Predictions / Football / Brazil. Copa Paulista / Juventus vs União São João

Prediction Audit: Juventus vs União São João Prediction, Odds & AI Betting Tips

Sep 21, 2026 - 23:30
1 1.27
1 1.33
xG Accuracy: 85%

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

The model had projected União São João 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 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 União São João Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The model rates União São João considerably stronger than the closing betting market.

Largest probability gap: União São João +14.7 pp

Outcome Model Closing Market Difference Signal
Juventus 33.8% 45.8% -12.0 pp Market Higher
Draw 29.6% 32.4% -2.7 pp Aligned
União São João 36.6% 21.9% +14.7 pp Model Edge

The statistical model estimates União São João's win probability at 36.6%, compared with the closing market's implied probability of 21.9%, a difference of 14.7 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 Draw 1–1.

Market Assessment

The statistical fair estimate is materially higher than the market on União São João.

  • 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

  • Both Teams To Score (Yes) matched the full-time result
  • Exact score 1–1 fell within the model's highlighted bins

What failed

  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)
  • 1X2: model leaned União São João; match finished Draw

Market lesson

The closing market differed from the model on União São João by 14.7 percentage points (21.9% 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 21, 2026 · 23:29 UTC Forecast generated
    • Model 1X2 · Juventus 33.8% · Draw 29.6% · União São João 36.6%
    • xG · Juventus 1.27 — União São João 1.33
  2. Sep 21, 2026 · 22:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Juventus 1.93 · Draw 2.73 · União São João 4.04
    • Implied 1X2 · Juventus 45.8% · Draw 32.4% · União São João 21.9%
    • Bookmaker · Pinnacle
  3. Sep 21, 2026 · 23:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Juventus 1.93 · Draw 2.73 · União São João 4.04
    • Implied 1X2 · Juventus 45.8% · Draw 32.4% · União São João 21.9%
    • Bookmaker · Pinnacle
  4. Sep 21, 2026 · 23:30 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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 56/100 · Moderate
  • Validation: Warning
  • Large market gap (15 pp)
Evidence ★★★★★
  • Statistical edge detected
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 9/100
Monitoring Confidence 19/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 15, 2026 · 02:58 UTC Snapshot ID: dp-8841059

Closing Odds 4.04
AI Fair Odds —
CLV Pending
Final Result Draw · Juventus 1–1 União São João
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

Quick read on how the model reads this matchup.

  • League: Copa Paulista
  • Fixture: Juventus vs União São João
  • Kickoff: 2026-09-21 23:30:00
  • 1X2 (model): Home 33.8% · Draw 29.6% · Away 36.6%
  • xG (showing): Juventus 1.27 — União São João 1.33 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): BTTS Yes
  • Model: 54.5% · Implied: 47.3% · Probability edge: +7.2 pts · Est. EV: +9.0%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Correct score remains high-variance even when a line is most likely on paper.

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 30, 2026 (UTC)

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