Prediction Audit: Aurora vs Marquense Prediction, Odds & AI Betting Tips

Sep 19, 2026 - 21:00
1 1.27
0 1.33
xG Accuracy: 64%

The model missed the final outcome (Aurora win 1–0).

The model had projected Marquense at 36.6%, 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 Over 2.5 Under 2.5 (1 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Marquense Aurora ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-0 ✔ Correct

Model vs Closing Market

Strong Disagreement

The model rates Marquense considerably stronger than the closing betting market.

Largest probability gap: Marquense +11.3 pp

Outcome Model Closing Market Difference Signal
Aurora 33.8% 44.7% -10.9 pp Market Higher
Draw 29.6% 30.1% -0.4 pp Aligned
Marquense 36.6% 25.2% +11.3 pp Model Edge

The statistical model estimates Marquense's win probability at 36.6%, compared with the closing market's implied probability of 25.2%, a difference of 11.3 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 result was Aurora win 1–0.

Market Assessment

The statistical fair estimate is materially higher than the market on Marquense.

  • The model may see a slower-scoring or closer matchup than the market.
  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What worked

  • Exact score 1–0 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (1 goals)

Market lesson

The closing market differed from the model on Marquense by 11.3 percentage points (25.3% vs model 36.6%) — in this case the market view proved closer.

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Prediction Timeline

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

  1. Sep 19, 2026 · 20:59 UTC Forecast generated
    • Model 1X2 · Aurora 33.8% · Draw 29.6% · Marquense 36.6%
    • xG · Aurora 1.27 — Marquense 1.33
  2. Sep 19, 2026 · 20:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Aurora 2.05 · Draw 3.05 · Marquense 3.63
    • Implied 1X2 · Aurora 44.7% · Draw 30.1% · Marquense 25.2%
    • Bookmaker · Pinnacle
  3. Sep 19, 2026 · 20:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Aurora 2.05 · Draw 3.05 · Marquense 3.63
    • Implied 1X2 · Aurora 44.7% · Draw 30.1% · Marquense 25.2%
    • Bookmaker · Pinnacle
  4. Sep 19, 2026 · 21:00 UTC Kickoff
  5. FT Full-time result Aurora win · 1–0
  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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 57/100 · Moderate
  • Validation: Warning
  • Large market gap (11 pp)
Evidence ★★★★★
  • Statistical edge detected
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 15/100
Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 14, 2026 · 03:44 UTC Snapshot ID: dp-8710030

Closing Odds 3.63
AI Fair Odds —
CLV Pending
Final Result Aurora win · Aurora 1–0 Marquense
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: Liga Nacional
  • Fixture: Aurora vs Marquense
  • Kickoff: 2026-09-19 21:00:00
  • 1X2 (model): Home 33.8% · Draw 29.6% · Away 36.6%
  • xG (showing): Aurora 1.27 — Marquense 1.33 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.9%, still below the +2.0% minimum for a headline / default stake (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 Over 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: Monitor

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 28, 2026 (UTC)

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