Austria Wien W vs Brann W Statistics & Analysis

Sep 01, 2026 - 16:00
4 1.34
0 1.26
xG Accuracy: 34%
Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

Tracked markets vs full-time result

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

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Austria Wien W Austria Wien W ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 4-0 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 26, 2026 · 02:12 UTC Snapshot ID: dp-5503003

Closing Odds 1.85
AI Fair Odds —
CLV +0.0%
Final Result Austria Wien W win · Austria Wien W 4–0 Brann W
Prediction ✔ Correct
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Market intelligence

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

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Austria Wien W (1X2), Draw (1X2), Under 2.5 goals meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Under 2.5 goals by about 11.6 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Austria Wien W (1X2) 37.0 26.7 +10.3
Draw (1X2) 29.6 24.1 +5.5
Brann W (1X2) 33.4 49.2 -15.9
Over 2.5 goals 48.2 59.8 -11.6
Under 2.5 goals 51.8 40.2 +11.6
What this means

In plain terms: the model lands near 51.8% on Under 2.5 goals, while the closing snapshot implied about 40.2%. The difference — about 11.6 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).

Closing-window line move

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.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
Austria Wien W (1X2) 3.41 3.41 0.0
Draw (1X2) 3.78 3.78 0.0
Brann W (1X2) 1.85 1.85 0.0
Over 2.5 goals 1.55 1.55 0.0
Under 2.5 goals 2.31 2.31 0.0

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: UEFA Champions League Women
  • Fixture: Austria Wien W vs Brann W
  • Kickoff: 2026-09-01 16:00:00
  • 1X2 (model): Home 37.0% · Draw 29.6% · Away 33.4%
  • xG (showing): Austria Wien W 1.34 — Brann W 1.26 (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: 40.1% · Probability edge: +11.8 pts · Est. EV: +24.3%
  • 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 Recommendation

Historical Decision: No Primary Bet

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

September 29, 2026 (UTC)

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Back to Statistics
UEFA Champions League Women UEFA Champions League Women — Standings
# TEAM MP W D L PTS
1 Lyon W 1 1 0 0 3
2 Barcelona W 1 1 0 0 3
3 SL Benfica 1 1 0 0 3
4 Arsenal W 1 1 0 0 3
5 Chelsea W 1 1 0 0 3
6 Inter Milano W 1 1 0 0 3
7 Manchester City W 1 0 1 0 1
8 Bayern Munich W 1 0 1 0 1
9 Paris Saint Germain W 1 0 1 0 1
10 Real Madrid W 1 0 1 0 1
11 OH Leuven W 1 0 1 0 1
12 Roma W 1 0 1 0 1
13 Juventus W 1 0 0 1 0
14 Austria Wien W 1 0 0 1 0
15 Häcken 1 0 0 1 0
16 Køge 1 0 0 1 0
17 Paris FC W 1 0 0 1 0
18 Servette Chênois W 1 0 0 1 0
# TEAM MP GS GC +/- PTS
1 Lyon W 1 8 0 +8 3
2 Barcelona W 1 5 2 +3 3
3 SL Benfica 1 2 1 +1 3
4 Manchester City W 1 2 2 0 1
5 Bayern Munich W 1 2 2 0 1
6 Paris FC W 1 2 5 -3 0
7 Arsenal W 1 1 0 +1 3
8 Chelsea W 1 1 0 +1 3
9 Inter Milano W 1 1 0 +1 3
10 Paris Saint Germain W 1 1 1 0 1
11 Real Madrid W 1 1 1 0 1
12 Juventus W 1 1 2 -1 0
13 OH Leuven W 1 0 0 0 1
14 Roma W 1 0 0 0 1
15 Austria Wien W 1 0 1 -1 0
16 Häcken 1 0 1 -1 0
17 Køge 1 0 1 -1 0
18 Servette Chênois W 1 0 8 -8 0