Statistics / Football / Italy. Serie A Cup Women / Inter Milano W vs Lazio W

Inter Milano W vs Lazio W Statistics & Analysis

Inter Milano W Inter Milano W
Sep 06, 2026 - 13:00
3 1.32
1 1.28
xG Accuracy: 58%
Lazio W Lazio 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 No Yes ✖ Incorrect
  • 1X2 Inter Milano W Inter Milano W ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-1 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 31, 2026 · 06:58 UTC Snapshot ID: dp-6354655

Closing Odds 1.53
AI Fair Odds —
CLV +0.0%
Final Result Inter Milano W win · Inter Milano W 3–1 Lazio 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 PRE5 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Draw (1X2), Lazio W (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 Lazio W (1X2) by about 16.4 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Inter Milano W (1X2) 36.1 59.8 -23.8
Draw (1X2) 29.7 22.3 +7.4
Lazio W (1X2) 34.2 17.9 +16.4
Over 2.5 goals 48.2 60.9 -12.7
Under 2.5 goals 51.8 39.1 +12.7
What this means

In plain terms: the model lands near 34.2% on Lazio W (1X2), while the closing snapshot implied about 17.9%. The difference — about 16.4 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 → PRE5 · 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 (PRE5) Implied Δ (pp)
Inter Milano W (1X2) 1.53 1.53 0.0
Draw (1X2) 4.11 4.11 0.0
Lazio W (1X2) 5.12 5.12 0.0
Over 2.5 goals 1.53 1.53 0.0
Under 2.5 goals 2.38 2.38 0.0

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Serie A Cup Women
  • Fixture: Inter Milano W vs Lazio W
  • Kickoff: 2026-09-06 13:00:00
  • 1X2 (model): Home 36.1% · Draw 29.7% · Away 34.2%
  • xG (showing): Inter Milano W 1.32 — Lazio W 1.28 (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 No (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

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

Historical Recommendation

Historical Decision: Wait - 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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