Statistics / Football / Germany. Oberliga - Bayern Süd / 1860 München II vs Deisenhofen

1860 München II vs Deisenhofen Statistics & Analysis

Aug 21, 2026 - 17:00
1 1.55
1 1.05
xG Accuracy: 85%
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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 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 1860 München II Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 2-1, 2-0, 0-1 1-1 ✔ Correct

Validation Report

Immutable Snapshot

Prediction Time: Aug 15, 2026 · 01:39 UTC Snapshot ID: dp-4028917

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Draw · 1860 München II 1–1 Deisenhofen
Prediction ✖ Missed
Decision Grade C

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Oberliga - Bayern Süd
  • Fixture: 1860 München II vs Deisenhofen
  • Kickoff: 2026-08-21 17:00:00
  • 1X2 (model): Home 47.3% · Draw 28.5% · Away 24.1%
  • xG (showing): 1860 München II 1.55 — Deisenhofen 1.05 (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 52.8% · No 47.2%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 52.8% · No 47.2%
  • Correct score (top bin): 1-1 (12.1%)

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: 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 29, 2026 (UTC)

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