Predictions / Football / South-Korea. FA Cup / Namyangju vs Gimpo Citizen

Prediction Audit: Namyangju vs Gimpo Citizen Prediction, Odds & AI Betting Tips

Namyangju Namyangju
Jul 15, 2026 - 10:00
1 1.29
2 1.31
xG Accuracy: 76%
Gimpo Citizen Gimpo Citizen

AI correctly predicted the Gimpo Citizen win.

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

Tracked markets vs full-time result

Prediction grade B-

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 Yes Yes ✔ Correct
  • 1X2 Gimpo Citizen Gimpo Citizen ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-2 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Gimpo Citizen higher than the statistical model.

Largest probability gap: Gimpo Citizen -23.4 pp

Outcome Model Closing Market Difference Signal
Namyangju 25.4% 11.2% +14.2 pp Model Edge
Draw 28.0% 18.9% +9.1 pp Model Higher
Gimpo Citizen 46.6% 70.0% -23.4 pp Market Higher

The closing market estimates Gimpo Citizen's win probability at 70.0%, compared with the model's estimate of 46.6%, a difference of 23.4 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 (Gimpo Citizen win 1–2).

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised
  • Both Teams To Score (Yes) matched the full-time result
  • Exact score 1–2 fell within the model's highlighted bins

What failed

  • 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 Gimpo Citizen higher (70.0% vs model 46.6%, 23.4 pp), but the model's lean was validated (Gimpo Citizen win 1–2).

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Prediction Timeline

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

  1. Jul 15, 2026 · 19:15 UTC Forecast generated
    • Model 1X2 · Namyangju 25.4% · Draw 28.0% · Gimpo Citizen 46.5%
    • xG · Namyangju 1.29 — Gimpo Citizen 1.31
  2. Jul 15, 2026 · 09:30 UTC Opening odds snapshot PRE30
    • 1X2 odds · Namyangju 8.00 · Draw 4.75 · Gimpo Citizen 1.28
    • Implied 1X2 · Namyangju 11.2% · Draw 18.9% · Gimpo Citizen 70.0%
    • Bookmaker · Bet365
  3. Jul 15, 2026 · 10:00 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Namyangju 8.00 · Draw 4.75 · Gimpo Citizen 1.28
    • Implied 1X2 · Namyangju 11.2% · Draw 18.9% · Gimpo Citizen 70.0%
    • Bookmaker · Bet365
  4. Jul 15, 2026 · 10:00 UTC Kickoff
  5. FT Full-time result Gimpo Citizen win · 1–2
  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: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 51/100 · Moderate
  • Validation: Warning
  • Large market gap (23 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 16:46 UTC Snapshot ID: dp-1476086

Closing Odds 1.28
AI Fair Odds —
CLV Pending
Final Result Gimpo Citizen win · Namyangju 1–2 Gimpo Citizen
Prediction ✔ Correct
Decision Grade B-

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: FA Cup
  • Fixture: Namyangju vs Gimpo Citizen
  • Kickoff: 2026-07-15 10:00:00
  • 1X2 (model): Home 33.0% · Draw 33.0% · Away 33.0%
  • xG (showing): Namyangju 1.29 — Gimpo Citizen 1.31 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: Wait

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 30, 2026 (UTC)

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