Predictions / World Cup 2026 / Qatar vs Switzerland

Qatar vs Switzerland

Group B
Qatar Qatar
Jun 13, 2026 - 19:00
1 0.64
1 2.06
Switzerland Switzerland

Betting Signal

Model says
Switzerland 69.3%
Market says
Switzerland 80.4%
Difference
11.1 pp
Status
Use caution — signals are mixed

OddsGPT Interpretation

The betting market strongly prefers Switzerland (80.4%).

Switzerland — market direction supports the model lean.

Model vs Market Comparison

Qatar
9.4% vs 6.54%
+2.9 pp
Draw
21.4% vs 13.08%
+8.3 pp
Switzerland
69.3% vs 80.39%
-11.1 pp

Largest Gap

Switzerland -11.1 pp

The market is substantially more bullish on Switzerland than the model.

The fair estimate differs noticeably from current market pricing. This may reflect genuine disagreement or incomplete rating inputs.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.

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AI Forecast
Qatar 9.4%
Draw 21.4%
Switzerland 69.3%

Generated from Elo-adjusted Poisson simulation. Not bookmaker odds.

Show Full Model Data
Poisson goal-line probabilities
Line Over Under
0.5 92.1% 7.9%
1.5 76.3% 23.7%
2.5 50.6% 49.4%
3.5 28.6% 71.4%
4.5 13.7% 86.3%
Match Expectations
Over 2.5 goals
50.6%
Balanced
Under 2.5 goals
49.4%
Both teams to score
42.6%
Balanced
Clean sheet likely
57.4%

Poisson total-goals expectation Σλ = 2.7 (Over 2.5 50.6% · Under 2.5 49.4%).

BTTS Yes 42.6% · No 57.4% — neither side dominates the BTTS split.

Most Likely Scorelines
Score Probability
0-2 14.2%
0-1 12.7%
1-1 10.1%
0-3 9.7%
1-2 9.1%

Top Poisson cell: 0-2 at 14.2% (exact-score variance remains high).

FAQ
How are win probabilities calculated?

Home and away expected goals (λ) are derived from Elo ratings and tournament parameters, then fed into a Dixon–Coles Poisson grid to produce 1X2, goal-line, and scoreline probabilities shown on this page.

Is this page betting advice?

No. OddsGPT displays model probabilities for informational purposes only. We do not recommend wagers or stake sizes on this page.

What does xG / λ mean here?

λ is the model’s pre-match expected goals for each team before variance is simulated. It is an input to the Poisson matrix, not a post-match expected-goals stat.

Why are exact score probabilities low?

Even the most likely scoreline typically sits below 15% because many score combinations share the probability mass — that is normal for Poisson models.

Match Phase: Finished

Decision Lifecycle

Current stage: Awaiting CLV

  1. Prediction Generated
  2. Market Compared
    Entry Pending
  3. Validation Passed
  4. Closing Recorded
    Closing 1.22
  5. CLV Evaluated
    CLV Pending Awaiting CLV calculation
Back to today's predictions
Group B fixtures