WC 2026 · Forecasting Oxford Football Forecasting
🇪🇬

Egypt

CAF Group G
0.1% Champion probability ±0.01 MC-SE
Coach
Hossam Hassan home · Egyptian
Elo (model)
1,696 world 40th
Squad value
€176M
Power → Reality
33rd 33rd +0.02 pp · neutral draw

Fig. D1 Fixture-aware · 100k sims

Egypt — stage progression

Round of 32: 67.63% (95% MC 67.34%–67.92%; MC-SE ±0.15 pts) Round of 32 reach 67.6% ±0.15 Round of 16: 28.14% (95% MC 27.86%–28.42%; MC-SE ±0.14 pts) Round of 16 reach 28.1% ±0.14 Quarter-final: 8.36% (95% MC 8.18%–8.53%; MC-SE ±0.09 pts) Quarter-final reach 8.4% ±0.09 Semi-final: 2.19% (95% MC 2.10%–2.28%; MC-SE ±0.05 pts) Semi-final reach 2.2% ±0.05 Final: 0.55% (95% MC 0.51%–0.60%; MC-SE ±0.02 pts) Final reach 0.6% ±0.02 Champion: 0.12% (95% MC 0.10%–0.15%; MC-SE ±0.01 pts) Champion reach 0.1% ±0.01

On the central forecast, Egypt more likely than not reaches the Round of 32 (68%). Champion probability is 0.1% ± 0.01 pts.

Source · Oxford Football Forecasting model
Group G Confed Advance (top 2) Reach R32
1🇧🇪BelgiumUEFA61.9%93.9%
2🇮🇷IR IranAFC39.5%79.4%
3🇪🇬EgyptCAF28.1%67.6%
4🇳🇿New ZealandOFC6.0%27.6%

Source · Oxford Football Forecasting model

Bracket position Half 0 · Quadrant 1

Earliest possible meetings

No collision rows recorded for this team.

Collision = the earliest round the bracket wiring could pit Egypt against that side. Full bracket & collision matrix →

Match 16 · 2026-06-15 · Seattle Stadium away
Egypt Belgium
18.6% win 28.5% draw 52.9% loss
Most likely 0–1 (14.8%) λ 0.77–1.47 Over 2.5 39% · BTTS 42%
Match 40 · 2026-06-22 · BC Place Vancouver away
Egypt New Zealand
50.1% win 31.3% draw 18.6% loss
Most likely 1–0 (17.1%) λ 1.28–0.67 Over 2.5 31% · BTTS 36%
Match 63 · 2026-06-27 · Seattle Stadium home
Egypt IR Iran
27.5% win 32.7% draw 39.8% loss
Most likely 0–0 (14.7%) λ 0.88–1.12 Over 2.5 32% · BTTS 40%
How a match forecast is built

Each pairing is scored by the ensemble (Dixon-Coles bivariate-Poisson, the Bayesian hierarchical model and the global LightGBM-Poisson, log-pooled), producing an 11×11 scoreline grid that is marginalised into win/draw/loss, expected goals (λ), over/under 2.5 and both-teams-to-score. These are the same distributions the tournament simulator consumes, oriented here to Egypt. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.

Fig. D2 Relative to the 48-team median

Egypt vs the field

Elo rating: 1696 vs field median 1780 (0.95× the field) Elo rating 1696 med 1780 Recent NT form: 1.60 ppg vs field median 1.87 ppg (0.86× the field) Recent NT form 1.60 ppg med 1.87 ppg Squad value: €176M vs field median €286M (0.62× the field) Squad value €176M med €286M Squad form (global): 0.158 vs field median 0.211 (0.75× the field) Squad form (global) 0.158 med 0.211 Fitness readiness: 0.661 vs field median 0.707 (0.93× the field) Fitness readiness 0.661 med 0.707 Familiarity / chemistry: 0.108 vs field median 0.015 (6.99× the field) Familiarity / chemistry 0.108 med 0.015 Experience (mean caps): 24 vs field median 25 (0.97× the field) Experience (mean caps) 24 med 25

Read each row as a multiple of the field median: dots to the right of the dashed line are above-field, to the left below. Raw values are labelled on the right so the comparison is transparent.

