Group G · Matchday 3
EgyptvsIran
2026-06-26·20:00 localPredictions finalised
The forecast
Match-outcome probability
- Egypt win27.1%
- Draw32.7%
- Iran win40.3%
The model projects one of the most closely-contested fixtures of the round — Egypt and Iran are separated by fine margins across every outcome.
Why the model says this
Favoring Egypt
- ·Egypt has a strong set-piece reliance, generating 82.9% of their xG from set pieces.
- ·Egypt has won 3 of their last 6 matches, including a 4-0 victory against an unnamed opponent.
- ·Egypt has conceded only 3 goals in their last 6 matches, keeping 3 clean sheets.
Favoring Iran
- ·Iran holds a higher FIFA ranking at 20th, compared to Egypt's 34th.
- ·The Elo model favours Iran by 71 points.
- ·Iran's expected goals (xG) for this match is 0.98, higher than Egypt's 0.81.
- ·Iran's style is highly direct (98.8 percentile), which could be effective in transitions.
What the model can't fully price
- ·Four players across both squads are carrying fitness doubts, with one projected starter, a factor not adjusted for by the model's current lineup channel.
Form check
Egypt
SteadyEgypt's recent form shows a mix of results, with 3 wins, 2 draws, and 1 loss in their last six outings. They have demonstrated attacking prowess with 10 goals scored and defensive solidity with 3 clean sheets in this period.
3 wins in their last 6 matches
Iran
SteadyIran's recent performances have been inconsistent, recording 2 wins, 2 draws, and 2 losses in their last six fixtures. While they showed strong attacking potential with a 5-0 victory, their overall results indicate variability.
Scored 5 goals in their most recent win
Analysis
How it plays out
Egypt's pragmatic setup will need to hold shape against Iran's direct transition game. The risk for Egypt: getting caught between attacking and defending. Egypt's aggressive press (PPDA 21.8) against Iran's deeper build-up (PPDA 29.0) creates a clear territory question: can Egypt force errors high up, or will Iran play through the press and find space behind it?
What decides it
Egypt adjust shape to the opponent. That flexibility is an asset, but it takes longer to settle into a game. Iran will concede possession willingly and attack in transition. Their defensive block needs to hold without fouling in dangerous areas. Mohamed Salah's 14.8% scoring probability is the highest in this fixture. Containing that output is Iran's primary defensive task.
Off the pitch
No major off-pitch asymmetries. This one is decided by the football.
The angle
Likely the last World Cup for Ehsan Hajsafi. Tournament experience at this level is hard to quantify but hard to replace.
▸Goals & scorelines
Likeliest score 0–0 (19.8%) · xG 0.8 - 0.9
Expected goals
Mean of the Dixon-Coles joint goal distribution. Same fit that produces the most-likely-scoreline list below.
Most likely scorelines
- 0–019.8%
- 0–115.9%
- 1–014.1%
- 1–113.9%
- 0–27.3%
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
- 0–044.0%
- 0–118.7%
- 1–016.6%
- 1–18.0%
- 0–24.2%
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 goals80.2%
- More than 1.5 goals50.3%
- More than 2.5 goals23.3%
- More than 3.5 goals8.8%
- More than 4.5 goals2.7%
- More than 5.5 goals0.7%
- Both teams score32.6%
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
- Egypt clean sheetOpposing team scores zero41.6%
- Iran clean sheetOpposing team scores zero45.6%
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
- Egypt by 4+0.4%
- Egypt by 3+2.2%
- Egypt by 2+9.5%
- Egypt by 1+29.3%
- Draw36.0%
- Iran by 1+34.6%
- Iran by 2+12.3%
- Iran by 3+3.2%
- Iran by 4+0.7%
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 23.3% · BTTS 32.6%
Game state through the match
- Egypt ahead30.1%
- Level34.5%
- Iran ahead35.4%
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
- 0–1524.2%
- 15–3018.3%
- 30–4513.9%
- 45–6010.5%
- 60–758.0%
- 75–906.1%
- No goal19.0%
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
| HT ↓ / FT → | HEgypt win | DDraw | AIran win |
|---|---|---|---|
| HEgypt ahead | 17.3% | 3.9% | 1.0% |
| DLevel | 11.8% | 26.9% | 13.6% |
| AIran ahead | 0.9% | 4.0% | 20.7% |
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
- Egypt trail at HT, avoid defeat at FT4.8%
- Iran trail at HT, avoid defeat at FT4.9%
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.
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: Salah (14.9%)
Match detail
Egypt
Model-rated key players: Mohamed Salah (FW) — P(scores) 14.9%; Omar Marmoush (FW) — P(scores) 9.2%; Trézéguet (FW) — P(scores) 6.3%.
Egypt under Hossam Hassan play a pragmatic game with 51% possession. They apply moderate pressing intensity (PPDA 21.8). They generate a high volume of shots (13.7 per 90).
Egypt play a pragmatic, results-oriented game that adapts shape to the opposition. Tactical flexibility is their strength. The risk is inconsistency — without a default identity, a poor result can cascade if the team struggles to find a Plan B. Managing the fitness of Mohamed Salah could prove decisive — their availability transforms the team's ceiling.
Iran
Model-rated key players: Mehdi Taremi (FW) — P(scores) 1.9%; Mehdi Ghayedi (FW) — P(scores) 1.4%; Shahriyar Moghanlou (FW) — P(scores) 1.3%.
