Statistics / Football / Germany. 3. Liga / Waldhof Mannheim vs Rot-Weiß Essen

Waldhof Mannheim vs Rot-Weiß Essen Statistics & Analysis

Waldhof Mannheim Waldhof Mannheim
Sep 16, 2026 - 17:00
1 1.91
2 1.80
xG Accuracy: 74%
Rot-Weiß Essen Rot-Weiß Essen
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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 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Waldhof Mannheim Rot-Weiß Essen ✖ Incorrect
  • Correct Score Insights 1-1, 2-1, 1-2, 2-2, 3-1 1-2 ✔ Correct

Validation Report

Immutable Snapshot

Prediction Time: Sep 10, 2026 · 15:41 UTC Snapshot ID: dp-7925764

Closing Odds 2.86
AI Fair Odds —
CLV +0.0%
Final Result Rot-Weiß Essen win · Waldhof Mannheim 1–2 Rot-Weiß Essen
Prediction ✖ Missed
Decision Grade C

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 Waldhof Mannheim (1X2), Over 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 Over 2.5 goals by about 10.1 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Waldhof Mannheim (1X2) 40.3 33.3 +7.0
Draw (1X2) 23.7 25.7 -2.0
Rot-Weiß Essen (1X2) 36.0 41.0 -5.1
Over 2.5 goals 71.6 61.5 +10.1
Under 2.5 goals 28.4 38.5 -10.1
What this means

In plain terms: the model lands near 71.6% on Over 2.5 goals, while the closing snapshot implied about 61.5%. The difference — about 10.1 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)
Waldhof Mannheim (1X2) 2.86 2.86 0.0
Draw (1X2) 3.7 3.7 0.0
Rot-Weiß Essen (1X2) 2.32 2.32 0.0
Over 2.5 goals 1.55 1.55 0.0
Under 2.5 goals 2.48 2.48 0.0

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: 3. Liga
  • Fixture: Waldhof Mannheim vs Rot-Weiß Essen
  • Kickoff: 2026-09-16 17:00:00
  • 1X2 (model): Home 40.3% · Draw 23.7% · Away 35.9%
  • xG (showing): Waldhof Mannheim 1.91 — Rot-Weiß Essen 1.8 (total xG ≈ 3.71)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Over 2.5 goals
  • Model: 71.6% · Implied: 62.3% · Probability edge: +9.3 pts · Est. EV: +11.0%
  • BTTS (model): Yes 72.2% · No 27.8%
  • Correct score (top bin): 1-1 (8.4%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

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

September 29, 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