Bangladesh W vs Myanmar W Statistics & Analysis

Tracked markets vs full-time result

Validation Report

Market intelligence

AI match briefing

Model Performance

Market briefing

Model vs. closing implied

Closing-window line move

AI Match Summary

Historical Recommendation

Risk Factors Considered Before Kickoff

Last Updated

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Asian Games Women — Standings

Bangladesh W

Sep 21, 2026 - 07:00

0 1.32

0 1.28

xG Accuracy: 49%

Myanmar W

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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 (0 goals) ✔ Correct
Both Teams To Score BTTS No No ✔ Correct
1X2 Bangladesh W Draw ✖ Incorrect
Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 0-0 ✖ Incorrect

Immutable Snapshot

Prediction Time: Sep 15, 2026 · 02:20 UTC Snapshot ID: dp-8835082

Closing Odds 1.76

AI Fair Odds —

CLV +0.0%

Final Result Draw · Bangladesh W 0–0 Myanmar W

Prediction ✖ Missed

Decision Grade C

This prediction contributes to:

Primary Bets ROI (180d): -100.0%

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

The largest late implied swing on this feed was about 1.36 percentage points on Myanmar W (1X2) between PRE30 and PRE1.

The model still exceeds closing implied on Bangladesh W (1X2) by about 9.5 percentage points — the clearest mispricing signal summarized on this page.

Market	Model %	Closing impl. %	Gap (pp)
Bangladesh W (1X2)	36.1	26.6	+9.5
Draw (1X2)	29.7	22.4	+7.3
Myanmar W (1X2)	34.2	51.0	-16.8
Over 2.5 goals	48.2	55.9	-7.7
Under 2.5 goals	51.8	44.1	+7.7

What this means

In plain terms: the model lands near 36.1% on Bangladesh W (1X2), while the closing snapshot implied about 26.6%. The difference — about 9.5 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Pinnacle

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Market	Early (PRE30)	Closing (PRE1)	Implied Δ (pp)
Bangladesh W (1X2)	3.21	3.38	-1.1
Draw (1X2)	3.93	4.01	-0.2
Myanmar W (1X2)	1.79	1.76	+1.4
Over 2.5 goals	1.65	1.66	+0.2
Under 2.5 goals	2.07	2.1	-0.2

Quick read on how the model reads this matchup.

League: Asian Games Women
Fixture: Bangladesh W vs Myanmar W
Kickoff: 2026-09-21 07:00:00
1X2 (model): Home 36.1% · Draw 29.7% · Away 34.2%
xG (showing): Bangladesh W 1.32 — Myanmar W 1.28 (total xG ≈ 2.6)
Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
Model: 51.8% · Implied: 43.9% · Probability edge: +7.9 pts · Est. EV: +14.0%
BTTS (model): Yes 54.5% · No 45.5%
Correct score (top bin): 1-1 (12.5%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

1X2 can look balanced even when side markets show clearer structure.

Historical Decision: No Primary Bet

Outcome: Missed — Pre-match 1X2 lean did not match the full-time result.

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%).

September 30, 2026 (UTC)

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