Prediction Audit: Austin vs Puebla Prediction, Odds & AI Betting Tips

Aug 10, 2026 - 01:00
3 1.36
0 1.24
xG Accuracy: 45%

AI correctly predicted the Austin win.

The match finished 3–0, validating the model's directional assessment.

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 Over 2.5 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Austin Austin ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Austin higher than the statistical model.

Largest probability gap: Austin -18.1 pp

Outcome Model Closing Market Difference Signal
Austin 38.0% 56.2% -18.1 pp Market Higher
Draw 29.6% 22.5% +7.1 pp Model Higher
Puebla 32.4% 21.3% +11.1 pp Model Edge

The closing market estimates Austin's win probability at 56.2%, compared with the model's estimate of 38.0%, a difference of 18.1 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 (Austin win 3–0).

Market Assessment

The market is materially more optimistic about Austin 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

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Austin higher (56.1% vs model 38.0%, 18.1 pp), but the model's lean was validated (Austin win 3–0).

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Prediction Timeline

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

  1. Aug 10, 2026 · 00:59 UTC Forecast generated
    • Model 1X2 · Austin 38.0% · Draw 29.6% · Puebla 32.4%
    • xG · Austin 1.36 — Puebla 1.24
  2. Aug 10, 2026 · 00:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Austin 1.71 · Draw 4.27 · Puebla 4.50
    • Implied 1X2 · Austin 56.2% · Draw 22.5% · Puebla 21.3%
    • Bookmaker · Pinnacle
  3. Aug 10, 2026 · 00:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Austin 1.71 · Draw 4.27 · Puebla 4.50
    • Implied 1X2 · Austin 56.2% · Draw 22.5% · Puebla 21.3%
    • Bookmaker · Pinnacle
  4. Aug 10, 2026 · 01:00 UTC Kickoff
  5. FT Full-time result Austin win · 3–0
  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: Monitor
Historical Decision Monitor
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 54/100 · Moderate
  • Validation: Warning
  • Large market gap (18 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 9/100
Betting Confidence 43/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 04, 2026 · 02:07 UTC Snapshot ID: dp-2971327

Closing Odds 1.71
AI Fair Odds —
CLV Pending
Final Result Austin win · Austin 3–0 Puebla
Prediction ✔ Correct
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

Quick read on how the model reads this matchup.

  • League: Leagues Cup
  • Fixture: Austin vs Puebla
  • Kickoff: 2026-08-10 01:00:00
  • 1X2 (model): Home 38.0% · Draw 29.6% · Away 32.4%
  • xG (showing): Austin 1.36 — Puebla 1.24 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • 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 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

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 28, 2026 (UTC)

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