Germany vs Ivory Coast
Group E · Saturday, June 20, 2026, 20:00 UTC · Toronto
The model's read
The model makes Germany strong favourites at 58%, leaving 19% for Ivory Coast and 23% for the draw. Goals project around 2.0–1.2 in an open game (both teams to score 57%, over 2.5 60%). The biggest single factor is Overall strength, favouring Germany. Confidence sits at 55/100 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
Germany win
58.0%
Draw
23.0%
Ivory Coast win
19.0%
Expected goals
1.96 – 1.17
Scoreline cluster
1-0 / 2-1 / 2-0
top exact 1-0 · 10.4%
Confidence
55/100
Result lean
Germany clear edge
Score band
Favorite multi-goal edge
Goal environment
Open
If it opens up — high-scoring alternative
3-1 at 6.4% — most likely scoreline with 3+ goals total.
BTTS 57% and Over 2.5 60% both elevated; top three scorelines within 2 pp
Risk & uncertainty
Upset risk
35/100
Data quality
87/100
Uncertainty band
44 – 71%
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. Germany vs Ivory Coast.
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 01:01:02 UTC.
Final (blended) home
58.0%
Final draw
23.0%
Final away
19.0%
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
- market36 signals
- crowd1 signal
- externalnot used
- intel20 signals
- fundamental18 signals
Why this prediction
Source conflict detected — model confidence has been reduced.
Technical
76/100
Fundamentals
82/100
Betting
78/100
Prediction market
94/100
Sentiment
0/100
Top positive drivers
- · crowd signal favours home (64.9 pp above uniform)
- · market signal favours home (28.3 pp above uniform)
- · technical signal favours home (24.2 pp above uniform)
- · learned signal favours home (19.0 pp above uniform)
Top risk drivers
- · Source conflict: technical vs crowd disagree (conflict score 79)
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.
Germany win
52.3%
Draw
36.4%
Ivory Coast win
11.3%
Total goals (λ)
2.50
Model confidence
30/100
Logistic regression model — version wdl-v1, trained on 19k historical internationals.
Article intelligence
Recent news, injury alerts and sentiment extracted by the NLP layer.
Germany
17 articles / 14d
Ivory Coast
3 articles / 14d
Goals markets
BTTS yes
57.4%
Over 1.5
80.1%
Over 2.5
60.4%
Over 3.5
38.1%
Under 2.5
39.6%
Market intelligence
Model probability
58.0%
Market probability
61.6%
Gap: -4.1 percentage points.
Market confidence: 98/100 across 36 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: Germany 58% to win, 24% for Ivory Coast, 18% draw. Expected goals: Germany 1.96 vs Ivory Coast 1.17. Scoreline cluster: 1-0 / 2-1 / 2-0. Top exact 1-0 only 10.4%. Goal environment open (BTTS 57%, Over 2.5 60%). Favorite multi-goal edge. Primary factor: overall strength difference is the dominant driver. Confidence: 55/100. Moderate confidence; outcome is meaningfully uncertain.
Factor contributions
Risk factors
- No notable risk factors identified.
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 and market are in close agreement.
These predictions are probabilistic and not guarantees. Not betting advice.