Iran under Amir Ghalenoei play a transition heavy game, with just 33% possession — among the lowest in the field. Their likely shape is a 4-4-2, though they have also used other. They sit deeper and pick their moments to press (PPDA 29.0) and move the ball forward quickly at 4.5 passes per attack. They are selective in their shooting (8.4 per 90).
Iran 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. Managing minutes for Ehsan Hajsafi across what could be seven matches will test the coaching staff's rotation planning.
Egypt historically converts 17.3% of xG from set-pieces, contributing 0.14 expected set-piece goals in this fixture. Combined, the model expects 0.14 set-piece goals across the 90 minutes.
- P(Egypt scores set-piece goal) 12.7%
- P(set-piece goal in match) 12.7%
If a penalty is awarded to Egypt, the model gives 75.0% conversion, 73.3% for Iran.
Egypt primary PK: Mohamed Salah (5/6 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
- PPDA
- 21.8
- Possession
- 51%
- Directness (yds/pass)
- 6.0
- Long balls/90
- 33
- Set-piece xG
- 17%
- PPDA
- 29.0
- Possession
- 33%
- Directness (yds/pass)
- 10.6
- Long balls/90
- 46
- Set-piece xG
- —
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
Egypt
- Omar MarmoushStrikerNo natural backup0.69gap
- Mohamed SalahWingerCover: Ibrahim Adel · 0.390.35gap
- Emam AshourCentral midfieldCover: Mahmoud Saber · 0.130.26gap
Iran
- Mehdi TaremiStrikerCover: Ali Alipour · 0.270.39gap
- Alireza JahanbakhshWingerCover: Mohammad Mohebi · 0.530.30gap
- Hossein KanaanizadeganCentre-backCover: Ali Nemati · 0.270.22gap
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)
- Mohamed SalahPKFW14.9%
- Omar MarmoushFW9.2%
- TrézéguetFW6.3%
- Mehdi TaremiFW1.9%
- Mehdi GhayediFW1.4%
- Shahriyar MoghanlouFW1.3%
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
Egypt
vs Australia · avg 6.1
Iran
vs Belgium · avg 6.4
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.
9TrézéguetScored two crucial goals and consistently posed an offensive threat with powerful shots and dribbling.
1goals2shots1on target▼
Scored two crucial goals and consistently posed an offensive threat with powerful shots and dribbling.
Match timeline
7Mohanad LasheenMade a vital defensive block to prevent a goal during a dangerous Iranian attack.
1blocks▼
Made a vital defensive block to prevent a goal during a dangerous Iranian attack.
Match timeline
7SentolanMade a critical defensive block from an Iranian corner, clearing the danger.
1blocks▼
Made a critical defensive block from an Iranian corner, clearing the danger.
Match timeline
6Mostafa ShobeirMade a vital penalty save but also mishandled a ball leading to a disallowed goal, balancing his performance.
2saves▼
Made a vital penalty save but also mishandled a ball leading to a disallowed goal, balancing his performance.
Match timeline
8Ramin RezaeianScored Iran's equalizing goal with good positioning and composure in a crowded area.
1goals▼
Scored Iran's equalizing goal with good positioning and composure in a crowded area.
Match timeline
7RaminProvided a crucial assist for Iran's equalizer, showing good composure and vision.
Provided a crucial assist for Iran's equalizer, showing good composure and vision.
7Mehdi GhayediTapped in a goal to equalize for Iran, demonstrating good positioning.
Tapped in a goal to equalize for Iran, demonstrating good positioning.
6Alireza JahanbakhshContributed to attacking efforts with a header from a corner, though it was saved.
1shots1on target▼
Contributed to attacking efforts with a header from a corner, though it was saved.
Match timeline
4Mehdi TaremiHis missed penalty was a significant setback for Iran, and no other significant positive impact was mentioned.
1shots1on target▼
His missed penalty was a significant setback for Iran, and no other significant positive impact was mentioned.
Match timeline
Match observations
- Iran secured a convincing victory over Jordan in this World Cup Qualifier match, maintaining a comfortable lead throughout the highlights.
- Their offensive strategy, featuring strong drives to the basket and effective three-point shooting, proved difficult for Jordan to contain.
- The home crowd provided a lively atmosphere, but it was not enough to shift the momentum decisively in Jordan's favour.
▸Under the hood
Model-by-model comparison
Egypt vs Iran
| Model | Weight | Home | Draw | Away |
|---|---|---|---|---|
| EloRating-based strength estimate | 32% | 33.6% | 22.0% | 44.5% |
| Dixon-ColesGoal-process model with low-score correction | 63% | 29.7% | 35.2% | 35.1% |
| Hierarchical PoissonBayesian model with confederation pooling | 6% | 29.0% | 33.6% | 37.5% |
| Bayesian stackingLearned-weight combination | — | 29.6% | 34.3% | 36.1% |
| Ensemble (published)Uniform average + isotonic calibration | — | 27.7% | 33.0% | 39.4% |
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
Probability decomposition (transparency surface)
- Baseline ensemble — P(Egypt win)27.7%
- + Lineup contribution0.0pp
- + Style-matchup contribution0.0pp
- Published P(Egypt win)27.7%
Decomposition of the published P(Egypt 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
| Date | Competition | Venue | Score | Result | xG |
|---|---|---|---|---|---|
| 7 Jun 2000 | Friendly | ATehran | 1–1(pens) | W | — |
Egypt vs Iran, every senior international meeting in the martj42 results dataset (score from Egypt's perspective; H/A/N = home/away/neutral).
Latest news & match context
No recent headlines for Egypt or Iran.
- Stage:
- Group G · Matchday 3
- Date:
- 26 Jun
Egypt and Iran 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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