Predictions / Football / Morocco. Botola 2 / USM Oujda vs Mouloudia Oujda

Prediction Audit: USM Oujda vs Mouloudia Oujda Prediction, Odds & AI Betting Tips

USM Oujda USM Oujda
Sep 27, 2026 - 15:00
2 1.27
1 1.33
xG Accuracy: 75%
Mouloudia Oujda Mouloudia Oujda

The model missed the final outcome (USM Oujda win 2–1).

The model had projected Mouloudia Oujda at 36.6%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade C

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Mouloudia Oujda USM Oujda ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 2-1 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The model rates Mouloudia Oujda considerably stronger than the closing betting market.

Largest probability gap: Mouloudia Oujda +8.7 pp

Outcome Model Closing Market Difference Signal
USM Oujda 33.8% 37.6% -3.9 pp Aligned
Draw 29.6% 34.5% -4.8 pp Aligned
Mouloudia Oujda 36.6% 27.9% +8.7 pp Model Higher

The statistical model estimates Mouloudia Oujda's win probability at 36.6%, compared with the closing market's implied probability of 27.9%, a difference of 8.7 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 USM Oujda win 2–1.

Market Assessment

The fair estimate shows a modest edge over current market pricing on Mouloudia Oujda.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised
  • Both Teams To Score (Yes) matched the full-time result
  • Over 2.5 goals aligned with the xG profile

What failed

  • 1X2: model leaned Mouloudia Oujda; match finished USM Oujda

Market lesson

The closing market differed from the model on Mouloudia Oujda by 8.7 percentage points (27.9% 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 27, 2026 · 15:01 UTC Forecast generated
    • Model 1X2 · USM Oujda 33.8% · Draw 29.6% · Mouloudia Oujda 36.6%
    • xG · USM Oujda 1.27 — Mouloudia Oujda 1.33
  2. Sep 27, 2026 · 14:32 UTC Opening odds snapshot PRE30
    • 1X2 odds · USM Oujda 2.45 · Draw 2.57 · Mouloudia Oujda 3.05
    • Implied 1X2 · USM Oujda 36.3% · Draw 34.6% · Mouloudia Oujda 29.1%
    • Bookmaker · Pinnacle
  3. Sep 27, 2026 · 15:01 UTC Closing snapshot recorded PRE1
    • 1X2 odds · USM Oujda 2.39 · Draw 2.61 · Mouloudia Oujda 3.22
    • Implied 1X2 · USM Oujda 37.6% · Draw 34.5% · Mouloudia Oujda 27.9%
    • Bookmaker · Pinnacle
  4. Sep 27, 2026 · 15:00 UTC Kickoff
  5. FT Full-time result USM Oujda win · 2–1
  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 75/100 · High
  • Validation: Pass
Evidence ★★★★★
  • Statistical edge detected
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 19/100
Monitoring Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 23, 2026 · 00:52 UTC Snapshot ID: dp-10412082

Closing Odds 3.22
AI Fair Odds —
CLV Pending
Final Result USM Oujda win · USM Oujda 2–1 Mouloudia Oujda
Prediction ✖ Missed
Decision Grade C

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: Botola 2
  • Fixture: USM Oujda vs Mouloudia Oujda
  • Kickoff: 2026-09-27 15:00:00
  • 1X2 (model): Home 33.8% · Draw 29.6% · Away 36.6%
  • xG (showing): USM Oujda 1.27 — Mouloudia Oujda 1.33 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Over 2.5 goals
  • Model: 48.2% · Implied: 32.3% · Probability edge: +15.9 pts · Est. EV: +39.3%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

1X2 can look balanced even when side markets show clearer structure.

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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