Prediction Audit: Verl vs MSV Duisburg Prediction, Odds & AI Betting Tips

Verl

Aug 15, 2026 - 14:30

2 1.24

4 1.14

xG Accuracy: 37%

MSV Duisburg

The model missed the final outcome (MSV Duisburg win 2–4).

The model had projected Verl at 36.9%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

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 Verl MSV Duisburg ✖ Incorrect
Correct Score Insights 1-1, 1-0, 0-1, 0-0, 2-1 2-4 ✖ Incorrect

Model vs Closing Market

Outcome	Model	Closing Market	Difference	Signal
Verl	36.9%	31.3%	+5.6 pp	Model Higher
Draw	31.2%	25.9%	+5.3 pp	Model Higher
MSV Duisburg	32.0%	42.9%	-10.9 pp	Market Higher

The closing market estimates MSV Duisburg's win probability at 42.9%, compared with the model's estimate of 32.0%, a difference of 10.9 percentage points. This highlights a disagreement between the model and market consensus, without indicating which view is ultimately correct.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.

After full time, the result was MSV Duisburg win 2–4.

Market Assessment

The market is materially more optimistic about MSV Duisburg than the current fair estimate.

Investors may be incorporating information not fully reflected in the baseline model.
Tournament-specific context can shift market pricing.

Post Match Insights

What worked

Both Teams To Score (Yes) matched the full-time result

What failed

Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (6 goals)
1X2: model leaned Verl; match finished MSV Duisburg

Market lesson

The closing market differed from the model on Verl by 10.9 percentage points (47.8% vs model 36.9%) — in this case the market view proved closer.

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Prediction Timeline

How this prediction moved from forecast to full-time review.

Aug 15, 2026 · 14:30 UTC Forecast generated
- Model 1X2 · Verl 36.9% · Draw 31.1% · MSV Duisburg 31.9%
- xG · Verl 1.24 — MSV Duisburg 1.14
Aug 15, 2026 · 14:22 UTC Opening odds snapshot PRE30
- 1X2 odds · Verl 3.04 · Draw 3.68 · MSV Duisburg 2.22
- Implied 1X2 · Verl 31.3% · Draw 25.9% · MSV Duisburg 42.9%
- Bookmaker · Pinnacle
Aug 15, 2026 · 14:30 UTC Closing snapshot recorded PRE1
- 1X2 odds · Verl 3.04 · Draw 3.68 · MSV Duisburg 2.22
- Implied 1X2 · Verl 31.3% · Draw 25.9% · MSV Duisburg 42.9%
- Bookmaker · Pinnacle
Aug 15, 2026 · 14:30 UTC Kickoff
FT Full-time result MSV Duisburg win · 2–4
FT Prediction missed 1X2 lean did not match full-time result
Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Monitor

Historical Decision Monitor

Outcome Missed

Pre-match metrics (historical context)

Prediction Reliability 58/100 · Moderate

Validation: Warning
Large market gap (11 pp)

Evidence ★★★★★

No strong statistical edge
Market has already priced much of the edge
Validation warning

Pricing proximity (inverse gap) 15/100

Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 09, 2026 · 02:28 UTC Snapshot ID: dp-3356825

Closing Odds 2.22

AI Fair Odds —

CLV Pending

Final Result MSV Duisburg win · Verl 2–4 MSV Duisburg

Prediction ✖ Missed

Decision Grade F

Model Performance

This prediction contributes to:

Primary Bets ROI (180d): -100.0%

Review FAQ

How accurate was the prediction?: This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
What does xG Accuracy measure?: xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
Why wasn't the exact score predicted?: Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
Does this improve the AI record?: Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.

Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

League: 3. Liga
Fixture: Verl vs MSV Duisburg
Kickoff: 2026-08-15 14:30:00
1X2 (model): Home 36.9% · Draw 31.1% · Away 31.9%
xG (showing): Verl 1.24 — MSV Duisburg 1.14 (total xG ≈ 2.38)
Value headline: None (actionable) — best tracked EV is about +0.5%, still below the +2.0% minimum for a headline / default stake (no default bet).
Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 57.5% · Over 2.5 42.5%); BTTS Yes (Yes 50.0% · No 50.0%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
BTTS (model): Yes 50.0% · No 50.0%
Correct score (top bin): 1-1 (13.1%)

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.

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

Historical Recommendation

Historical Decision: Monitor

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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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