Inter Milano W vs VfL Wolfsburg W Statistics & Analysis

Inter Milano W

Sep 02, 2026 - 16:30

2(5) 1.24

0(4) 1.36

xG Accuracy: 56%

VfL Wolfsburg W

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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 Yes ✔ Correct
1X2 VfL Wolfsburg W Inter Milano W ✖ Incorrect
Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 3-1 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 27, 2026 · 02:17 UTC Snapshot ID: dp-5624706

Closing Odds 2.07

AI Fair Odds —

CLV +0.0%

Final Result Inter Milano W win · Inter Milano W 3–1 VfL Wolfsburg W

Prediction ✖ Missed

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 Inter Milano 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 13.0 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market	Model %	Closing impl. %	Gap (pp)
Inter Milano W (1X2)	32.4	30.3	+2.0
Draw (1X2)	29.6	25.4	+4.2
VfL Wolfsburg W (1X2)	38.0	44.3	-6.2
Over 2.5 goals	48.2	61.2	-13.0
Under 2.5 goals	51.8	38.8	+13.0

What this means

In plain terms: the model lands near 51.8% on Under 2.5 goals, while the closing snapshot implied about 38.8%. The difference — about 13.0 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)
Inter Milano W (1X2)	3.02	3.02
Draw (1X2)	3.61	3.61
VfL Wolfsburg W (1X2)	2.07	2.07
Over 2.5 goals	1.52	1.52
Under 2.5 goals	2.4	2.4

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: Inter Milano W vs VfL Wolfsburg W
Kickoff: 2026-09-02 16:30:00
1X2 (model): Home 32.4% · Draw 29.6% · Away 38.0%
xG (showing): Inter Milano W 1.24 — VfL Wolfsburg W 1.36 (total xG ≈ 2.6)
Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
Model: 51.8% · Implied: 40.0% · Probability edge: +11.8 pts · Est. EV: +24.3%
BTTS (model): Yes 54.4% · No 45.6%
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: Primary Bet

Outcome: Missed — Pre-match 1X2 lean did not match 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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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