England vs Ghana
Group L · Tuesday, June 23, 2026, 20:00 UTC · Boston (Foxborough)
The model's read
The model makes England strong favourites at 61%, leaving 13% for Ghana and 25% for the draw. Goals project around 2.3–1.1 in an open game (both teams to score 58%, over 2.5 65%). The biggest single factor is Overall strength, favouring England. Confidence sits at 58/100 with moderate upset risk; the underdog has paths to a result.
Auto-updated every hour as ratings, odds and news change.
Match outcome
oracle-v1.0.0
England win
61.4%
Draw
25.4%
Ghana win
13.2%
Expected goals
2.26 – 1.10
Scoreline cluster
2-1 / 1-0 / 2-0
top exact 2-1 · 9.8%
Confidence
58/100
Result lean
England clear edge
Score band
Favorite multi-goal edge
Goal environment
Open
If it opens up — high-scoring alternative
3-1 at 7.3% — most likely scoreline with 3+ goals total.
no exact score is dominant; BTTS 58% and Over 2.5 65% both elevated; top three scorelines within 2 pp
Risk & uncertainty
Upset risk
28/100
Data quality
86/100
Uncertainty band
53 – 77%
Most likely scorelines
Top 12 from a Dixon-Coles adjusted Poisson matrix.
Top 12 most likely scorelines. Heat is relative to the most likely outcome. England vs Ghana.
Team comparison
Rating profile across the key dimensions.
Ensemble breakdown
Final probabilities blend the technical model with every available source layer. Persisted 2026-07-11 02:02:34 UTC.
Final (blended) home
61.4%
Final draw
25.4%
Final away
13.2%
Source weights applied
- technical38.5%
- learned16.1%
- market19.3%
- crowd7.5%
- external0.0%
- intel8.6%
- fundamental7.0%
- sentimentMomentum3.0%
Source presence
- technical1 signal
- learned1 signal
- market38 signals
- crowd1 signal
- externalnot used
- intel143 signals
- fundamental84 signals
Why this prediction
Source conflict detected — model confidence has been reduced.
Technical
80/100
Fundamentals
82/100
Betting
86/100
Prediction market
94/100
Sentiment
0/100
Top positive drivers
- · learned signal favours home (50.6 pp above uniform)
- · market signal favours home (38.1 pp above uniform)
- · technical signal favours home (31.6 pp above uniform)
Top risk drivers
- · Source conflict: learned vs crowd disagree (conflict score 100)
- · crowd signal is against home (-32.8 pp below uniform)
Missing: external prediction sites
Learned model
The learned model contributes to the public ensemble blend, alongside ratings, market signals and news intelligence. Performance is validated against an Elo baseline.
England win
83.9%
Draw
15.0%
Ghana win
1.2%
Total goals (λ)
2.50
Model confidence
76/100
Logistic regression model — version wdl-v1, trained on 19k historical internationals.
Article intelligence
Recent news, injury alerts and sentiment extracted by the NLP layer.
England
142 articles / 14d
Injury alerts
· World Cup (out — red card)
· Quansah (out — red card)
· Jarell Quansah (out — red card)
Ghana
1 article / 14d
Goals markets
BTTS yes
58.2%
Over 1.5
83.3%
Over 2.5
65.2%
Over 3.5
43.2%
Under 2.5
34.8%
Market intelligence
Model probability
61.4%
Market probability
71.5%
Gap: -6.5 percentage points.
Market confidence: 97/100 across 38 bookmakers.
Odds shown for analysis only — CupCastLab does not place bets, list bookmakers, or recommend wagers.
Explanation
Why the model sees the match this way.
Model prediction: England 65% to win, 19% for Ghana, 16% draw. Expected goals: England 2.26 vs Ghana 1.10. Scoreline cluster: 2-1 / 1-0 / 2-0. Top exact 2-1 only 9.8%. Goal environment open (BTTS 58%, Over 2.5 65%). Favorite multi-goal edge. Primary factor: overall strength difference is the dominant driver. Confidence: 58/100. Moderate confidence; outcome is meaningfully uncertain.
Factor contributions
Risk factors
- England carry injury concerns into the match.
Uncertainty factors
- No major uncertainty flags.
Tactical read
No standout tactical mismatch — the stylistic edge is modest.
Upset risk
Moderate upset risk — the underdog has identifiable paths to a result.
Market divergence
Model is slightly more cautious than the market.
These predictions are probabilistic and not guarantees. Not betting advice.