Predictions / Football / Netherlands. KNVB Beker / Eemdijk vs Roosendaal

Prediction Audit: Eemdijk vs Roosendaal Prediction, Odds & AI Betting Tips

Sep 22, 2026 - 18:00
2 1.31
1 1.29
xG Accuracy: 76%

AI correctly predicted the Eemdijk win.

The match finished 2–1, validating the model's directional assessment.

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 Eemdijk Eemdijk ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 2-1 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The closing market prices Roosendaal higher than the statistical model.

Largest probability gap: Roosendaal -9.2 pp

Outcome Model Closing Market Difference Signal
Eemdijk 35.6% 34.9% +0.8 pp Aligned
Draw 29.6% 21.3% +8.4 pp Model Higher
Roosendaal 34.7% 43.9% -9.2 pp Market Higher

The closing market estimates Roosendaal's win probability at 43.9%, compared with the model's estimate of 34.7%, a difference of 9.2 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: PRE1.

After full time, the model's directional lean matched the result (Eemdijk win 2–1).

Market Assessment

The market and model broadly agree on Roosendaal. 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 2.60) — 3 goals materialised
  • Exact score 2–1 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

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Eemdijk higher (44.8% vs model 35.6%, 9.2 pp), but the model's lean was validated (Eemdijk win 2–1).

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Prediction Timeline

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

  1. Sep 22, 2026 · 18:01 UTC Forecast generated
    • Model 1X2 · Eemdijk 35.6% · Draw 29.7% · Roosendaal 34.7%
    • xG · Eemdijk 1.31 — Roosendaal 1.29
  2. Sep 22, 2026 · 17:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · Eemdijk 2.58 · Draw 4.23 · Roosendaal 2.05
    • Implied 1X2 · Eemdijk 34.9% · Draw 21.3% · Roosendaal 43.9%
    • Bookmaker · Pinnacle
  3. Sep 22, 2026 · 18:01 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Eemdijk 2.58 · Draw 4.23 · Roosendaal 2.05
    • Implied 1X2 · Eemdijk 34.9% · Draw 21.3% · Roosendaal 43.9%
    • Bookmaker · Pinnacle
  4. Sep 22, 2026 · 18:00 UTC Kickoff
  5. FT Full-time result Eemdijk win · 2–1
  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: Monitor
Historical Decision Monitor
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 74/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 18/100
Monitoring Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 16, 2026 · 02:46 UTC Snapshot ID: dp-8991615

Closing Odds 2.05
AI Fair Odds —
CLV Pending
Final Result Eemdijk win · Eemdijk 2–1 Roosendaal
Prediction ✔ Correct
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: KNVB Beker
  • Fixture: Eemdijk vs Roosendaal
  • Kickoff: 2026-09-22 18:00:00
  • 1X2 (model): Home 35.6% · Draw 29.7% · Away 34.7%
  • xG (showing): Eemdijk 1.31 — Roosendaal 1.29 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 51.8% · Implied: 30.7% · Probability edge: +21.1 pts · Est. EV: +65.8%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.6%)

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.

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

Historical Recommendation

Historical Decision: Monitor

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

September 29, 2026 (UTC)

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