Predictions / Football / World. Friendlies Clubs / Cavese vs Sarnese

Prediction Audit: Cavese vs Sarnese Prediction, Odds & AI Betting Tips

Cavese Cavese
Jul 30, 2026 - 15:30
1 1.37
0 1.23
xG Accuracy: 64%
Sarnese Sarnese

AI correctly predicted the Cavese win.

The match finished 1–0, 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 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Cavese Cavese ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-0 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Cavese higher than the statistical model.

Largest probability gap: Cavese -26.4 pp

Outcome Model Closing Market Difference Signal
Cavese 38.5% 64.8% -26.4 pp Market Higher
Draw 29.6% 21.2% +8.4 pp Model Higher
Sarnese 31.9% 13.9% +18.0 pp Model Edge

The closing market estimates Cavese's win probability at 64.8%, compared with the model's estimate of 38.5%, a difference of 26.4 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 (Cavese win 1–0).

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–0 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Cavese higher (64.9% vs model 38.5%, 26.4 pp), but the model's lean was validated (Cavese win 1–0).

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Prediction Timeline

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

  1. Jul 30, 2026 · 15:29 UTC Forecast generated
    • Model 1X2 · Cavese 38.5% · Draw 29.6% · Sarnese 31.9%
    • xG · Cavese 1.37 — Sarnese 1.23
  2. Jul 30, 2026 · 14:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Cavese 1.37 · Draw 4.19 · Sarnese 6.37
    • Implied 1X2 · Cavese 64.8% · Draw 21.2% · Sarnese 13.9%
    • Bookmaker · Pinnacle
  3. Jul 30, 2026 · 15:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Cavese 1.37 · Draw 4.19 · Sarnese 6.37
    • Implied 1X2 · Cavese 64.8% · Draw 21.2% · Sarnese 13.9%
    • Bookmaker · Pinnacle
  4. Jul 30, 2026 · 15:30 UTC Kickoff
  5. FT Full-time result Cavese win · 1–0
  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 50/100 · Moderate
  • Validation: Warning
  • Large market gap (26 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 32/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 29, 2026 · 09:01 UTC Snapshot ID: dp-2346834

Closing Odds 1.37
AI Fair Odds —
CLV Pending
Final Result Cavese win · Cavese 1–0 Sarnese
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: Cavese vs Sarnese
  • Kickoff: 2026-07-30 15:30:00
  • 1X2 (model): Home 38.5% · Draw 29.6% · Away 31.9%
  • xG (showing): Cavese 1.37 — Sarnese 1.23 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • 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.

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 28, 2026 (UTC)

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