Group G · Matchday 2
EgyptvsNew Zealand
2026-06-21·18:00 localPredictions finalised
The forecast
Match-outcome probability
- Egypt win48.0%
- Draw30.1%
- New Zealand win21.9%
A clash of identities: Egypt's pragmatic approach meets New Zealand's balanced style in a fixture the model gives to Egypt at 61%.
Why the model says this
Favoring Egypt
- ·Egypt holds a significant Elo advantage, with a 104-point gap over New Zealand.
- ·Egypt is ranked 34th in FIFA, considerably higher than New Zealand at 86th.
- ·Egypt has a strong historical record against New Zealand, winning 2 and drawing 1 of their 3 encounters, including a 1-0 victory in their most recent match on 2024-03-22.
- ·The model projects Egypt to generate substantially more expected goals (1.23 xG) compared to New Zealand (0.49 xG).
Favoring New Zealand
- ·New Zealand's ensemble win probability of 21.9% is notably higher than the 12.0% predicted by the stacking model and 14.1% by the DC model, suggesting some factors might be mitigating Egypt's advantage.
- ·New Zealand demonstrated attacking capability in their most recent fixture, securing a 4-1 victory in the FIFA Series.
What the model can't fully price
- ·Six players across both squads are carrying fitness doubts, including two projected starters. The model's current lineup channel does not account for the impact of these potential absences.
Form check
Egypt
SteadyEgypt's recent form shows a mixed bag of results, with 3 wins, 2 draws, and 1 loss in their last six matches. They have demonstrated defensive solidity with two clean sheets, but also experienced two goalless draws, indicating some inconsistency in their attacking output.
Scored 10 goals and conceded 4 in their last six matches.
New Zealand
DecliningNew Zealand's recent form has been challenging, recording only 1 win, 1 draw, and 4 losses in their last six fixtures. While their most recent match was a convincing 4-1 victory, this followed a period of four winless games where they struggled to score, netting only 1 goal.
Secured only 1 win in their last six matches.
Analysis
How it plays out
Neither side has a rigid tactical identity. Both adapt to the opponent, so the first 15 minutes will reveal who imposes their plan first. Egypt will expect to hold 51% possession. New Zealand need their shape to stay compact without the ball and be clinical when they win it back.
What decides it
Egypt adjust shape to the opponent. That flexibility is an asset, but it takes longer to settle into a game. The scoring threat is evenly split: Mohamed Salah (13.5%) and Chris Wood (11.4%).
Off the pitch
No major off-pitch asymmetries. This one is decided by the football.
The angle
A Group G fixture where the result matters more for the standings than the headlines.
▸Goals & scorelines
Likeliest score 1–0 (21.8%) · xG 1.3 - 0.5
Expected goals
Mean of the Dixon-Coles joint goal distribution. Same fit that produces the most-likely-scoreline list below.
Most likely scorelines
- 1–021.8%
- 0–018.1%
- 2–014.4%
- 1–110.9%
- 0–17.4%
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
- 0–042.2%
- 1–026.5%
- 0–19.2%
- 2–08.6%
- 1–16.5%
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 goals81.9%
- More than 1.5 goals52.7%
- More than 2.5 goals25.4%
- More than 3.5 goals10.0%
- More than 4.5 goals3.3%
- More than 5.5 goals0.9%
- Both teams score27.3%
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
- Egypt clean sheetOpposing team scores zero63.2%
- New Zealand clean sheetOpposing team scores zero27.7%
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
- Egypt by 4+2.9%
- Egypt by 3+10.1%
- Egypt by 2+27.6%
- Egypt by 1+56.8%
- Draw30.7%
- New Zealand by 1+12.6%
- New Zealand by 2+2.6%
- New Zealand by 3+0.4%
- New Zealand 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 25.4% · BTTS 27.3%
Game state through the match
- Egypt ahead57.4%
- Level29.4%
- New Zealand ahead13.2%
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
- 0–1525.2%
- 15–3018.9%
- 30–4514.1%
- 45–6010.5%
- 60–757.9%
- 75–905.9%
- No goal17.5%
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
| HT ↓ / FT → | HEgypt win | DDraw | ANew Zealand win |
|---|---|---|---|
| HEgypt ahead | 36.4% | 3.0% | 0.4% |
| DLevel | 19.7% | 23.6% | 5.7% |
| ANew Zealand ahead | 1.1% | 3.0% | 7.0% |
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 FT4.1%
- New Zealand trail at HT, avoid defeat at FT3.4%
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 (13.5%)
Match detail
Egypt
Model-rated key players: Mohamed Salah (FW) — P(scores) 13.5%; Omar Marmoush (FW) — P(scores) 7.1%; Trézéguet (FW) — P(scores) 4.8%.
