Prediction Audit: Wigan vs Port Vale Prediction, Odds & AI Betting Tips

Jul 18, 2026 - 12:00
1 1.29
3 1.31
xG Accuracy: 58%

AI correctly predicted the Port Vale win.

The match finished 1–3, 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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Port Vale Port Vale ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-3 ✖ Incorrect

Model vs Closing Market

Moderate Disagreement

The closing market prices Wigan higher than the statistical model.

Largest probability gap: Wigan -7.1 pp

Outcome Model Closing Market Difference Signal
Wigan 34.7% 41.8% -7.1 pp Market Higher
Draw 29.6% 29.6% +0.0 pp Aligned
Port Vale 35.6% 28.6% +7.0 pp Model Higher

The closing market estimates Wigan's win probability at 41.8%, compared with the model's estimate of 34.7%, a difference of 7.1 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 (Port Vale win 1–3).

Market Assessment

The market and model broadly agree on Wigan. 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) — 4 goals materialised
  • Both Teams To Score (Yes) matched the full-time result

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)
  • Exact score: outside the model's top score bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Port Vale higher (42.7% vs model 35.6%, 7.1 pp), but the model's lean was validated (Port Vale win 1–3).

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Prediction Timeline

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

  1. Jul 18, 2026 · 20:02 UTC Forecast generated
    • Model 1X2 · Wigan 34.7% · Draw 29.7% · Port Vale 35.6%
    • xG · Wigan 1.29 — Port Vale 1.31
  2. Jul 18, 2026 · 11:33 UTC Opening odds snapshot PRE30
    • 1X2 odds · Wigan 2.13 · Draw 3.00 · Port Vale 3.11
    • Implied 1X2 · Wigan 41.8% · Draw 29.6% · Port Vale 28.6%
    • Bookmaker · Pinnacle
  3. Jul 18, 2026 · 12:01 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Wigan 2.13 · Draw 3.00 · Port Vale 3.11
    • Implied 1X2 · Wigan 41.8% · Draw 29.6% · Port Vale 28.6%
    • Bookmaker · Pinnacle
  4. Jul 18, 2026 · 12:00 UTC Kickoff
  5. FT Full-time result Port Vale win · 1–3
  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 75/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 22/100
Monitoring Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 18:28 UTC Snapshot ID: dp-1484422

Closing Odds 2.13
AI Fair Odds —
CLV Pending
Final Result Port Vale win · Wigan 1–3 Port Vale
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

Pre-match snapshot for this fixture.

  • League: Club Friendlies
  • Fixture: Wigan Athletic vs Port Vale
  • Kickoff: 2026-07-18 12:00:00
  • 1X2 (model): Home 0.0% · Draw 50.0% · Away 50.0%
  • xG (showing): Wigan Athletic 1.29 — Port Vale 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

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

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 30, 2026 (UTC)

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