Waldhof Mannheim vs Preußen Münster Statistics & Analysis

Waldhof Mannheim

Sep 20, 2026 - 14:30

2 2.09

0 1.11

xG Accuracy: 72%

Preußen Münster

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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 Under 2.5 (2 goals) ✖ Incorrect
Both Teams To Score BTTS No No ✔ Correct
1X2 Waldhof Mannheim Waldhof Mannheim ✔ Correct
Correct Score Insights 2-1, 1-1, 2-0, 1-0, 3-1 2-0 ✔ Correct

Validation Report

Immutable Snapshot

Prediction Time: Sep 14, 2026 · 02:05 UTC Snapshot ID: dp-8683323

Closing Odds 2.06

AI Fair Odds —

CLV +0.0%

Final Result Waldhof Mannheim win · Waldhof Mannheim 2–0 Preußen Münster

Prediction ✔ Correct

Decision Grade B-

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 Waldhof Mannheim (1X2) by about 12.4 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market	Model %	Closing impl. %	Gap (pp)
Waldhof Mannheim (1X2)	58.6	46.1	+12.4
Draw (1X2)	23.1	24.9	-1.8
Preußen Münster (1X2)	18.3	28.9	-10.6
Over 2.5 goals	62.0	60.3	+1.7
Under 2.5 goals	38.0	39.7	-1.7

What this means

In plain terms: the model lands near 58.6% on Waldhof Mannheim (1X2), while the closing snapshot implied about 46.1%. The difference — about 12.4 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 → 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)
Waldhof Mannheim (1X2)	2.06	2.06
Draw (1X2)	3.81	3.81
Preußen Münster (1X2)	3.29	3.29
Over 2.5 goals	1.58	1.58
Under 2.5 goals	2.4	2.4

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

League: 3. Liga
Fixture: Waldhof Mannheim vs Preußen Münster
Kickoff: 2026-09-20 14:30:00
1X2 (model): Home 58.6% · Draw 23.1% · Away 18.3%
xG (showing): Waldhof Mannheim 2.09 — Preußen Münster 1.11 (total xG ≈ 3.2)
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 Over 2.5 (Under 2.5 38.0% · Over 2.5 62.0%); BTTS Yes (Yes 60.0% · No 40.0%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS No
BTTS (model): Yes 60.0% · No 40.0%
Correct score (top bin): 2-1 (9.9%)

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.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

Historical Recommendation

Historical Decision: Selective Lean - 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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Back to Statistics

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