Predictions / Football / World. Friendlies Clubs / Empoli vs Virtus Entella

Prediction Audit: Empoli vs Virtus Entella Prediction, Odds & AI Betting Tips

Empoli Empoli
Jul 25, 2026 - 16:00
1 1.37
0 1.23
xG Accuracy: 64%
Virtus Entella Virtus Entella

AI correctly predicted the Empoli 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 Empoli Empoli ✔ 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 Empoli higher than the statistical model.

Largest probability gap: Empoli -10.3 pp

Outcome Model Closing Market Difference Signal
Empoli 38.5% 48.8% -10.3 pp Market Higher
Draw 29.6% 26.3% +3.3 pp Aligned
Virtus Entella 31.9% 24.9% +7.0 pp Model Higher

The closing market estimates Empoli's win probability at 48.8%, compared with the model's estimate of 38.5%, a difference of 10.3 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 (Empoli win 1–0).

Market Assessment

The market is materially more optimistic about Empoli 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

  • 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 Empoli higher (48.8% vs model 38.5%, 10.3 pp), but the model's lean was validated (Empoli win 1–0).

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Prediction Timeline

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

  1. Jul 25, 2026 · 22:30 UTC Forecast generated
    • Model 1X2 · Empoli 38.5% · Draw 29.6% · Virtus Entella 31.9%
    • xG · Empoli 1.37 — Virtus Entella 1.23
  2. Jul 25, 2026 · 15:35 UTC Opening odds snapshot PRE30
    • 1X2 odds · Empoli 1.82 · Draw 3.38 · Virtus Entella 3.56
    • Implied 1X2 · Empoli 48.8% · Draw 26.3% · Virtus Entella 24.9%
    • Bookmaker · Pinnacle
  3. Jul 25, 2026 · 16:04 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Empoli 1.82 · Draw 3.38 · Virtus Entella 3.56
    • Implied 1X2 · Empoli 48.8% · Draw 26.3% · Virtus Entella 24.9%
    • Bookmaker · Pinnacle
  4. Jul 25, 2026 · 16:00 UTC Kickoff
  5. FT Full-time result Empoli 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: Monitor
Historical Decision Monitor
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 58/100 · Moderate
  • Validation: Warning
  • Large market gap (10 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 48/100
Betting Confidence 46/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 14:09 UTC Snapshot ID: dp-1456578

Closing Odds 1.82
AI Fair Odds —
CLV Pending
Final Result Empoli win · Empoli 1–0 Virtus Entella
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: Empoli vs Virtus Entella
  • Kickoff: 2026-07-25 16:00:00
  • 1X2 (model): Home 33.0% · Draw 33.0% · Away 33.0%
  • xG (showing): Empoli 1.37 — Virtus Entella 1.23 (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 28, 2026 (UTC)

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