • ·The specific venue and city are not provided, meaning any potential home advantage or environmental factors are not factored into the probabilities.
  • ·The specific motivation for this Group H Matchday 3 fixture (e.g., qualification scenarios) is not explicitly captured by the statistical models.

Form check

Spain

Improving

Spain enters this match in strong form, having secured four wins and two draws in their last six outings. Their defensive record has been particularly impressive, keeping four clean sheets in this period while scoring 15 goals.

Spain has conceded only 2 goals in their last 6 matches.

Uruguay

Steady

Uruguay's recent form is mixed, with two wins, three draws, and one loss in their last six fixtures. They have struggled for goals, scoring only 5 times, and conceded 7, including a 1-5 defeat.

Uruguay has scored 5 goals in their last 6 matches.

Analysis

How it plays out

Spain will dominate the ball. Whether Uruguay can stay organised through long spells without it determines if Spain's possession converts to chances. Spain will expect to hold 68% possession. Uruguay need their shape to stay compact without the ball and be clinical when they win it back.

What decides it

Spain's possession game (68% avg) requires patience in the final third and quick ball recovery when they lose it. Mikel Oyarzabal's 9.7% scoring probability is the highest in this fixture. Containing that output is Uruguay's primary defensive task.

Off the pitch

No major off-pitch asymmetries. This one is decided by the football.

The angle

The model and FIFA ranking diverge by 9 percentage points on Spain. This fixture is a direct test of that disagreement.

Goals & scorelines

Likeliest score 1–0 (16.9%) · xG 1.4 - 0.7

Expected goals

Spain
1.40
Uruguay
0.67

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

Most likely scorelines

  • 1–0
    16.9%
  • 0–0
    13.3%
  • 1–1
    12.6%
  • 2–0
    12.3%
  • 2–1
    8.3%

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
    35.9%
  • 1–0
    24.3%
  • 0–1
    11.4%
  • 1–1
    8.9%
  • 2–0
    8.7%

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
    86.7%
  • More than 1.5 goals
    62.2%
  • More than 2.5 goals
    34.4%
  • More than 3.5 goals
    15.7%
  • More than 4.5 goals
    6.0%
  • More than 5.5 goals
    1.9%
  • Both teams score
    37.7%

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

  • Spain clean sheetOpposing team scores zero51.0%
  • Uruguay clean sheetOpposing team scores zero24.6%

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

  • Spain by 4+
    3.3%
  • Spain by 3+
    10.5%
  • Spain by 2+
    27.3%
  • Spain by 1+
    53.8%
  • Draw
    28.9%
  • Uruguay by 1+
    17.2%
  • Uruguay by 2+
    4.8%
  • Uruguay by 3+
    0.9%
  • Uruguay 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.

How the match unfolds

Over 2.5 goals 34.4% · BTTS 37.7%

Game state through the match

0%25%50%75%100%0'15'30'45'60'75'90'
  • Spain ahead54.6%
  • Level27.5%
  • Uruguay ahead17.9%

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
    29.3%
  • 15–30
    20.7%
  • 30–45
    14.6%
  • 45–60
    10.4%
  • 60–75
    7.3%
  • 75–90
    5.2%
  • No goal
    12.5%

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 →HSpain winDDrawAUruguay win
HSpain ahead34.8%3.9%0.7%
DLevel18.1%20.1%7.2%
AUruguay ahead1.6%3.8%9.9%

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

  • Spain trail at HT, avoid defeat at FT
    5.4%
  • Uruguay trail at HT, avoid defeat at FT
    4.6%

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.

Cards

  • Expected yellow cardsMean of the Poisson on total yellow cards.3.45
  • Total yellows over 2.567.0%
  • Total yellows over 3.545.3%
  • Total yellows over 4.526.5%
  • Any red cardP(at least one red card in the match).9.5%

Referee not yet assigned. Using the 2026 pool-mean per-match rate as a placeholder; the model picks up the referee's personal rate once the assignment is published. Total yellow cards modelled as a Poisson with mean equal to two team baselines plus the referee's deviation from the pool mean. Reds are modelled the same way, independently. See /docs/methodology/.

Teams & players

Top scorer: Oyarzabal (9.9%)

Match detail

Spain

Model-rated key players: Mikel Oyarzabal (FW) — P(scores) 9.9%; Ferran Torres (FW) — P(scores) 4.1%; Lamine Yamal (FW) — P(scores) 3.7%.

How they play

Spain under Luis de la Fuente play a possession dominant game, holding 68% of the ball — among the highest in the tournament field. Their likely shape is a 4-3-3. They press intensely (PPDA 15.7, top quartile (4th of 40)) and build patiently through midfield with 10.0 passes per attacking sequence. They generate a high volume of shots (15.3 per 90).

What they must execute

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

Storylines
Club core: 8 of 26 predicted-squad players play their club football for Barcelona — a single-club spine on the international side.
Club xG: Squad averages 1.85 xG per match across club football last season — #3 of 20 in the field for attacking pedigree from each player's domestic side (23 of 26 players matched to a known club).
Teen starter: Lamine Yamal18 at kickoff — 25 caps — projected on the bench, the squad's youngest pick.

