Statistics / Football / Switzerland. Schweizer Cup / FC Aesch vs Langenthal

FC Aesch vs Langenthal Statistics & Analysis

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FC Aesch
Aug 15, 2026 - 15:00
1 1.37
5 1.23
xG Accuracy: 32%
Langenthal Langenthal
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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 (6 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 FC Aesch Langenthal ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-5 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 09, 2026 · 02:40 UTC Snapshot ID: dp-3359525

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Langenthal win · FC Aesch 1–5 Langenthal
Prediction ✖ Missed
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Schweizer Cup
  • Fixture: FC Aesch vs Langenthal
  • Kickoff: 2026-08-15 15:00:00
  • 1X2 (model): Home 38.5% · Draw 29.6% · Away 31.9%
  • xG (showing): FC Aesch 1.37 — Langenthal 1.23 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • 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 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: No 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 27, 2026 (UTC)

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