Predictions / Football / Paraguay. Copa Paraguay / Deportivo Obrero vs Fernando De La Mora

Prediction Audit: Deportivo Obrero vs Fernando De La Mora Prediction, Odds & AI Betting Tips

Deportivo Obrero Deportivo Obrero
Aug 19, 2026 - 17:00
0 1.36
3 1.24
xG Accuracy: 42%
Fernando De La Mora Fernando De La Mora

The model missed the final outcome (Fernando De La Mora win 0–3).

The model had projected Deportivo Obrero at 38.0%, 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 Under 2.5 Over 2.5 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Deportivo Obrero Fernando De La Mora ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 0-3 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Fernando De La Mora higher than the statistical model.

Largest probability gap: Fernando De La Mora -48.6 pp

Outcome Model Closing Market Difference Signal
Deportivo Obrero 38.0% 7.8% +30.2 pp Model Edge
Draw 29.6% 11.2% +18.4 pp Model Edge
Fernando De La Mora 32.4% 81.0% -48.6 pp Market Higher

The closing market estimates Fernando De La Mora's win probability at 81.0%, compared with the model's estimate of 32.4%, a difference of 48.6 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 result was Fernando De La Mora win 0–3.

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

The closing market differed from the model on Deportivo Obrero by 48.6 percentage points (86.6% vs model 38.0%) — 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. Aug 19, 2026 · 16:59 UTC Forecast generated
    • Model 1X2 · Deportivo Obrero 38.0% · Draw 29.6% · Fernando De La Mora 32.4%
    • xG · Deportivo Obrero 1.36 — Fernando De La Mora 1.24
  2. Aug 19, 2026 · 16:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · Deportivo Obrero 11.36 · Draw 7.95 · Fernando De La Mora 1.10
    • Implied 1X2 · Deportivo Obrero 7.8% · Draw 11.2% · Fernando De La Mora 81.0%
    • Bookmaker · Pinnacle
  3. Aug 19, 2026 · 16:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Deportivo Obrero 11.36 · Draw 7.95 · Fernando De La Mora 1.10
    • Implied 1X2 · Deportivo Obrero 7.8% · Draw 11.2% · Fernando De La Mora 81.0%
    • Bookmaker · Pinnacle
  4. Aug 19, 2026 · 17:00 UTC Kickoff
  5. FT Full-time result Fernando De La Mora win · 0–3
  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: Cautious / Wait

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

Historical Decision Wait
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 25/100 · Low
  • Validation: Fail
  • Large market gap (49 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation failed
Pricing proximity (inverse gap) 0/100
Monitoring Confidence 7/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 13, 2026 · 02:05 UTC Snapshot ID: dp-3820475

Closing Odds 1.1
AI Fair Odds —
CLV Pending
Final Result Fernando De La Mora win · Deportivo Obrero 0–3 Fernando De La Mora
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

Model favours Deportivo Obrero; market prices Fernando De La Mora instead — inputs may be missing or stale.

  • Model: Deportivo Obrero 1.36 xG vs Fernando De La Mora 1.24 → Deportivo Obrero 38.0%
  • Market: Fernando De La Mora ~7.8% implied
  • Validation failed — do not treat 1X2 EV as actionable.

Do not act on 1X2 value until validation passes. Structural leans (O/U, BTTS) need separate odds review.

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

Historical Recommendation

Historical Decision: Wait

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

October 01, 2026 (UTC)

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