Predictions / Football / Italy. Serie B / Padova vs Ascoli

Prediction Audit: Padova vs Ascoli Prediction, Odds & AI Betting Tips

Padova Padova
Sep 12, 2026 - 13:00
1 1.15
0 1.16
xG Accuracy: 70%
Ascoli Ascoli

AI correctly predicted the Padova win.

The match finished 1–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade A

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 No No ✔ Correct
  • 1X2 Padova Padova ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 0-0, 1-2 1-0 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The closing market prices Padova higher than the statistical model.

Largest probability gap: Padova -6.4 pp

Outcome Model Closing Market Difference Signal
Padova 36.5% 42.8% -6.4 pp Market Higher
Draw 31.0% 29.4% +1.6 pp Aligned
Ascoli 32.5% 27.7% +4.8 pp Aligned

The closing market estimates Padova's win probability at 42.8%, compared with the model's estimate of 36.5%, a difference of 6.4 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 (Padova win 1–0).

Market Assessment

The market and model broadly agree on Padova. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.

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

Post Match Insights

What worked

  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–0 fell within the model's highlighted bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Padova higher (42.9% vs model 36.5%, 6.4 pp), but the model's lean was validated (Padova win 1–0).

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Prediction Timeline

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

  1. Sep 12, 2026 · 19:26 UTC Forecast generated
    • Model 1X2 · Padova 36.5% · Draw 31.1% · Ascoli 32.5%
    • xG · Padova 1.15 — Ascoli 1.16
  2. Sep 12, 2026 · 12:33 UTC Opening odds snapshot PRE30
    • 1X2 odds · Padova 2.26 · Draw 3.29 · Ascoli 3.49
    • Implied 1X2 · Padova 42.8% · Draw 29.4% · Ascoli 27.7%
    • Bookmaker · Pinnacle
  3. Sep 12, 2026 · 13:02 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Padova 2.26 · Draw 3.29 · Ascoli 3.49
    • Implied 1X2 · Padova 42.8% · Draw 29.4% · Ascoli 27.7%
    • Bookmaker · Pinnacle
  4. Sep 12, 2026 · 13:00 UTC Kickoff
  5. FT Full-time result Padova 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: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 76/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 68/100
Betting Confidence 79/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 07, 2026 · 01:25 UTC Snapshot ID: dp-7433865

Closing Odds 2.26
AI Fair Odds —
CLV Pending
Final Result Padova win · Padova 1–0 Ascoli
Prediction ✔ Correct
Decision Grade A

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): +37.5%

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: Serie B
  • Fixture: Padova vs Ascoli
  • Kickoff: 2026-09-12 13:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Padova 1.15 — Ascoli 1.16 (total xG ≈ 2.31)
  • 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

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: 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 15, 2026 (UTC)

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Serie B Serie B — Standings
# TEAM MP W D L PTS
1 Mantova 4 3 1 0 10
2 Palermo 4 3 1 0 10
3 Sudtirol 4 2 2 0 8
4 Avellino 4 2 1 1 7
5 Padova 4 2 1 1 7
6 Modena 4 2 1 1 7
7 Ascoli 4 2 1 1 7
8 Cesena 4 1 3 0 6
9 Pisa 4 2 0 2 6
10 Empoli 4 2 0 2 6
11 Arezzo 4 2 0 2 6
12 Vicenza Virtus 4 1 2 1 5
13 Benevento 4 1 1 2 4
14 Virtus Entella 4 1 1 2 4
15 Cremonese 4 1 1 2 4
16 Verona 4 1 1 2 4
17 Catanzaro 4 1 0 3 3
18 Juve Stabia 4 1 1 2 2
19 Carrarese 4 0 1 3 1
20 Sampdoria 4 0 1 3 1
# TEAM MP GS GC +/- PTS
1 Mantova 4 8 3 +5 10
2 Palermo 4 8 4 +4 10
3 Verona 4 8 6 +2 4
4 Virtus Entella 4 7 6 +1 4
5 Avellino 4 6 3 +3 7
6 Modena 4 6 3 +3 7
7 Cesena 4 6 5 +1 6
8 Pisa 4 6 6 0 6
9 Vicenza Virtus 4 6 8 -2 5
10 Sudtirol 4 5 2 +3 8
11 Benevento 4 5 5 0 4
12 Cremonese 4 5 7 -2 4
13 Arezzo 4 5 9 -4 6
14 Ascoli 4 4 3 +1 7
15 Padova 4 4 4 0 7
16 Catanzaro 4 4 7 -3 3
17 Empoli 4 3 4 -1 6
18 Juve Stabia 4 3 6 -3 2
19 Sampdoria 4 3 8 -5 1
20 Carrarese 4 2 5 -3 1
# TEAM MP xG xGC +/- PTS
1 Verona 4 4.8 2.2 +2.6 4
2 Modena 4 3.2 1.3 +1.9 7
3 Benevento 4 2.8 1.1 +1.7 4
4 Pisa 4 3.7 2.2 +1.5 6
5 Palermo 4 3.2 2.2 +1.0 10
6 Cesena 4 3.0 2.1 +0.9 6
7 Mantova 4 2.9 2.6 +0.3 10
8 Sampdoria 4 2.3 2.3 0.0 1
9 Carrarese 4 2.7 2.8 -0.1 1
10 Vicenza Virtus 4 2.9 3.1 -0.2 5
11 Arezzo 4 2.5 2.7 -0.2 6
12 Empoli 4 1.4 1.6 -0.2 6
13 Virtus Entella 4 1.2 1.4 -0.2 4
14 Juve Stabia 4 2.1 2.4 -0.3 2
15 Cremonese 4 0.7 1.6 -0.9 4
16 Catanzaro 4 2.8 3.8 -1.0 3
17 Padova 4 2.0 3.3 -1.3 7
18 Sudtirol 4 1.5 2.8 -1.3 8
19 Avellino 4 2.5 4.4 -1.9 7
20 Ascoli 4 2.9 4.9 -2.0 7
Serie B Italy. Serie B Predictions