Predictions / Football / World. Friendlies Clubs / Bologna vs Iraklis 1908

Prediction Audit: Bologna vs Iraklis 1908 Prediction, Odds & AI Betting Tips

Bologna Bologna
Jul 25, 2026 - 14:00
2 1.41
0 1.19
xG Accuracy: 61%
Iraklis 1908 Iraklis 1908

AI correctly predicted the Bologna win.

The match finished 2–0, 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 (2 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Bologna Bologna ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 0-0 2-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Bologna higher than the statistical model.

Largest probability gap: Bologna -24.2 pp

Outcome Model Closing Market Difference Signal
Bologna 57.2% 81.4% -24.2 pp Market Higher
Draw 22.9% 10.4% +12.6 pp Model Edge
Iraklis 1908 19.9% 8.2% +11.7 pp Model Edge

The closing market estimates Bologna's win probability at 81.4%, compared with the model's estimate of 57.2%, a difference of 24.2 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: PRE10.

After full time, the model's directional lean matched the result (Bologna win 2–0).

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Exact score: outside the model's top score bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Bologna higher (81.4% vs model 57.2%, 24.2 pp), but the model's lean was validated (Bologna win 2–0).

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Prediction Timeline

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

  1. Jul 25, 2026 · 21:58 UTC Forecast generated
    • Model 1X2 · Bologna 57.2% · Draw 22.9% · Iraklis 1908 19.9%
    • xG · Bologna 1.41 — Iraklis 1908 1.19
  2. Jul 25, 2026 · 13:41 UTC Opening odds snapshot PRE30
    • 1X2 odds · Bologna 1.05 · Draw 11.26 · Iraklis 1908 13.03
    • Implied 1X2 · Bologna 85.2% · Draw 7.9% · Iraklis 1908 6.9%
    • Bookmaker · Pinnacle
  3. Jul 25, 2026 · 14:02 UTC Closing snapshot recorded PRE10
    • 1X2 odds · Bologna 1.11 · Draw 8.69 · Iraklis 1908 11.01
    • Implied 1X2 · Bologna 81.4% · Draw 10.4% · Iraklis 1908 8.2%
    • Bookmaker · Pinnacle
  4. Jul 25, 2026 · 14:00 UTC Kickoff
  5. FT Full-time result Bologna win · 2–0
  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: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 51/100 · Moderate
  • Validation: Warning
  • Large market gap (24 pp)
Evidence ★★★★★
  • Moderate model lean
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 14:08 UTC Snapshot ID: dp-1456300

Closing Odds 1.11
AI Fair Odds —
CLV Pending
Final Result Bologna win · Bologna 2–0 Iraklis 1908
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

Quick read on how the model reads this matchup.

  • League: Club Friendlies
  • Fixture: Bologna vs Iraklis 1908
  • Kickoff: 2026-07-25 14:00:00
  • 1X2 (model): Home 33.0% · Draw 33.0% · Away 33.0%
  • xG (showing): Bologna 1.41 — Iraklis 1908 1.19 (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

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.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: Wait

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 26, 2026 (UTC)

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