AI correctly predicted the Diriangén win.
The match finished 1–3, validating the model's directional assessment.
Tracked markets vs full-time result
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 (4 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Diriangén Diriangén ✔ Correct
- Correct Score Insights 1-1, 0-1, 1-2, 1-0, 0-2 1-3 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Walter Ferretti | 27.1% | 23.8% | +3.3 pp | Aligned |
| Draw | 29.1% | 26.5% | +2.6 pp | Aligned |
| Diriangén | 43.8% | 49.7% | -5.8 pp | Market Higher |
The closing market estimates Diriangén's win probability at 49.7%, compared with the model's estimate of 43.8%, a difference of 5.8 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 (Diriangén win 1–3).
Market Assessment
The market and model broadly agree on Diriangén. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.
- Monitor line movement before kickoff — not a betting recommendation.
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 2.60) — 4 goals materialised
- Diriangén attacking xG significantly stronger (1.48 vs 1.12)
- Both Teams To Score (Yes) matched the full-time result
What failed
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)
- Exact score: outside the model's top score bins
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Diriangén higher (49.6% vs model 43.8%, 5.8 pp), but the model's lean was validated (Diriangén win 1–3).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Jul 25, 2026 · 19:18 UTC Forecast generated
- Model 1X2 · Walter Ferretti 27.1% · Draw 29.1% · Diriangén 43.9%
- xG · Walter Ferretti 1.12 — Diriangén 1.48
-
Jul 24, 2026 · 23:29 UTC Opening odds snapshot PRE30
- 1X2 odds · Walter Ferretti 3.84 · Draw 3.45 · Diriangén 1.84
- Implied 1X2 · Walter Ferretti 23.8% · Draw 26.5% · Diriangén 49.7%
- Bookmaker · Pinnacle
-
Jul 24, 2026 · 23:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Walter Ferretti 3.84 · Draw 3.45 · Diriangén 1.84
- Implied 1X2 · Walter Ferretti 23.8% · Draw 26.5% · Diriangén 49.7%
- Bookmaker · Pinnacle
-
Jul 25, 2026 · 00:00 UTC Kickoff
-
FT Full-time result Diriangén win · 1–3
-
FT Prediction validated Directional lean matched full-time result
-
Archived Prediction review
Historical Snapshot
Frozen at kickoff — the model output as it stood before the match started.
Pre-match metrics (historical context)
- Validation: Pass
- No strong statistical edge
- Direction agrees with model lean
- Validation passed
Validation Report
Immutable SnapshotModel 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.
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Primera Division — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Managua | 9 | 7 | 2 | 0 | 23 |
| 2 | Diriangén | 9 | 6 | 3 | 0 | 21 |
| 3 | Real Estelí | 9 | 5 | 3 | 1 | 18 |
| 4 | UNAN Managua | 9 | 5 | 2 | 2 | 17 |
| 5 | San Marcos | 9 | 3 | 2 | 4 | 11 |
| 6 | H&H Export | 9 | 3 | 2 | 4 | 11 |
| 7 | Matagalpa | 9 | 3 | 0 | 6 | 9 |
| 8 | Walter Ferretti | 10 | 2 | 1 | 7 | 7 |
| 9 | Jalapa | 10 | 2 | 1 | 7 | 7 |
| 10 | Rancho Santana | 9 | 1 | 2 | 6 | 5 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Managua | 9 | 27 | 9 | +18 | 23 |
| 2 | Diriangén | 9 | 18 | 7 | +11 | 21 |
| 3 | Real Estelí | 9 | 17 | 6 | +11 | 18 |
| 4 | Walter Ferretti | 10 | 12 | 17 | -5 | 7 |
| 5 | UNAN Managua | 9 | 11 | 7 | +4 | 17 |
| 6 | San Marcos | 9 | 9 | 12 | -3 | 11 |
| 7 | H&H Export | 9 | 9 | 17 | -8 | 11 |
| 8 | Rancho Santana | 9 | 7 | 14 | -7 | 5 |
| 9 | Jalapa | 10 | 5 | 14 | -9 | 7 |
| 10 | Matagalpa | 9 | 4 | 16 | -12 | 9 |
