Predictions / Football / South-Korea. WK-League / Seoul vs Gyeongju

Prediction Audit: Seoul vs Gyeongju Prediction, Odds & AI Betting Tips

Seoul Seoul
Aug 14, 2026 - 10:00
0 1.37
0 1.23
xG Accuracy: 49%
Gyeongju Gyeongju

The model missed the final outcome (Draw 0–0).

The model had projected Seoul at 38.5%, 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 Under 2.5 (0 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Seoul Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 0-0 ✖ Incorrect

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Draw +3.0 pp

Outcome Model Closing Market Difference Signal
Seoul 38.5% 41.1% -2.6 pp Aligned
Draw 29.6% 26.6% +3.0 pp Aligned
Gyeongju 31.9% 32.3% -0.4 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 result was Draw 0–0.

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

  • Under 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 1X2: model leaned Seoul; match finished Draw

Market lesson

The full-time result was Draw 0–0, which did not match the model's pre-match lean on 1X2.

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Prediction Timeline

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

  1. Aug 14, 2026 · 09:59 UTC Forecast generated
    • Model 1X2 · Seoul 38.5% · Draw 29.6% · Gyeongju 31.9%
    • xG · Seoul 1.37 — Gyeongju 1.23
  2. Aug 14, 2026 · 09:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Seoul 2.20 · Draw 3.40 · Gyeongju 2.80
    • Implied 1X2 · Seoul 41.1% · Draw 26.6% · Gyeongju 32.3%
    • Bookmaker · Bet365
  3. Aug 14, 2026 · 09:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Seoul 2.20 · Draw 3.40 · Gyeongju 2.80
    • Implied 1X2 · Seoul 41.1% · Draw 26.6% · Gyeongju 32.3%
    • Bookmaker · Bet365
  4. Aug 14, 2026 · 10:00 UTC Kickoff
  5. FT Full-time result Draw · 0–0
  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 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: Aug 08, 2026 · 01:01 UTC Snapshot ID: dp-3225505

Closing Odds 3.4
AI Fair Odds —
CLV Pending
Final Result Draw · Seoul 0–0 Gyeongju
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: WK-League
  • Fixture: Seoul vs Gyeongju
  • Kickoff: 2026-08-14 10:00:00
  • 1X2 (model): Home 38.5% · Draw 29.6% · Away 31.9%
  • xG (showing): Seoul 1.37 — Gyeongju 1.23 (total xG ≈ 2.6)
  • Value headline: None — no positive EV on tracked lines at current best prices (same as the decision block: no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

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

September 30, 2026 (UTC)

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WK-League WK-League — Standings
# TEAM MP W D L PTS
1 Suwon FMC 24 18 2 4 56
2 Hwacheon KSPO 24 13 8 3 47
3 Gyeongju 24 9 7 8 34
4 Boeun Sangmu 24 10 3 11 33
5 Gumi Sportstoto 24 9 4 11 31
6 Seoul 24 9 3 12 30
7 Incheon Red Angels 24 6 5 13 23
8 Changnyeong 24 3 6 15 15
# TEAM MP GS GC +/- PTS
1 Suwon FMC 24 58 19 +39 56
2 Gyeongju 24 35 29 +6 34
3 Hwacheon KSPO 24 32 11 +21 47
4 Boeun Sangmu 24 25 31 -6 33
5 Gumi Sportstoto 24 24 31 -7 31
6 Seoul 24 22 33 -11 30
7 Changnyeong 24 21 49 -28 15
8 Incheon Red Angels 24 20 34 -14 23
WK-League South-Korea. WK-League Predictions