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.
New Zealand
Model-rated key players: Chris Wood (FW) — P(scores) 11.4%; Ben Waine (FW) — P(scores) 2.4%; Kosta Barbarouses (FW) — P(scores) 2.4%.
Limited recent tournament data is available for New Zealand's tactical profile. Early indicators suggest a balanced approach.
New Zealand will need to leverage their strengths while managing the physical demands of a tournament spread across three host countries.
Egypt historically converts 17.3% of xG from set-pieces, contributing 0.22 expected set-piece goals in this fixture. New Zealand converts 6.0% from set-pieces (0.03 expected). Combined, the model expects 0.25 set-piece goals across the 90 minutes.
- P(Egypt scores set-piece goal) 19.9%
- P(New Zealand scores set-piece goal) 2.8%
- P(set-piece goal in match) 22.1%
If a penalty is awarded to Egypt, the model gives 75.0% conversion, 76.0% for New Zealand.
Egypt primary PK: Mohamed Salah (5/6 in 2021-22, per fbref 2021 22) · New Zealand primary PK: Chris Wood (1/1 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%
Partial coverage from FotMob match stats (recent qualifiers and friendlies): possession and shot volume only. Press and build-up metrics are not available for this side.
- PPDA
- —
- Possession
- 44%
- Directness (yds/pass)
- —
- Long balls/90
- —
- Set-piece xG
- 6%
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
New Zealand
- Marko StamenićCentral midfieldCover: Lachlan Bayliss · 0.000.58gap
- Chris WoodStrikerNo natural backup0.45gap
- Liberato CacaceFull-backCover: Ben Old · 0.280.26gap
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 level3 m
- Avg temperatureFive-year mean over the tournament window17.4 °C
- Avg humidity73%
- Heat stressShade WBGT ~19.5 °CLow heat stress
- Pitch surfacetemporary natural grass over artificial turf
Artificial-turf stadium with a retractable roof; a temporary natural-grass pitch 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. 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 SalahPKFW13.5%
- Omar MarmoushFW7.1%
- TrézéguetFW4.8%
- Chris WoodPKFW11.4%
- Ben WaineFW2.4%
- Kosta BarbarousesFW2.4%
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
New Zealand
vs Belgium · avg 6.0
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.
9Omar MarmoushScored two crucial goals with clinical finishing, putting Egypt back in the lead twice.
Scored two crucial goals with clinical finishing, putting Egypt back in the lead twice.
9Mohamed SalahDelivered a standout offensive display with a powerful long-range goal and a composed penalty conversion.
2goals▼
Delivered a standout offensive display with a powerful long-range goal and a composed penalty conversion.
Match timeline
Match observations
- This was a high-scoring and dynamic encounter, with both teams showcasing their attacking prowess.
- Egypt established an early lead with two well-taken goals, but New Zealand displayed resilience to draw level.
- The match featured several momentum swings, keeping the contest exciting until Egypt ultimately secured the victory.
▸Under the hood
Model-by-model comparison
Egypt vs New Zealand
| Model | Weight | Home | Draw | Away |
|---|---|---|---|---|
| EloRating-based strength estimate | 32% | 58.5% | 22.0% | 19.5% |
| Dixon-ColesGoal-process model with low-score correction | 63% | 57.7% | 29.7% | 12.6% |
| Hierarchical PoissonBayesian model with confederation pooling | 6% | 55.2% | 29.3% | 15.5% |
| Bayesian stackingLearned-weight combination | — | 63.0% | 29.9% | 7.1% |
| Ensemble (published)Uniform average + isotonic calibration | — | 60.7% | 29.4% | 9.9% |
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)47.9%
- + Lineup contribution0.0pp
- + Style-matchup contribution0.0pp
- Published P(Egypt win)47.9%
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 |
|---|---|---|---|---|---|
| 21 Jun 2026 | FIFA World Cup | NVancouver | 3–1 | W | — |
| 22 Mar 2024 | FIFA Series | HCairo | 1–0 | W | — |
| 15 Jul 1999 | Friendly | NGuadalajara | 1–0 | W | — |
| 10 Jul 1999 | Friendly | NMexico City | 1–1 | D | — |
Egypt vs New Zealand, 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 New Zealand.
- Stage:
- Group G · Matchday 2
- Date:
- 21 Jun
Egypt
Egypt come in at close to full strength.
New Zealand
New Zealand come in at close to full strength.
Egypt and New Zealand 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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