Statistics / Football / Germany. 3. Liga / SV Meppen vs FC Viktoria Köln

SV Meppen vs FC Viktoria Köln Statistics & Analysis

SV Meppen SV Meppen
Sep 15, 2026 - 17:00
1 1.32
3 1.28
xG Accuracy: 57%
FC Viktoria Köln FC Viktoria Köln
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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 SV Meppen FC Viktoria Köln ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-3 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 09, 2026 · 02:29 UTC Snapshot ID: dp-7702968

Closing Odds 2.16
AI Fair Odds —
CLV +0.0%
Final Result FC Viktoria Köln win · SV Meppen 1–3 FC Viktoria Köln
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 SV Meppen (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 15.9 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
SV Meppen (1X2) 36.1 33.6 +2.5
Draw (1X2) 29.7 22.3 +7.4
FC Viktoria Köln (1X2) 34.2 44.1 -9.8
Over 2.5 goals 48.2 64.1 -15.9
Under 2.5 goals 51.8 35.9 +15.9
What this means

In plain terms: the model lands near 51.8% on Under 2.5 goals, while the closing snapshot implied about 35.9%. The difference — about 15.9 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)
SV Meppen (1X2) 2.83 2.83 0.0
Draw (1X2) 4.27 4.27 0.0
FC Viktoria Köln (1X2) 2.16 2.16 0.0
Over 2.5 goals 1.48 1.48 0.0
Under 2.5 goals 2.64 2.64 0.0

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: 3. Liga
  • Fixture: SV Meppen vs FC Viktoria Köln
  • Kickoff: 2026-09-15 17:00:00
  • 1X2 (model): Home 36.1% · Draw 29.7% · Away 34.2%
  • xG (showing): SV Meppen 1.32 — FC Viktoria Köln 1.28 (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: 37.3% · Probability edge: +14.5 pts · Est. EV: +36.8%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

Totals and BTTS are evaluated against current market prices where available.

1X2 can look balanced even when side markets show clearer structure.

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

October 01, 2026 (UTC)

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Back to Statistics
3. Liga 3. Liga — Standings
# TEAM MP W D L PTS
1 MSV Duisburg 7 6 0 1 18
2 FC Viktoria Köln 7 5 0 2 15
3 Rot-Weiß Essen 7 4 2 1 14
4 FC Saarbrücken 7 4 1 2 13
5 Hoffenheim II 7 4 1 2 13
6 Hansa Rostock 7 3 3 1 12
7 Alemannia Aachen 7 3 2 2 11
8 Preußen Münster 7 3 2 2 11
9 Waldhof Mannheim 7 3 1 3 10
10 Fortuna Düsseldorf 7 3 1 3 10
11 Verl 7 3 1 3 10
12 Fortuna Köln 7 2 3 2 9
13 SG Sonnenhof Grossaspach 7 2 2 3 8
14 FC Ingolstadt 04 7 2 2 3 8
15 Stuttgart II 7 2 1 4 7
16 Würzburger Kickers 7 2 1 4 7
17 SV Meppen 7 2 0 5 6
18 SSV Jahn Regensburg 7 1 2 4 5
19 SV Wehen 7 1 2 4 5
20 Havelse 7 1 1 5 4
# TEAM MP GS GC +/- PTS
1 MSV Duisburg 7 19 7 +12 18
2 FC Viktoria Köln 7 19 9 +10 15
3 FC Saarbrücken 7 19 12 +7 13
4 Hansa Rostock 7 15 15 0 12
5 Hoffenheim II 7 14 8 +6 13
6 Rot-Weiß Essen 7 13 9 +4 14
7 SSV Jahn Regensburg 7 13 17 -4 5
8 Preußen Münster 7 12 13 -1 11
9 Stuttgart II 7 12 15 -3 7
10 Alemannia Aachen 7 11 8 +3 11
11 Waldhof Mannheim 7 11 10 +1 10
12 Würzburger Kickers 7 11 15 -4 7
13 Verl 7 10 13 -3 10
14 Havelse 7 10 15 -5 4
15 Fortuna Köln 7 8 8 0 9
16 SV Meppen 7 8 15 -7 6
17 FC Ingolstadt 04 7 7 11 -4 8
18 Fortuna Düsseldorf 7 6 7 -1 10
19 SG Sonnenhof Grossaspach 7 6 9 -3 8
20 SV Wehen 7 5 13 -8 5