Prediction Audit: Jong PSV vs Den Bosch Prediction, Odds & AI Betting Tips

Sep 07, 2026 - 18:00
3 1.71
1 1.81
xG Accuracy: 56%

The model missed the final outcome (Jong PSV win 3–1).

The model had projected Den Bosch at 39.8%, 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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Den Bosch Jong PSV ✖ Incorrect
  • Correct Score Insights 1-1, 1-2, 2-1, 2-2, 0-1 3-1 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Jong PSV higher than the statistical model.

Largest probability gap: Jong PSV -12.6 pp

Outcome Model Closing Market Difference Signal
Jong PSV 35.7% 48.3% -12.6 pp Market Higher
Draw 24.6% 22.5% +2.1 pp Aligned
Den Bosch 39.8% 29.3% +10.5 pp Model Edge

The closing market estimates Jong PSV's win probability at 48.3%, compared with the model's estimate of 35.7%, a difference of 12.6 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 Jong PSV win 3–1.

Market Assessment

The market is materially more optimistic about Jong PSV 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

  • Expected goals projected a high-scoring match (ΣxG 3.52) — 4 goals materialised

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 (4 goals)

Market lesson

The closing market differed from the model on Den Bosch by 12.6 percentage points (52.4% vs model 39.8%) — 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. Sep 07, 2026 · 17:59 UTC Forecast generated
    • Model 1X2 · Jong PSV 35.7% · Draw 24.5% · Den Bosch 39.8%
    • xG · Jong PSV 1.71 — Den Bosch 1.81
  2. Sep 07, 2026 · 17:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Jong PSV 1.97 · Draw 4.23 · Den Bosch 3.25
    • Implied 1X2 · Jong PSV 48.3% · Draw 22.5% · Den Bosch 29.3%
    • Bookmaker · Pinnacle
  3. Sep 07, 2026 · 17:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Jong PSV 1.97 · Draw 4.23 · Den Bosch 3.25
    • Implied 1X2 · Jong PSV 48.3% · Draw 22.5% · Den Bosch 29.3%
    • Bookmaker · Pinnacle
  4. Sep 07, 2026 · 18:00 UTC Kickoff
  5. FT Full-time result Jong PSV win · 3–1
  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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 57/100 · Moderate
  • Validation: Warning
  • Large market gap (13 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 12/100
Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 01, 2026 · 02:31 UTC Snapshot ID: dp-6474020

Closing Odds 1.97
AI Fair Odds —
CLV Pending
Final Result Jong PSV win · Jong PSV 3–1 Den Bosch
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: Eerste Divisie
  • Fixture: Jong PSV vs Den Bosch
  • Kickoff: 2026-09-07 18:00:00
  • 1X2 (model): Home 35.7% · Draw 24.5% · Away 39.8%
  • xG (showing): Jong PSV 1.71 — Den Bosch 1.81 (total xG ≈ 3.52)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 31.7% · Implied: 26.6% · Probability edge: +5.1 pts · Est. EV: +20.5%
  • BTTS (model): Yes 69.7% · No 30.3%
  • Correct score (top bin): 1-1 (9.2%)

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

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

September 28, 2026 (UTC)

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Eerste Divisie Eerste Divisie — Standings
# TEAM MP W D L PTS
1 Heracles 8 7 0 1 21
2 Almere City FC 8 5 1 2 16
3 MVV 8 5 1 2 16
4 VVV Venlo 8 5 0 3 15
5 Roda 8 4 3 1 15
6 Emmen 8 5 0 3 15
7 Waalwijk 8 3 4 1 13
8 Vitesse 8 4 1 3 13
9 NAC Breda 8 4 1 3 13
10 Jong AZ 9 4 1 4 13
11 FC Volendam 8 4 0 4 12
12 Jong PSV 9 3 3 3 12
13 FC Eindhoven 8 3 1 4 10
14 Helmond Sport 8 2 2 4 8
15 Jong Ajax 9 2 2 5 8
16 Den Bosch 7 2 1 4 7
17 Dordrecht 8 2 1 5 7
18 Jong Utrecht 9 2 1 6 7
19 FC OSS 8 2 0 6 6
20 De Graafschap 7 1 1 5 4
# TEAM MP GS GC +/- PTS
1 Heracles 8 26 10 +16 21
2 Jong AZ 9 22 17 +5 13
3 VVV Venlo 8 21 14 +7 15
4 FC Volendam 8 20 16 +4 12
5 Almere City FC 8 18 7 +11 16
6 Waalwijk 8 18 11 +7 13
7 Emmen 8 18 17 +1 15
8 NAC Breda 8 17 17 0 13
9 Jong Utrecht 9 15 21 -6 7
10 Jong PSV 9 14 16 -2 12
11 Vitesse 8 13 11 +2 13
12 Helmond Sport 8 13 14 -1 8
13 FC Eindhoven 8 13 17 -4 10
14 Jong Ajax 9 13 22 -9 8
15 MVV 8 12 15 -3 16
16 Den Bosch 7 12 16 -4 7
17 Dordrecht 8 12 23 -11 7
18 Roda 8 9 5 +4 15
19 FC OSS 8 8 13 -5 6
20 De Graafschap 7 8 20 -12 4
# TEAM MP xG xGC +/- PTS
1 FC Volendam 8 9.6 5.1 +4.5 12
2 Heracles 8 10.1 6.0 +4.1 21
3 Emmen 8 9.2 6.2 +3.0 15
4 NAC Breda 8 9.8 6.9 +2.9 13
5 MVV 8 6.7 3.8 +2.9 16
6 Jong PSV 9 8.5 5.7 +2.8 12
7 Den Bosch 7 9.6 7.0 +2.6 7
8 Vitesse 8 8.0 6.8 +1.2 13
9 Jong AZ 9 6.9 5.7 +1.2 13
10 Almere City FC 8 7.2 6.1 +1.1 16
11 Roda 8 8.1 7.2 +0.9 15
12 Waalwijk 8 4.8 4.6 +0.2 13
13 FC OSS 8 5.3 7.3 -2.0 6
14 De Graafschap 7 5.4 7.6 -2.2 4
15 Jong Ajax 9 8.4 10.8 -2.4 8
16 VVV Venlo 8 5.7 8.9 -3.2 15
17 Helmond Sport 8 2.6 6.2 -3.6 8
18 Jong Utrecht 9 5.4 9.6 -4.2 7
19 FC Eindhoven 8 3.9 8.2 -4.3 10
20 Dordrecht 8 5.0 10.7 -5.7 7