WC2026 Model Tracker
Bivariate-Poisson predictions vs actual results ยท a live, honest experiment
๐ด๓ ง๓ ข๓ ฅ๓ ฎ๓ ง๓ ฟ England vs Ghana ๐ฌ๐ญ WINNER MISS
FIFA World Cup 2026, Group L, Matchday 2 ยท Neutral site (USA)
Kickoff Jun 23, 2026 ยท 20:00 UTC
Kickoff Jun 23, 2026 ยท 20:00 UTC
Final ยท England 0โ0 Ghana
Goals: โ
Actual stats: xG 1.36 โ 0.17 ยท 11 corners ยท 2 cards (0 red)
Prediction vs result 4/8 markets hit
| Market | Model called | Actual | Outcome |
|---|---|---|---|
| 1X2 | England | Draw (0-0) | MISS |
| Score | 1-0 | 0-0 | MISS |
| O/U 2.5 | Under 2.5 (53.4%) | 0 goals | HIT |
| BTTS | No (54.1%) | No | HIT |
| Corners | Under 8.5 (51.0%) | 11 corners | MISS |
| Cards | Under 3.5 (59.7%) | 2 cards | HIT |
| Red card | No (87.8%) | No | HIT |
| AH | England -1.00 | Loss | MISS |
Model vs market
| Market | Model | Book odds | Book p* | EV |
|---|---|---|---|---|
| England win | 61.9% | 1.18 | 80.9% | -27.0% |
| Draw | 23.8% | 7.50 | 12.7% | +78.6% |
| Ghana win | 14.3% | 15.00 | 6.4% | +115.0% |
| Over 2.5 goals | 46.6% | 1.57 | 60.2% | -26.7% |
| Under 2.5 goals | 53.4% | 2.38 | 39.8% | +26.8% |
| Both teams score: yes | 45.9% | 2.38 | 39.2% | +9.0% |
| Both teams score: no | 54.1% | 1.53 | 60.8% | -17.1% |
| Over 8.5 corners (exp 8.59) | 49.0% | 1.73 | 53.7% | -15.4% |
| Under 8.5 corners | 51.0% | 2.00 | 46.3% | +2.1% |
| Over 3.5 cards (exp 3.22) | 40.3% | โ | โ | โ |
| Under 3.5 cards | 59.7% | โ | โ | โ |
| Any red card | 12.2% | โ | โ | โ |
Model-only estimates (no straight market equivalent): expected goals England 1.79 โ 0.78 Ghana ยท fair Asian handicap England -1.00
In the table above, Model = our probability and Book odds / Book p* = the bookmaker's (p* has the margin removed). EV = value per unit staked at the model's probability (positive = model sees value). โโโ = market not in the captured feed.
Model reasoning (chain of thought)
PREDICTION RATIONALE โ England vs Ghana (FIFA World Cup 2026, Group L, Matchday 2)
Venue: Neutral site (USA)
1. DATA. Last-10 internationals (Sofascore interception scraper).
England: record WWWWWDLWWW, 2.60 GF / 0.40 GA,
xG 2.31 / xGA 0.67.
Ghana: record WWWLLLLLDW, 1.10 GF / 1.30 GA,
xG 1.05 / xGA 1.62.
Opponent-strength tiers (configs.MASTER_TIERS) applied per match.
2. RATINGS. England atk 1.55 def 0.60; Ghana atk 0.91 def 0.91.
NEUTRAL VENUE: home boost / away penalty set to 1.0/1.0 (both teams
travel to a host-nation site; no host advantage applies โ a key difference
from the Korea/Canada/USA host-nation games). lambda England 1.79, Ghana 0.78
after 90% model weight + shrink to 1.3 baseline.
Injuries: {'England': ['No major absences reported'], 'Ghana': ['No major absences reported']}.
Context: Group L. England heavy favourites after a 4-2 MD1 win over Croatia; Ghana a capable CAF side fresh off beating Panama. Expect the model to under-rate England (cold-on-elites). Neutral venue.
3. MODEL. Bivariate Poisson (lambda3 0.12). 1X2 England 61.9% /
draw 23.8% / Ghana 14.3%. Winner England; score 1-0; fair AH England -1.00.
Over 2.5 46.6%; BTTS 45.9%.
4. EVENTS. Referee TBD: 4.2 Y + 0.13 R/match
blended (weight 0.26) with WC base 2.8392 -> expected
cards 3.22, P(over 3.5) 40.3%; P(any red)
12.2%. Corners expected 8.6 (scale
0.9325) -> P(over 8.5) 49.0%.
5. LIMITATIONS. 10-match samples; hand-set tiers/priors; Poisson corners; lineups
probable not confirmed; card base rate calibrated on only 4 WC matches.