Uruguay

Model-rated key players: Darwin Núñez (FW) — P(scores) 2.9%; Brian Rodríguez (FW) — P(scores) 1.4%; Rodrigo Aguirre (FW) — P(scores) 1.4%.

How they play

Uruguay under Marcelo Bielsa play a balanced game with 49% possession. Their likely shape is a 3-5-2, though they have also used 4-3-3 and 4-4-2. They apply moderate pressing intensity (PPDA 18.0) and move the ball forward quickly at 5.7 passes per attack.

What they must execute

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

Storylines
Veteran #1: Fernando Muslera39 at kickoff with 134 caps — last World Cup for the #1.
Top scorer: Darwin NúñezModel's top anytime-scorer for the team — 22% probability of scoring at least once, rank #23 of all players.
Heat schedule: 2 group-stage matches at venues averaging 26°C+ — Miami, Miami (peak 27.0°C average).
Workload going in

Spain's predicted XI averages 1,633 club minutes over the 2024-25 season (light load).

Spain coverage: 81.0% (9/11 XI matched against the FBref Big-5) · Uruguay: 43.0% (8/11).

Set-piece outlook

Spain historically converts 17.4% of xG from set-pieces, contributing 0.24 expected set-piece goals in this fixture. Uruguay converts 15.4% from set-pieces (0.10 expected). Combined, the model expects 0.35 set-piece goals across the 90 minutes.

  • P(Spain scores set-piece goal) 21.7%
  • P(Uruguay scores set-piece goal) 9.9%
  • P(set-piece goal in match) 29.5%

Spain: Mikel Oyarzabal on corners (56 corners), Aleix García on free kicks (per fbref 2021 22) · Uruguay: Nahitan Nández on corners (5 corners), Lucas Torreira on free kicks (per fbref 2021 22)

Penalty outlook

If a penalty is awarded to Spain, the model gives 72.5% conversion, 73.3% for Uruguay.

Spain primary PK: Mikel Oyarzabal (4/5 in 2021-22, per fbref 2021 22).

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.

Tactical forecast

Spainpossession-dominant
PPDA
15.7
Possession
68%
Directness (yds/pass)
3.1
Long balls/90
21
Set-piece xG
17%
Uruguaybalanced
PPDA
18.0
Possession
49%
Directness (yds/pass)
7.6
Long balls/90
35
Set-piece xG
15%

Style profile per side from StatsBomb open-data aggregation across recent international tournaments (Euro 2020/2024, Copa America 2024, AFCON 2023, World Cup 2018/2022). The tactical-fingerprint badge maps each team’s observed style vector into one of eight canonical archetypes via a rule-based classifier; teams with fewer than three matches of qualifying coverage carry an “insufficient-data” label rather than being forced into a default. Sides outside the StatsBomb-open corpus use FotMob team match stats from recent qualifiers and friendlies instead (possession and shot volume only), marked as partial coverage. PPDA = passes the side allows per defensive action (lower = more intense press). Formation distributions are not yet produced — that head of the §2.7 classifier is pending its own data pull. See /docs/methodology/.

Squad depth

Most irreplaceable starters

Spain

  1. Dani OlmoAttacking midfieldNo natural backup0.51gap
  2. RodriDefensive midfieldCover: Martín Zubimendi · 0.390.27gap
  3. Ferran TorresStrikerCover: Borja Iglesias · 0.650.26gap

Uruguay

  1. Nicolás de la CruzCentral midfieldNo natural backup0.53gap
  2. Darwin NúñezStrikerCover: Agustín Álvarez · 0.520.46gap
  3. Federico ValverdeCentral midfieldNo natural backup0.45gap

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

High-altitude venue. Guadalajara sits at 1,565 m above sea level — thinner air affects stamina and ball flight.

  • AltitudeHigh altitude1,565 m
  • Avg temperatureFive-year mean over the tournament window20.2 °C
  • Avg humidity76%
  • Heat stressShade WBGT ~22.4 °CLow heat stress
  • Pitch surfacenatural grass

Natural-grass football stadium.

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)

Uruguay

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

Spain

vs Austria · avg 8.0

8
Mikel OyarzabalAM
ATK
DEF
PAS
8
Dani OlmoAM
ATK
DEF
PAS
8
Pedro PorroRB
ATK
DEF
PAS
8
Marc CucurellaLB
ATK
DEF
PAS

Worked well: Their ability to create a high volume of chances, combined with effective finishing for three goals, proved decisive. The full-backs' forward runs were particularly impactful.

Struggled: Spain could have been more efficient with their finishing, as several clear-cut opportunities, including shots hitting the woodwork, were not converted.

Uruguay

vs Cape Verde · avg 8.0

8
Luis SuarezST
ATK
DEF
PAS
8
Uruguay Player #9ST
ATK
DEF
PAS

Worked well: Showed strong fighting spirit and clinical finishing in key moments, particularly from their number 13, to secure two equalisers.

