Predictions / Football / Germany. 2. Bundesliga / Karlsruher SC vs VfL Bochum

Prediction Audit: Karlsruher SC vs VfL Bochum Prediction, Odds & AI Betting Tips

Karlsruher SC Karlsruher SC
May 17, 2026 - 13:30
1 1.60
2 1.33
xG Accuracy: 70%
VfL Bochum VfL Bochum

The model missed the final outcome (VfL Bochum win 1–2).

The model had projected Karlsruher SC at 42.3%, 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 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Karlsruher SC VfL Bochum ✖ Incorrect
  • Correct Score Insights 1-1, 2-1, 1-0, 1-2, 0-1 1-2 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The closing market prices VfL Bochum higher than the statistical model.

Largest probability gap: VfL Bochum -6.5 pp

Outcome Model Closing Market Difference Signal
Karlsruher SC 42.3% 39.3% +3.0 pp Aligned
Draw 27.3% 23.9% +3.5 pp Aligned
VfL Bochum 30.4% 36.9% -6.5 pp Market Higher

The closing market estimates VfL Bochum's win probability at 36.9%, compared with the model's estimate of 30.4%, a difference of 6.5 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 VfL Bochum win 1–2.

Market Assessment

The market and model broadly agree on VfL Bochum. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.93) — 3 goals materialised
  • Exact score 1–2 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)

Market lesson

The closing market differed from the model on Karlsruher SC by 6.5 percentage points (48.8% vs model 42.3%) — in this case the market view proved closer.

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Prediction Timeline

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

  1. May 17, 2026 · 13:29 UTC Forecast generated
    • Model 1X2 · Karlsruher SC 42.4% · Draw 27.3% · VfL Bochum 30.3%
    • xG · Karlsruher SC 1.60 — VfL Bochum 1.33
  2. May 17, 2026 · 13:00 UTC Opening odds snapshot PRE30
    • 1X2 odds · Karlsruher SC 2.55 · Draw 3.89 · VfL Bochum 2.55
    • Implied 1X2 · Karlsruher SC 37.7% · Draw 24.7% · VfL Bochum 37.7%
    • Bookmaker · Pinnacle
  3. May 17, 2026 · 13:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Karlsruher SC 2.44 · Draw 4.02 · VfL Bochum 2.60
    • Implied 1X2 · Karlsruher SC 39.3% · Draw 23.9% · VfL Bochum 36.9%
    • Bookmaker · Pinnacle
  4. May 17, 2026 · 13:30 UTC Kickoff
  5. FT Full-time result VfL Bochum win · 1–2
  6. FT Prediction missed 1X2 lean did not match 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 Missed
Pre-match metrics (historical context)
Prediction Reliability 76/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 67/100
Betting Confidence 79/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 24, 2026 · 08:42 UTC Snapshot ID: dp-1574879

Closing Odds 2.6
AI Fair Odds —
CLV Pending
Final Result VfL Bochum win · Karlsruher SC 1–2 VfL Bochum
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

Pre-match snapshot for this fixture.

  • League: 2. Bundesliga
  • Fixture: Karlsruher SC vs VfL Bochum
  • Kickoff: 2026-05-17 13:30:00
  • 1X2 (model): Home 42.4% · Draw 27.3% · Away 30.3%
  • xG (showing): Karlsruher SC 1.6 — VfL Bochum 1.33 (total xG ≈ 2.93)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 43.9% · Implied: 32.1% · Probability edge: +11.8 pts · Est. EV: +36.1%
  • BTTS (model): Yes 60.2% · No 39.8%
  • Correct score (top bin): 1-1 (11.4%)

Totals and BTTS are evaluated against current market prices where available.

Early match state can move realised goals away from pre-kick projections.

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

October 02, 2026 (UTC)

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2. Bundesliga 2. Bundesliga — Standings
# TEAM MP W D L PTS
1 FC Schalke 04 34 21 7 6 70
2 SV Elversberg 34 18 8 8 62
3 SC Paderborn 07 34 18 8 8 62
4 Hannover 96 34 16 12 6 60
5 SV Darmstadt 98 34 13 13 8 52
6 1. FC Kaiserslautern 34 16 4 14 52
7 Hertha BSC 34 14 9 11 51
8 1. FC Nürnberg 34 12 10 12 46
9 VfL Bochum 34 11 11 12 44
10 Karlsruher SC 34 12 8 14 44
11 Dynamo Dresden 34 11 8 15 41
12 Holstein Kiel 34 11 8 15 41
13 Arminia Bielefeld 34 10 9 15 39
14 1. FC Magdeburg 34 12 3 19 39
15 Eintracht Braunschweig 34 10 7 17 37
16 SpVgg Greuther Fürth 34 10 7 17 37
17 Fortuna Düsseldorf 34 11 4 19 37
18 Preußen Münster 34 6 12 16 30
# TEAM MP GS GC +/- PTS
1 SV Elversberg 34 64 39 +25 62
2 Hannover 96 34 60 44 +16 60
3 SC Paderborn 07 34 59 45 +14 62
4 SV Darmstadt 98 34 57 45 +12 52
5 Dynamo Dresden 34 54 53 +1 41
6 Arminia Bielefeld 34 53 51 +2 39
7 Karlsruher SC 34 53 64 -11 44
8 1. FC Kaiserslautern 34 52 47 +5 52
9 1. FC Magdeburg 34 52 58 -6 39
10 FC Schalke 04 34 50 31 +19 70
11 VfL Bochum 34 49 47 +2 44
12 SpVgg Greuther Fürth 34 49 68 -19 37
13 Hertha BSC 34 47 44 +3 51
14 1. FC Nürnberg 34 47 45 +2 46
15 Holstein Kiel 34 44 48 -4 41
16 Preußen Münster 34 38 61 -23 30
17 Eintracht Braunschweig 34 36 54 -18 37
18 Fortuna Düsseldorf 34 33 53 -20 37
# TEAM MP xG xGC +/- PTS
1 FC Schalke 04 34 51.0 30.4 +20.6 70
2 SC Paderborn 07 34 58.1 38.1 +20.0 62
3 Hannover 96 34 55.4 38.5 +16.9 60
4 SV Elversberg 34 54.6 37.8 +16.8 62
5 1. FC Magdeburg 34 52.6 45.9 +6.7 39
6 Arminia Bielefeld 34 50.3 46.2 +4.1 39
7 VfL Bochum 34 51.9 48.6 +3.3 44
8 1. FC Nürnberg 34 46.2 44.2 +2.0 46
9 SV Darmstadt 98 34 52.1 51.8 +0.3 52
10 1. FC Kaiserslautern 34 46.7 47.1 -0.4 52
11 Dynamo Dresden 34 43.2 43.9 -0.7 41
12 Hertha BSC 34 44.7 51.4 -6.7 51
13 Fortuna Düsseldorf 34 40.3 49.4 -9.1 37
14 Eintracht Braunschweig 34 36.7 48.1 -11.4 37
15 SpVgg Greuther Fürth 34 39.4 51.4 -12.0 37
16 Holstein Kiel 34 41.0 53.1 -12.1 41
17 Preußen Münster 34 36.7 55.9 -19.2 30
18 Karlsruher SC 34 42.5 61.9 -19.4 44