Source · Oxford Football Forecasting model

Fig. D3 Bayesian projection residual g

Egypt on the decoupling axis

aligned (0) ← record > squad price squad valued > record →

g = +0.25 ± 0.06: the squad is valued above its record — the transfer market rates this side above what its results have earned.

Source · Oxford Football Forecasting model
What g means — and its limits

g is the residual from regressing a team’s current squad market value on its history-based strength in the Bayesian hierarchical model. Positive g means the squad is valued above what the team’s record predicts; negative means the record outruns the squad’s price (the side achieves more than its market value implies). Regressed on out-of-sample success the slope is positive — squad-rich sides go a touch further — but not statistically significant at n = 3 tournaments, so treat a single team’s g as a descriptive read, not a hard prediction. The full decoupling essay →

26players
27.5mean age
24mean caps
15%in a top-5 league
14distinct clubs
8largest club bloc
# Player Pos Club League Club min Gls Caps NT gls
1Mohamed El ShenawyGKAl AhlyPremier League −0.83z1,4290760
2Yasser IbrahimDFAl AhlyPremier League −0.83z2,2762171
3Mohamed HanyDFAl AhlyPremier League −0.83z2,6820420
4Hossam AbdelmaguidDFZamalekPremier League −0.83z3,3176130
5Ramy RabiaDFAl AinPro League −0.09z8101445
6Mohamed AbdelmonemDFNiceno club data363
7TrézéguetFWAl AhlyPremier League −0.83z2,389189623
8Emam AshourMFAl AhlyPremier League −0.83z1,2582290
9Hamza AbdelkarimFWBarcelona Bno club data20
10Mohamed Salah (captain)FWLiverpoolPremier League +2.21z3,2441311667
11Mostafa ZikoMFPyramidsPremier League −0.83z1,494822
12Haissem HassanFWOviedoLa Liga +2.13z2,024040
13Ahmed FatouhDFZamalekPremier League −0.83z1,5641391
14Hamdy FathyMFAl-WakrahStars League −2.20z7721633
15Karim HafezDFPyramidsPremier League −0.83z1,548290
16El Mahdy SolimanGKZamalekPremier League −0.83z1,406000
17Mohanad LasheenMFPyramidsPremier League −0.83z2,8120230
18Nabil EmadMFAl-NajmaPro League −0.86z9140120
19Marwan AttiaMFAl AhlyPremier League −0.83z2,2290341
20Ibrahim AdelFWNordsjællandSuperliga −0.53z6293243
21Mahmoud SaberMFZEDno club data151
22Omar MarmoushFWManchester CityPremier League +2.21z1,80364911
23Mostafa ShobeirGKAl AhlyPremier League −0.83z1,631090
24Tarek AlaaDFZEDno club data30
25ZizoFWAl AhlyPremier League −0.83z1,7785635
26Mohamed AlaaGKEl GounaPremier League −0.83z2,520000

Source · Official squad announcements · API-Football (global club coverage). 4 of 26 players have no club season matched in API-Football — shown as “— no club data”, not imputed. Form coverage for this squad: 85%.

Diaspora in the hosts

274,801

2.0 per 1,000 of home population

Host-language familiarity

Foreign

primary language Arabic

Climate adaptation gap

−13.6°C

home-vs-venue heat differential

Venue extremes

23°C

peak heat index · altitude up to 14 m

Travel

10h

max time-zone shift · nearest venue 8,748 km

Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records

Fig. D4 eloratings.net method · year-end values

Egypt — Elo since 1950

1810 world #40
Egypt Qualified-field median

Egypt ends the series at 1810 Elo, the world’s 40th-ranked side — below the qualified-field median.

Source · eloratings.net
Which Elo is this?

This line is the public eloratings.net series (year-end ratings), which terminates exactly at the current rating and world rank shown on the marker. It is a different number from the Elo shown in the header band (a panel-normalised rating used inside the forecast); the two are ~0.99 correlated but on different scales. We keep them distinct rather than blend them.

85% Squad club-form coverage Share of this squad with a matched club season feeding the global form layer.
85% Fitness-readiness coverage Where below 100%, part of the fitness signal is imputed by the de-biasing layer.
n = 3 Out-of-sample tournaments The model is validated on three held-out World Cups; it matches the market, it does not beat it.

Validated on n=3 held-out tournaments; coverage below 1.0 means part of this squad's club-form/fitness is imputed (the global de-biasing layer). For Egypt, 4 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →