Predictions / Football / World. ASEAN Championship / Thailand vs Myanmar

Prediction Audit: Thailand vs Myanmar Prediction, Odds & AI Betting Tips

Thailand Thailand
Aug 08, 2026 - 13:00
2 1.45
0 1.15
xG Accuracy: 63%
Myanmar Myanmar

AI correctly predicted the Thailand win.

The match finished 2–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade B-

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Thailand Thailand ✔ Correct
  • Correct Score Insights 1-1, 1-0, 2-1, 0-1, 2-0 2-0 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Thailand higher than the statistical model.

Largest probability gap: Thailand -25.5 pp

Outcome Model Closing Market Difference Signal
Thailand 42.4% 67.8% -25.5 pp Market Higher
Draw 29.3% 17.8% +11.5 pp Model Edge
Myanmar 28.4% 14.4% +14.0 pp Model Edge

The closing market estimates Thailand's win probability at 67.8%, compared with the model's estimate of 42.4%, a difference of 25.5 percentage points. This highlights a disagreement between the model and market consensus, without indicating which view is ultimately correct.

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: PRE5.

After full time, the model's directional lean matched the result (Thailand win 2–0).

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile
  • Exact score 2–0 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Thailand higher (67.9% vs model 42.4%, 25.5 pp), but the model's lean was validated (Thailand win 2–0).

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Aug 08, 2026 · 12:58 UTC Forecast generated
    • Model 1X2 · Thailand 42.4% · Draw 29.2% · Myanmar 28.4%
    • xG · Thailand 1.45 — Myanmar 1.15
  2. Aug 08, 2026 · 12:33 UTC Opening odds snapshot PRE30
    • 1X2 odds · Thailand 1.36 · Draw 5.19 · Myanmar 6.42
    • Implied 1X2 · Thailand 67.8% · Draw 17.8% · Myanmar 14.4%
    • Bookmaker · Pinnacle
  3. Aug 08, 2026 · 12:58 UTC Closing snapshot recorded PRE5
    • 1X2 odds · Thailand 1.36 · Draw 5.19 · Myanmar 6.42
    • Implied 1X2 · Thailand 67.8% · Draw 17.8% · Myanmar 14.4%
    • Bookmaker · Pinnacle
  4. Aug 08, 2026 · 13:00 UTC Kickoff
  5. FT Full-time result Thailand win · 2–0
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 50/100 · Moderate
  • Validation: Warning
  • Large market gap (25 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 32/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 02, 2026 · 01:37 UTC Snapshot ID: dp-2815915

Closing Odds 1.36
AI Fair Odds —
CLV Pending
Final Result Thailand win · Thailand 2–0 Myanmar
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Review FAQ

How accurate was the prediction?
This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
What does xG Accuracy measure?
xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
Why wasn't the exact score predicted?
Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
Does this improve the AI record?
Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.

Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: ASEAN Championship
  • Fixture: Thailand vs Myanmar
  • Kickoff: 2026-08-08 13:00:00
  • 1X2 (model): Home 42.4% · Draw 29.2% · Away 28.4%
  • xG (showing): Thailand 1.45 — Myanmar 1.15 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 53.9% · No 46.1%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 53.9% · No 46.1%
  • Correct score (top bin): 1-1 (12.4%)

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: Wait

Outcome: Validated — Pre-match lean validated against the full-time result.

Risk Factors Considered Before Kickoff

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Last Updated

October 02, 2026 (UTC)

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