Predictions / Football / Italy. Serie A / Verona vs AS Roma

Prediction Audit: Verona vs AS Roma Prediction, Odds & AI Betting Tips

Verona Verona
May 24, 2026 - 18:45
0 0.70
2 1.56
xG Accuracy: 73%
AS Roma AS Roma

AI correctly predicted the AS Roma win.

The match finished 0–2, 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 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 AS Roma AS Roma ✔ Correct
  • Correct Score Insights 0-1, 0-2, 1-1, 0-0, 1-2 0-2 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices AS Roma higher than the statistical model.

Largest probability gap: AS Roma -13.3 pp

Outcome Model Closing Market Difference Signal
Verona 15.2% 10.7% +4.5 pp Aligned
Draw 28.3% 19.5% +8.8 pp Model Higher
AS Roma 56.5% 69.8% -13.3 pp Market Higher

The closing market estimates AS Roma's win probability at 69.8%, compared with the model's estimate of 56.5%, a difference of 13.3 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 (AS Roma win 0–2).

Market Assessment

The market is materially more optimistic about AS Roma 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

  • AS Roma attacking xG significantly stronger (1.56 vs 0.70)
  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced AS Roma higher (69.8% vs model 56.5%, 13.3 pp), but the model's lean was validated (AS Roma win 0–2).

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Prediction Timeline

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

  1. May 24, 2026 · 18:19 UTC Forecast generated
    • Model 1X2 · Verona 15.2% · Draw 28.3% · AS Roma 56.5%
    • xG · Verona 0.70 — AS Roma 1.56
  2. May 24, 2026 · 12:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Verona 9.03 · Draw 4.94 · AS Roma 1.38
    • Implied 1X2 · Verona 10.7% · Draw 19.5% · AS Roma 69.8%
    • Bookmaker · Pinnacle
  3. May 24, 2026 · 12:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Verona 9.03 · Draw 4.94 · AS Roma 1.38
    • Implied 1X2 · Verona 10.7% · Draw 19.5% · AS Roma 69.8%
    • Bookmaker · Pinnacle
  4. May 24, 2026 · 18:45 UTC Kickoff
  5. FT Full-time result AS Roma win · 0–2
  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 56/100 · Moderate
  • Validation: Warning
  • Large market gap (13 pp)
Evidence ★★★★★
  • Moderate model lean
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 33/100
Betting Confidence 44/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 25, 2026 · 09:09 UTC Snapshot ID: dp-1692523

Closing Odds 1.38
AI Fair Odds —
CLV Pending
Final Result AS Roma win · Verona 0–2 AS Roma
Prediction ✔ Correct
Decision Grade A

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 A
  • Fixture: Verona vs AS Roma
  • Kickoff: 2026-05-24 13:00:00
  • 1X2 (model): Home 15.2% · Draw 28.3% · Away 56.5%
  • xG (showing): Verona 0.7 — AS Roma 1.56 (total xG ≈ 2.26)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 60.7% · Implied: 47.2% · Probability edge: +13.5 pts · Est. EV: +26.9%
  • BTTS (model): Yes 41.2% · No 58.8%
  • Correct score (top bin): 0-1 (16.3%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

1X2 can look balanced even when side markets show clearer structure.

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 29, 2026 (UTC)

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Serie A Serie A — Standings
# TEAM MP W D L PTS
1 Inter 38 27 6 5 87
2 Napoli 38 23 7 8 76
3 AS Roma 38 23 4 11 73
4 Como 38 20 11 7 71
5 AC Milan 38 20 10 8 70
6 Juventus 38 19 12 7 69
7 Atalanta 38 15 14 9 59
8 Bologna 38 16 8 14 56
9 Lazio 38 14 12 12 54
10 Udinese 38 14 8 16 50
11 Sassuolo 38 14 7 17 49
12 Torino 38 12 9 17 45
13 Parma 38 11 12 15 45
14 Cagliari 38 11 10 17 43
15 Fiorentina 38 9 15 14 42
16 Genoa 38 10 11 17 41
17 Lecce 38 10 8 20 38
18 Cremonese 38 8 10 20 34
19 Verona 38 3 12 23 21
20 Pisa 38 2 12 24 18
# TEAM MP GS GC +/- PTS
1 Inter 38 89 35 +54 87
2 Como 38 65 29 +36 71
3 Juventus 38 61 34 +27 69
4 AS Roma 38 59 31 +28 73
5 Napoli 38 58 36 +22 76
6 AC Milan 38 53 35 +18 70
7 Atalanta 38 51 36 +15 59
8 Bologna 38 49 46 +3 56
9 Sassuolo 38 46 50 -4 49
10 Udinese 38 45 48 -3 50
11 Torino 38 44 63 -19 45
12 Lazio 38 41 40 +1 54
13 Fiorentina 38 41 50 -9 42
14 Genoa 38 41 51 -10 41
15 Cagliari 38 40 53 -13 43
16 Cremonese 38 32 57 -25 34
17 Parma 38 28 46 -18 45
18 Lecce 38 28 50 -22 38
19 Pisa 38 26 71 -45 18
20 Verona 38 25 61 -36 21
# TEAM MP xG xGC +/- PTS
1 Inter 38 71.5 34.8 +36.7 87
2 Juventus 38 65.6 32.0 +33.6 69
3 Como 38 62.2 33.8 +28.4 71
4 AC Milan 38 59.6 43.3 +16.3 70
5 AS Roma 38 55.4 39.1 +16.3 73
6 Atalanta 38 57.3 42.2 +15.1 59
7 Napoli 38 49.7 36.7 +13.0 76
8 Fiorentina 38 49.8 47.5 +2.3 42
9 Bologna 38 44.0 45.8 -1.8 56
10 Lazio 38 41.0 43.5 -2.5 54
11 Genoa 38 45.1 48.8 -3.7 41
12 Torino 38 44.8 52.8 -8.0 45
13 Udinese 38 42.0 52.2 -10.2 50
14 Sassuolo 38 42.6 55.3 -12.7 49
15 Verona 38 35.7 50.4 -14.7 21
16 Cagliari 38 38.6 53.8 -15.2 43
17 Pisa 38 39.6 58.9 -19.3 18
18 Cremonese 38 35.0 57.8 -22.8 34
19 Parma 38 32.2 56.6 -24.4 45
20 Lecce 38 30.9 57.4 -26.5 38