Predictions / Football / World. Friendlies Clubs / Cardiff vs AS Roma

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

Cardiff Cardiff
Aug 01, 2026 - 14:00
4 1.33
1 1.27
xG Accuracy: 45%
AS Roma AS Roma

AI correctly predicted the Cardiff win.

The match finished 4–1, 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 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Cardiff Cardiff ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 4-1 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

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

Largest probability gap: AS Roma -24.5 pp

Outcome Model Closing Market Difference Signal
Cardiff 36.6% 22.0% +14.6 pp Model Edge
Draw 29.6% 19.7% +9.9 pp Model Higher
AS Roma 33.8% 58.3% -24.5 pp Market Higher

The closing market estimates AS Roma's win probability at 58.3%, compared with the model's estimate of 33.8%, a difference of 24.5 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 (Cardiff win 4–1).

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 5 goals materialised
  • Both Teams To Score (Yes) matched the full-time result

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (5 goals)
  • 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 Cardiff higher (61.1% vs model 36.6%, 24.5 pp), but the model's lean was validated (Cardiff win 4–1).

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Prediction Timeline

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

  1. Aug 01, 2026 · 13:59 UTC Forecast generated
    • Model 1X2 · Cardiff 36.6% · Draw 29.6% · AS Roma 33.8%
    • xG · Cardiff 1.33 — AS Roma 1.27
  2. Aug 01, 2026 · 13:43 UTC Opening odds snapshot PRE30
    • 1X2 odds · Cardiff 4.09 · Draw 4.55 · AS Roma 1.54
    • Implied 1X2 · Cardiff 22.0% · Draw 19.7% · AS Roma 58.3%
    • Bookmaker · Pinnacle
  3. Aug 01, 2026 · 13:59 UTC Closing snapshot recorded PRE10
    • 1X2 odds · Cardiff 4.09 · Draw 4.55 · AS Roma 1.54
    • Implied 1X2 · Cardiff 22.0% · Draw 19.7% · AS Roma 58.3%
    • Bookmaker · Pinnacle
  4. Aug 01, 2026 · 14:00 UTC Kickoff
  5. FT Full-time result Cardiff win · 4–1
  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 (25 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Monitoring Confidence 14/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 26, 2026 · 03:48 UTC Snapshot ID: dp-1813559

Closing Odds 1.54
AI Fair Odds —
CLV Pending
Final Result Cardiff win · Cardiff 4–1 AS Roma
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

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

  • League: Friendlies Clubs
  • Fixture: Cardiff vs AS Roma
  • Kickoff: 2026-08-01 14:00:00
  • 1X2 (model): Home 36.6% · Draw 29.6% · Away 33.8%
  • xG (showing): Cardiff 1.33 — AS Roma 1.27 (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 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Prefer skipping to over-staking when the engine is honest about missing edge.

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 29, 2026 (UTC)

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