Predictions / Football / World. Friendlies Clubs / Olot vs Sabadell

Prediction Audit: Olot vs Sabadell Prediction, Odds & AI Betting Tips

Olot Olot
Aug 09, 2026 - 19:00
0 1.26
3 1.34
xG Accuracy: 45%
Sabadell Sabadell

AI correctly predicted the Sabadell win.

The match finished 0–3, 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 Yes No ✖ Incorrect
  • 1X2 Sabadell Sabadell ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-3 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Sabadell higher than the statistical model.

Largest probability gap: Sabadell -18.5 pp

Outcome Model Closing Market Difference Signal
Olot 33.3% 19.0% +14.3 pp Model Edge
Draw 29.6% 25.4% +4.2 pp Aligned
Sabadell 37.1% 55.6% -18.5 pp Market Higher

The closing market estimates Sabadell's win probability at 55.6%, compared with the model's estimate of 37.1%, a difference of 18.5 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 (Sabadell win 0–3).

Market Assessment

The market is materially more optimistic about Sabadell than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 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 Sabadell higher (55.6% vs model 37.1%, 18.5 pp), but the model's lean was validated (Sabadell win 0–3).

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Prediction Timeline

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

  1. Aug 09, 2026 · 19:02 UTC Forecast generated
    • Model 1X2 · Olot 33.4% · Draw 29.6% · Sabadell 37.0%
    • xG · Olot 1.26 — Sabadell 1.34
  2. Aug 09, 2026 · 18:32 UTC Opening odds snapshot PRE30
    • 1X2 odds · Olot 4.67 · Draw 3.50 · Sabadell 1.60
    • Implied 1X2 · Olot 19.0% · Draw 25.4% · Sabadell 55.6%
    • Bookmaker · Pinnacle
  3. Aug 09, 2026 · 19:01 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Olot 4.67 · Draw 3.50 · Sabadell 1.60
    • Implied 1X2 · Olot 19.0% · Draw 25.4% · Sabadell 55.6%
    • Bookmaker · Pinnacle
  4. Aug 09, 2026 · 19:00 UTC Kickoff
  5. FT Full-time result Sabadell win · 0–3
  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 54/100 · Moderate
  • Validation: Warning
  • Large market gap (18 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 7/100
Betting Confidence 43/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 04, 2026 · 01:38 UTC Snapshot ID: dp-2968266

Closing Odds 1.6
AI Fair Odds —
CLV Pending
Final Result Sabadell win · Olot 0–3 Sabadell
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: Friendlies Clubs
  • Fixture: Olot vs Sabadell
  • Kickoff: 2026-08-09 19:00:00
  • 1X2 (model): Home 33.4% · Draw 29.6% · Away 37.0%
  • xG (showing): Olot 1.26 — Sabadell 1.34 (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 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

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 28, 2026 (UTC)

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