Struggled: Also conceded two goals, indicating that their defense was not impenetrable and allowed Uruguay to regain the lead at one point.

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.

Spain
8
Mikel Oyarzabal37'–37'

Scored the crucial opening goal with a clinical finish from inside the box.

2goals

Match timeline

37'Mikel Oyarzabal scores for Spain with a clinical finish from inside the box.
8
Borja Mayoral

Scored Spain's second goal by arriving in the box with excellent timing and a well-placed finish.

8
Marc Cucurella88'–88'

Secured Spain's third goal with a decisive forward run and clinical finish from a defensive position.

2goals

Match timeline

88'Marc Cucurella scores Spain's third goal with a well-timed run and finish.
7
Fabián Ruiz

Registered a powerful shot on goal that required a brilliant save from the opposition goalkeeper.

1shots1on target

Match timeline

7
Álex Baena59'–59'

Came very close to scoring, hitting the post and forcing a good save with powerful shots.

2goals3shots1on target

Match timeline

59'Spain hits the post with a shot from Baena.
7
M. ARAUJO

Displayed composure in possession and actively contributed to Spain's offensive build-up from the back.

7
Aymeric Laporte

Played a key role in Spain's ball distribution from the defensive line, maintaining possession and initiating attacks.

Match timeline

Uruguay
9
Alexander Schlager

Made multiple brilliant and crucial saves, preventing a much larger deficit for his team.

8
Nicolás de la Cruz

Was instrumental in creating offensive opportunities for Uruguay through his dribbling and passing.

Match timeline

Match observations

  • Spain delivered a dominant performance, showcasing their attacking flair and control of the midfield.
  • Austria's goalkeeper, Alexander Schlager, was a standout performer, making numerous saves to prevent a larger deficit.
  • Spain's persistent pressure and intricate passing eventually broke down the Austrian defense, leading to three well-taken goals.

Under the hood

Model-by-model comparison

Spain vs Uruguay

High disagreement (21.4%)
ModelWeightHomeDrawAway
EloRating-based strength estimate32%
75.3%
22.0%
2.8%
Dixon-ColesGoal-process model with low-score correction63%
54.8%
28.4%
16.8%
Hierarchical PoissonBayesian model with confederation pooling6%
53.8%
27.7%
18.5%
Bayesian stackingLearned-weight combination
67.0%
28.4%
4.6%
Ensemble (published)Uniform average + isotonic calibration
60.6%
27.3%
12.1%
Home spread: 21.4%
Draw spread: 6.4%
Away spread: 15.7%
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

Probability decomposition (transparency surface)

  • Baseline ensemble — P(Spain win)57.4%
  • + Lineup contribution0.0pp
  • + Style-matchup contribution0.0pp
  • Published P(Spain win)57.4%
Spain
57.4%
Draw
26.5%
Uruguay
16.1%

Decomposition of the published P(Spain win) into the calibrated- baseline plus contributions from the §2.3 expected-XI lineup delta and the §2.7 style-matchup interaction. The §2.7 roadmap is explicit that style effects are second-order to team strength — single-digit-percentage P(win) shifts on extreme style matchups, near-zero on balanced ones. We surface the decomposition for transparency even when the contributions are small; the baseline carries the prediction. Methodology: /docs/methodology.

For this fixture both contributions round to under 0.05pp — the fitted style-matchup pair effect is in the small-magnitude regime the model expects to dominate.

Head-to-head history

DateCompetitionVenueScoreResultxG
16 Jun 2013Confederations CupNRecife21W
6 Feb 2013FriendlyNDoha31W
17 Aug 2005FriendlyHGijón20W
18 Jan 1995FriendlyHA Coruña22D
4 Sep 1991FriendlyHOviedo21W
13 Jun 1990FIFA World CupNUdine00D

Spain vs Uruguay, every senior international meeting in the martj42 results dataset (score from Spain's perspective; H/A/N = home/away/neutral). See all 10 meetings →

Latest news & match context

Match conditions
Stage:
Group H · Matchday 3
Date:
26 Jun
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.
Availability

Spain

Spain come in at close to full strength.

Uruguay

Uruguay: 1 carrying a fitness doubt.

  • DoubtGiorgian de Arrascaeta, the second-choice midfielder, is recovering from Muscle injury and is a fitness watch item; if unavailable the projected XI shifts.
What it means

Availability runs in Spain's favour here: Uruguay are managing a fitness concern over Giorgian de Arrascaeta, while Spain's projected XI looks intact.

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

Standard Pass

This match is a free preview

You're seeing the model's full forecast for this fixture for free. Unlock the same depth: probabilities, expected goals, scoreline distributions, and per-player scoring, for all 104 matches with a Standard Pass, valid through the tournament.

Get the Pass, $15

Every forecast graded against the real result, scored on 987 matches since 2014. See the scorecard.

24h money-back, no questions asked·No subscription, no auto-renewal·Access through 31 Dec 2026. See refund policy.