Predictions / Football / Italy. Serie B / Cesena vs Mantova

Prediction Audit: Cesena vs Mantova Prediction, Odds & AI Betting Tips

Cesena Cesena
Sep 06, 2026 - 13:00
1 1.04
1 1.18
xG Accuracy: 94%
Mantova Mantova

The model missed the final outcome (Draw 1–1).

The model had projected Mantova at 37.4%, 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 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Mantova Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 0-0, 1-2 1-1 ✔ Correct

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Draw +3.0 pp

Outcome Model Closing Market Difference Signal
Cesena 31.4% 33.9% -2.5 pp Aligned
Draw 31.1% 28.1% +3.0 pp Aligned
Mantova 37.4% 37.9% -0.5 pp Aligned

The model and closing market are broadly aligned, with probability differences below 5 percentage points.

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: PRE5.

After full time, the result was Draw 1–1.

Market Assessment

The market and model are broadly aligned. Any small pricing gap likely reflects rounding or bookmaker margin, not a structural disagreement.

  • Current pricing remains close to the model baseline.

Post Match Insights

What worked

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

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • 1X2: model leaned Mantova; match finished Draw

Market lesson

The full-time result was Draw 1–1, which did not match the model's pre-match lean on 1X2.

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Prediction Timeline

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

  1. Sep 06, 2026 · 19:20 UTC Forecast generated
    • Model 1X2 · Cesena 31.4% · Draw 31.1% · Mantova 37.4%
    • xG · Cesena 1.04 — Mantova 1.18
  2. Sep 06, 2026 · 12:33 UTC Opening odds snapshot PRE30
    • 1X2 odds · Cesena 2.85 · Draw 3.44 · Mantova 2.55
    • Implied 1X2 · Cesena 33.9% · Draw 28.1% · Mantova 37.9%
    • Bookmaker · Pinnacle
  3. Sep 06, 2026 · 12:58 UTC Closing snapshot recorded PRE5
    • 1X2 odds · Cesena 2.85 · Draw 3.44 · Mantova 2.55
    • Implied 1X2 · Cesena 33.9% · Draw 28.1% · Mantova 37.9%
    • Bookmaker · Pinnacle
  4. Sep 06, 2026 · 13:00 UTC Kickoff
  5. FT Full-time result Draw · 1–1
  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 77/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 84/100
Betting Confidence 80/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 31, 2026 · 07:02 UTC Snapshot ID: dp-6355791

Closing Odds 3.44
AI Fair Odds —
CLV Pending
Final Result Draw · Cesena 1–1 Mantova
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

Pre-match snapshot for this fixture.

  • League: Serie B
  • Fixture: Cesena vs Mantova
  • Kickoff: 2026-09-06 13:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Cesena 1.04 — Mantova 1.18 (total xG ≈ 2.22)
  • 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

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.

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 29, 2026 (UTC)

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