Prediction Audit: Preußen Münster vs FC Ingolstadt 04 Prediction, Odds & AI Betting Tips

Preußen Münster

Aug 15, 2026 - 12:00

1 1.17

1 1.69

xG Accuracy: 79%

FC Ingolstadt 04

The model missed the final outcome (Draw 1–1).

The model had projected FC Ingolstadt 04 at 48.1%, 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 Over 2.5 Under 2.5 (2 goals) ✖ Incorrect
Both Teams To Score BTTS Yes Yes ✔ Correct
1X2 FC Ingolstadt 04 Draw ✖ Incorrect
Correct Score Insights 1-1, 0-1, 1-2, 0-2, 1-0 1-1 ✔ Correct

Model vs Closing Market

Outcome	Model	Closing Market	Difference	Signal
Preußen Münster	24.9%	40.2%	-15.2 pp	Market Higher
Draw	27.0%	25.6%	+1.4 pp	Aligned
FC Ingolstadt 04	48.1%	34.2%	+13.8 pp	Model Edge

The closing market estimates Preußen Münster's win probability at 40.2%, compared with the model's estimate of 24.9%, a difference of 15.2 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: PRE5.

After full time, the result was Draw 1–1.

Market Assessment

The market is materially more optimistic about Preußen Münster 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
Exact score 1–1 fell within the model's highlighted bins

What failed

Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)
1X2: model leaned FC Ingolstadt 04; match finished Draw

Market lesson

The closing market differed from the model on FC Ingolstadt 04 by 15.2 percentage points (63.3% vs model 48.1%) — in this case the market view proved closer.

Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

Prediction Timeline

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

Aug 15, 2026 · 11:58 UTC Forecast generated
- Model 1X2 · Preußen Münster 24.9% · Draw 27.0% · FC Ingolstadt 04 48.1%
- xG · Preußen Münster 1.17 — FC Ingolstadt 04 1.69
Aug 15, 2026 · 11:34 UTC Opening odds snapshot PRE30
- 1X2 odds · Preußen Münster 2.36 · Draw 3.71 · FC Ingolstadt 04 2.77
- Implied 1X2 · Preußen Münster 40.2% · Draw 25.6% · FC Ingolstadt 04 34.2%
- Bookmaker · Pinnacle
Aug 15, 2026 · 11:58 UTC Closing snapshot recorded PRE5
- 1X2 odds · Preußen Münster 2.36 · Draw 3.71 · FC Ingolstadt 04 2.77
- Implied 1X2 · Preußen Münster 40.2% · Draw 25.6% · FC Ingolstadt 04 34.2%
- Bookmaker · Pinnacle
Aug 15, 2026 · 12:00 UTC Kickoff
FT Full-time result Draw · 1–1
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 55/100 · Moderate

Validation: Warning
Large market gap (15 pp)

Evidence ★★★★★

No strong statistical edge
Pricing remains divergent
Validation warning

Pricing proximity (inverse gap) 8/100

Monitoring Confidence 19/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 09, 2026 · 01:37 UTC Snapshot ID: dp-3345154

Closing Odds 2.36

AI Fair Odds —

CLV Pending

Final Result Draw · Preußen Münster 1–1 FC Ingolstadt 04

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

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

League: 3. Liga
Fixture: Preußen Münster vs FC Ingolstadt 04
Kickoff: 2026-08-15 12:00:00
1X2 (model): Home 24.9% · Draw 27.0% · Away 48.1%
xG (showing): Preußen Münster 1.17 — FC Ingolstadt 04 1.69 (total xG ≈ 2.86)
Best +EV line (same label as hero card when Primary thresholds are not met): FC Ingolstadt 04
Model: 48.1% · Implied: 34.2% · Probability edge: +13.9 pts · Est. EV: +8.5%
BTTS (model): Yes 57.7% · No 42.3%
Correct score (top bin): 1-1 (11.3%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

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

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

October 01, 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