Predictions / Football / Germany. 2. Bundesliga / 1. FC Heidenheim vs Holstein Kiel

Prediction Audit: 1. FC Heidenheim vs Holstein Kiel Prediction, Odds & AI Betting Tips

1. FC Heidenheim 1. FC Heidenheim
Sep 13, 2026 - 11:30
1 1.59
0 1.50
xG Accuracy: 56%
Holstein Kiel Holstein Kiel

AI correctly predicted the 1. FC Heidenheim win.

The match finished 1–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade A

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 1. FC Heidenheim 1. FC Heidenheim ✔ Correct
  • Correct Score Insights 1-1, 2-1, 1-2, 1-0, 0-1 1-0 ✔ Correct

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: 1. FC Heidenheim -3.0 pp

Outcome Model Closing Market Difference Signal
1. FC Heidenheim 38.6% 41.6% -3.0 pp Aligned
Draw 26.7% 24.7% +2.0 pp Aligned
Holstein Kiel 34.7% 33.7% +1.0 pp Aligned

The model and closing market are broadly aligned, with probability differences below 5 percentage points.

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 model's directional lean matched the result (1. FC Heidenheim win 1–0).

Market Assessment

The market and model are broadly aligned. Any small pricing gap likely reflects rounding or bookmaker margin, not a structural disagreement.

  • Current pricing remains close to the model baseline.

Post Match Insights

What worked

  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–0 fell within the model's highlighted bins

Market lesson

The model's directional lean matched the full-time result (1. FC Heidenheim win 1–0).

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Prediction Timeline

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

  1. Sep 13, 2026 · 11:30 UTC Forecast generated
    • Model 1X2 · 1. FC Heidenheim 38.6% · Draw 26.7% · Holstein Kiel 34.7%
    • xG · 1. FC Heidenheim 1.59 — Holstein Kiel 1.50
  2. Sep 13, 2026 · 11:03 UTC Opening odds snapshot PRE30
    • 1X2 odds · 1. FC Heidenheim 2.33 · Draw 3.92 · Holstein Kiel 2.87
    • Implied 1X2 · 1. FC Heidenheim 41.6% · Draw 24.7% · Holstein Kiel 33.7%
    • Bookmaker · Pinnacle
  3. Sep 13, 2026 · 11:30 UTC Closing snapshot recorded PRE1
    • 1X2 odds · 1. FC Heidenheim 2.33 · Draw 3.92 · Holstein Kiel 2.87
    • Implied 1X2 · 1. FC Heidenheim 41.6% · Draw 24.7% · Holstein Kiel 33.7%
    • Bookmaker · Pinnacle
  4. Sep 13, 2026 · 11:30 UTC Kickoff
  5. FT Full-time result 1. FC Heidenheim win · 1–0
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

Historical Snapshot

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

Historical verdict: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 78/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 85/100
Betting Confidence 81/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 07, 2026 · 01:10 UTC Snapshot ID: dp-7427403

Closing Odds 2.33
AI Fair Odds —
CLV Pending
Final Result 1. FC Heidenheim win · 1. FC Heidenheim 1–0 Holstein Kiel
Prediction ✔ Correct
Decision Grade A

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: 2. Bundesliga
  • Fixture: 1. FC Heidenheim vs Holstein Kiel
  • Kickoff: 2026-09-13 11:30:00
  • 1X2 (model): Home 38.6% · Draw 26.7% · Away 34.7%
  • xG (showing): 1. FC Heidenheim 1.59 — Holstein Kiel 1.5 (total xG ≈ 3.09)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 40.3% · Implied: 36.5% · Probability edge: +3.8 pts · Est. EV: +6.8%
  • BTTS (model): Yes 63.3% · No 36.7%
  • Correct score (top bin): 1-1 (10.9%)

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

Correct score remains high-variance even when a line is most likely on paper.

Historical Recommendation

Historical Decision: 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

October 01, 2026 (UTC)

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2. Bundesliga 2. Bundesliga — Standings
# TEAM MP W D L PTS
1 Hertha BSC 6 6 0 0 18
2 1. FC Nürnberg 6 5 1 0 16
3 1. FC Heidenheim 6 4 1 1 13
4 VfL Wolfsburg 6 3 2 1 11
5 1. FC Kaiserslautern 6 3 2 1 11
6 1. FC Magdeburg 6 3 1 2 10
7 Energie Cottbus 6 2 2 2 8
8 FC St. Pauli 6 1 4 1 7
9 VfL Bochum 6 2 1 3 7
10 Hannover 96 6 2 1 3 7
11 VfL Osnabrück 6 2 1 3 7
12 SpVgg Greuther Fürth 6 1 3 2 6
13 Arminia Bielefeld 6 1 2 3 5
14 Karlsruher SC 6 1 2 3 5
15 Eintracht Braunschweig 6 1 1 4 4
16 Holstein Kiel 6 0 4 2 4
17 Dynamo Dresden 6 1 1 4 4
18 SV Darmstadt 98 6 1 1 4 4
# TEAM MP GS GC +/- PTS
1 Hertha BSC 6 17 7 +10 18
2 1. FC Nürnberg 6 16 6 +10 16
3 VfL Wolfsburg 6 15 8 +7 11
4 1. FC Heidenheim 6 14 12 +2 13
5 Energie Cottbus 6 14 13 +1 8
6 Eintracht Braunschweig 6 12 13 -1 4
7 1. FC Magdeburg 6 11 9 +2 10
8 Arminia Bielefeld 6 10 12 -2 5
9 SpVgg Greuther Fürth 6 9 11 -2 6
10 VfL Osnabrück 6 9 12 -3 7
11 FC St. Pauli 6 8 8 0 7
12 Dynamo Dresden 6 8 14 -6 4
13 Hannover 96 6 7 9 -2 7
14 Holstein Kiel 6 7 10 -3 4
15 1. FC Kaiserslautern 6 6 4 +2 11
16 Karlsruher SC 6 6 12 -6 5
17 VfL Bochum 6 5 6 -1 7
18 SV Darmstadt 98 6 5 13 -8 4
# TEAM MP xG xGC +/- PTS
1 Arminia Bielefeld 6 5.9 2.9 +3.0 5
2 Hannover 96 6 6.3 4.0 +2.3 7
3 VfL Wolfsburg 6 6.0 3.7 +2.3 11
4 Hertha BSC 6 7.5 5.6 +1.9 18
5 1. FC Heidenheim 6 7.7 6.0 +1.7 13
6 Holstein Kiel 6 5.6 4.1 +1.5 4
7 FC St. Pauli 6 5.7 4.3 +1.4 7
8 VfL Bochum 6 3.8 2.6 +1.2 7
9 Eintracht Braunschweig 6 9.4 8.5 +0.9 4
10 SpVgg Greuther Fürth 6 6.9 7.0 -0.1 6
11 1. FC Kaiserslautern 6 2.6 3.2 -0.6 11
12 1. FC Nürnberg 6 4.2 5.2 -1.0 16
13 Karlsruher SC 6 3.8 5.3 -1.5 5
14 VfL Osnabrück 6 5.7 7.7 -2.0 7
15 SV Darmstadt 98 6 2.0 4.3 -2.3 4
16 Dynamo Dresden 6 3.4 5.8 -2.4 4
17 1. FC Magdeburg 6 4.7 7.7 -3.0 10
18 Energie Cottbus 6 5.0 8.3 -3.3 8