Predictions / Football / World. Friendlies Clubs / Valladolid vs CD Coria

Prediction Audit: Valladolid vs CD Coria Prediction, Odds & AI Betting Tips

Valladolid Valladolid
Jul 29, 2026 - 16:00
4 1.34
1 1.26
xG Accuracy: 45%
CD Coria CD Coria

AI correctly predicted the Valladolid win.

The match finished 4–1, 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 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Valladolid Valladolid ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 4-1 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Valladolid higher than the statistical model.

Largest probability gap: Valladolid -29.6 pp

Outcome Model Closing Market Difference Signal
Valladolid 37.1% 66.7% -29.6 pp Market Higher
Draw 29.6% 21.0% +8.7 pp Model Higher
CD Coria 33.3% 12.3% +21.0 pp Model Edge

The closing market estimates Valladolid's win probability at 66.7%, compared with the model's estimate of 37.1%, a difference of 29.6 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 model's directional lean matched the result (Valladolid win 4–1).

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 5 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 (5 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 Valladolid higher (66.7% vs model 37.1%, 29.6 pp), but the model's lean was validated (Valladolid win 4–1).

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Prediction Timeline

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

  1. Jul 29, 2026 · 19:46 UTC Forecast generated
    • Model 1X2 · Valladolid 37.0% · Draw 29.6% · CD Coria 33.4%
    • xG · Valladolid 1.34 — CD Coria 1.26
  2. Jul 29, 2026 · 15:30 UTC Opening odds snapshot PRE30
    • 1X2 odds · Valladolid 1.33 · Draw 4.23 · CD Coria 7.19
    • Implied 1X2 · Valladolid 66.7% · Draw 21.0% · CD Coria 12.3%
    • Bookmaker · Pinnacle
  3. Jul 29, 2026 · 15:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Valladolid 1.33 · Draw 4.23 · CD Coria 7.19
    • Implied 1X2 · Valladolid 66.7% · Draw 21.0% · CD Coria 12.3%
    • Bookmaker · Pinnacle
  4. Jul 29, 2026 · 16:00 UTC Kickoff
  5. FT Full-time result Valladolid win · 4–1
  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: Cautious / Wait

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

Historical Decision Wait
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 48/100 · Moderate
  • Validation: Warning
  • Large market gap (30 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 31/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 14:03 UTC Snapshot ID: dp-1455319

Closing Odds 1.33
AI Fair Odds —
CLV Pending
Final Result Valladolid win · Valladolid 4–1 CD Coria
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: Friendlies Clubs
  • Fixture: Valladolid vs CD Coria
  • Kickoff: 2026-07-29 16:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Valladolid 1.34 — CD Coria 1.26 (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: 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 29, 2026 (UTC)

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