WC 2026 · Forecasting Oxford Football Forecasting
🇨🇦

Canada

CONCACAF Group B Host nation
0.3% Champion probability ±0.02 MC-SE
Coach
Jesse Marsch foreign · American
Elo (model)
1,788 world 25th
Squad value
€201M
Power → Reality
26th 24th +0.08 pp · neutral draw

Fig. D1 Fixture-aware · 100k sims

Canada — stage progression

Round of 32: 91.81% (95% MC 91.64%–91.98%; MC-SE ±0.09 pts) Round of 32 reach 91.8% ±0.09 Round of 16: 44.38% (95% MC 44.08%–44.69%; MC-SE ±0.16 pts) Round of 16 reach 44.4% ±0.16 Quarter-final: 14.81% (95% MC 14.59%–15.03%; MC-SE ±0.11 pts) Quarter-final reach 14.8% ±0.11 Semi-final: 4.21% (95% MC 4.09%–4.34%; MC-SE ±0.06 pts) Semi-final reach 4.2% ±0.06 Final: 1.21% (95% MC 1.14%–1.28%; MC-SE ±0.03 pts) Final reach 1.2% ±0.03 Champion: 0.31% (95% MC 0.28%–0.35%; MC-SE ±0.02 pts) Champion reach 0.3% ±0.02

On the central forecast, Canada more likely than not reaches the Round of 32 (92%). Champion probability is 0.3% ± 0.02 pts.

Source · Oxford Football Forecasting model
Group B Confed Advance (top 2) Reach R32
1🇨🇭SwitzerlandUEFA60.6%96.2%
2🇨🇦CanadaCONCACAF44.4%91.8%
3🇧🇦Bosnia and HerzegovinaUEFA19.2%60.1%
4🇶🇦QatarAFC2.8%18.2%

Source · Oxford Football Forecasting model

Bracket position Half 1 · Quadrant 3

Earliest possible meetings

No collision rows recorded for this team.

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

Match 3 · 2026-06-12 · Toronto Stadium home
55.8% win 26.4% draw 17.8% loss
Most likely 1–0 (13.0%) λ 1.64–0.83 Over 2.5 45% · BTTS 46%
Match 27 · 2026-06-18 · BC Place Vancouver home
Canada Qatar
77.4% win 16.2% draw 6.4% loss
Most likely 2–0 (14.9%) λ 2.39–0.57 Over 2.5 57% · BTTS 40%
Match 51 · 2026-06-24 · BC Place Vancouver away
Canada Switzerland
24.1% win 29.9% draw 46% loss
Most likely 1–1 (13.8%) λ 0.90–1.35 Over 2.5 39% · BTTS 45%
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 Canada. 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

Canada vs the field

Elo rating: 1788 vs field median 1780 (1.00× the field) Elo rating 1788 med 1780 Recent NT form: 1.73 ppg vs field median 1.87 ppg (0.93× the field) Recent NT form 1.73 ppg med 1.87 ppg Squad value: €201M vs field median €286M (0.70× the field) Squad value €201M med €286M Squad form (global): 0.293 vs field median 0.211 (1.39× the field) Squad form (global) 0.293 med 0.211 Fitness readiness: 0.669 vs field median 0.707 (0.95× the field) Fitness readiness 0.669 med 0.707 Familiarity / chemistry: 0.017 vs field median 0.015 (1.08× the field) Familiarity / chemistry 0.017 med 0.015 Experience (mean caps): 34 vs field median 25 (1.37× the field) Experience (mean caps) 34 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

Canada on the decoupling axis

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

g = +0.32 ± 0.05: 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 →

25players
24.9mean age
34mean caps
24%in a top-5 league
21distinct clubs
3largest club bloc
# Player Pos Club League Club min Gls Caps NT gls
1Dayne St. ClairGKInter Miami CFno club data200
2Alistair JohnstonDFCelticLeague Cup −0.28z1,7961581
3Alfie JonesDFMiddlesbroughChampionship +2.21z1,976120
4Luc de FougerollesDFDenderJupiler Pro League −0.07z1,7170130
5Joel WatermanDFChicago Fire FCMajor League Soccer −0.71z8101170
6Mathieu ChoinièreMFLos Angeles FCMajor League Soccer −0.71z7281230
7Stephen EustáquioMFLos Angeles FCno club data564
8Ismaël KonéMFSassuoloSerie A +1.70z2,8406404
9Cyle LarinFWSouthamptonChampionship +2.21z1,15399030
10Jonathan DavidFWJuventusSerie A +1.70z2,41597739
11Liam MillarMFHull CityChampionship +2.21z2,2163411
12Tani OluwaseyiFWVillarrealLa Liga +2.13z1,5657242
13Derek CorneliusDFRangersLeague Cup −0.28z1,5421441
14Jacob ShaffelburgMFLos Angeles FCno club data316
15Moïse BombitoDFNiceno club data200
16Maxime CrépeauGKOrlando City SCno club data320
17Tajon BuchananFWVillarrealLa Liga +2.13z2,3457608
18Owen GoodmanGKBarnsleyLeague One +2.21z1,980000
19Alphonso Davies (captain)DFBayern MunichBundesliga +1.84z1,05415815
20Ali AhmedFWNorwich Cityno club data241
21Jonathan OsorioMFToronto FCMajor League Soccer −0.71z1,95849010
22Richie LaryeaDFToronto FCMajor League Soccer −0.71z1,2651751
23Niko SigurDFHajduk SplitHNL +0.34z2,2351192
24Promise DavidFWUnion Saint-GilloiseJupiler Pro League −0.07z3,73328103
25Nathan SalibaMFAnderlechtJupiler Pro League −0.07z2,3583152

Source · Official squad announcements · API-Football (global club coverage). 6 of 25 players have no club season matched in API-Football — shown as “— no club data”, not imputed. Form coverage for this squad: 76%.

Diaspora in the hosts

804,291

19.0 per 1,000 of home population

Host-language familiarity

Shared

primary language English · spoken in a host

Climate adaptation gap

−4.6°C

home-vs-venue heat differential

Venue extremes

25°C

peak heat index · altitude up to 81 m

Travel

3h

max time-zone shift · nearest venue 355 km

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

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

Canada — Elo since 1957

1899 world #25
Canada Qualified-field median

Canada ends the series at 1899 Elo, the world’s 25th-ranked side — above 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.

76% Squad club-form coverage Share of this squad with a matched club season feeding the global form layer.
76% 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 Canada, 6 of 25 players are shown as “— no club data”. Full validation, calibration & conformal coverage →