Prediction Audit: Nissa vs Vibonese Prediction, Odds & AI Betting Tips

Sep 27, 2026 - 13:00
0 1.52
2 1.08
xG Accuracy: 51%

The model missed the final outcome (Vibonese win 0–2).

The model had projected Nissa at 45.8%, but the full-time result went the other way.

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 Over 2.5 Under 2.5 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Nissa Vibonese ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 2-1, 2-0, 0-1 0-2 ✖ Incorrect

Model vs Closing Market

Moderate Disagreement

The model rates Nissa considerably stronger than the closing betting market.

Largest probability gap: Nissa +7.2 pp

Outcome Model Closing Market Difference Signal
Nissa 45.8% 38.6% +7.2 pp Model Higher
Draw 28.8% 29.9% -1.1 pp Aligned
Vibonese 25.4% 31.4% -6.0 pp Market Higher

The statistical model estimates Nissa's win probability at 45.8%, compared with the closing market's implied probability of 38.6%, a difference of 7.2 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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: PRE10.

After full time, the result was Vibonese win 0–2.

Market Assessment

The fair estimate shows a modest edge over current market pricing on Nissa.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)

Market lesson

The closing market differed from the model on Nissa by 7.2 percentage points (38.6% vs model 45.8%) — in this case the market view proved closer.

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Prediction Timeline

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

  1. Sep 27, 2026 · 12:57 UTC Forecast generated
    • Model 1X2 · Nissa 45.8% · Draw 28.8% · Vibonese 25.4%
    • xG · Nissa 1.52 — Vibonese 1.08
  2. Sep 27, 2026 · 12:38 UTC Opening odds snapshot PRE30
    • 1X2 odds · Nissa 2.30 · Draw 2.97 · Vibonese 2.83
    • Implied 1X2 · Nissa 38.6% · Draw 29.9% · Vibonese 31.4%
    • Bookmaker · Pinnacle
  3. Sep 27, 2026 · 12:57 UTC Closing snapshot recorded PRE10
    • 1X2 odds · Nissa 2.30 · Draw 2.97 · Vibonese 2.83
    • Implied 1X2 · Nissa 38.6% · Draw 29.9% · Vibonese 31.4%
    • Bookmaker · Pinnacle
  4. Sep 27, 2026 · 13:00 UTC Kickoff
  5. FT Full-time result Vibonese win · 0–2
  6. FT Prediction missed 1X2 lean did not match full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Observe
Historical Decision No Primary Bet
Outcome Missed
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) 64/100
Betting Confidence 78/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 21, 2026 · 01:33 UTC Snapshot ID: dp-10093992

Closing Odds 2.3
AI Fair Odds —
CLV Pending
Final Result Vibonese win · Nissa 0–2 Vibonese
Prediction ✖ Missed
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

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: Serie D - Girone I
  • Fixture: Nissa vs Vibonese
  • Kickoff: 2026-09-27 13:00:00
  • 1X2 (model): Home 45.8% · Draw 28.8% · Away 25.4%
  • xG (showing): Nissa 1.52 — Vibonese 1.08 (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 53.2% · No 46.8%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 53.2% · No 46.8%
  • Correct score (top bin): 1-1 (12.2%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

Historical Recommendation

Historical Decision: No Primary Bet

Outcome: Missed — Pre-match 1X2 lean did not match 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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Serie D - Girone I Serie D - Girone I — Standings
# TEAM MP W D L PTS
1 Reggina 4 4 0 0 12
2 Igea Virtus 4 3 1 0 10
3 Sambiase 4 3 1 0 10
4 Licata 5 2 2 1 8
5 Vibonese 4 2 1 1 7
6 Nissa 4 2 1 1 7
7 Digiesse PraiaTortora 4 1 3 0 6
8 Milazzo 4 2 0 2 6
9 Calcio Avola 4 2 0 2 6
10 CastrumFavara 4 1 1 2 4
11 Modica 4 1 1 2 4
12 AC Palermo 4 1 1 2 4
13 Gela 4 1 1 2 3
14 Ragusa 4 0 2 2 2
15 Vigor Lamezia 4 0 2 2 2
16 Siracusa 4 2 2 0 1
17 Enna 5 0 1 4 1
18 Trapani 1905 4 0 0 4
# TEAM MP GS GC +/- PTS
1 Reggina 4 13 0 +13 12
2 Igea Virtus 4 13 8 +5 10
3 Vibonese 4 11 5 +6 7
4 Nissa 4 8 6 +2 7
5 Digiesse PraiaTortora 4 7 2 +5 6
6 Siracusa 4 7 4 +3 1
7 Calcio Avola 4 7 10 -3 6
8 Licata 5 6 7 -1 8
9 AC Palermo 4 6 8 -2 4
10 Sambiase 4 5 2 +3 10
11 CastrumFavara 4 5 4 +1 4
12 Milazzo 4 4 5 -1 6
13 Gela 4 4 5 -1 3
14 Ragusa 4 4 7 -3 2
15 Vigor Lamezia 4 4 9 -5 2
16 Modica 4 3 4 -1 4
17 Trapani 1905 4 1 10 -9
18 Enna 5 0 12 -12 1