AI correctly predicted the Zimbru win.
The match finished 4–2, 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 (6 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Zimbru Zimbru ✔ Correct
- Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 4-2 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Zimbru | 37.5% | 52.5% | -14.9 pp | Market Higher |
| Draw | 29.6% | 25.9% | +3.8 pp | Aligned |
| Milsami Orhei | 32.9% | 21.7% | +11.2 pp | Model Edge |
The closing market estimates Zimbru's win probability at 52.5%, compared with the model's estimate of 37.5%, a difference of 14.9 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 (Zimbru win 4–2).
Market Assessment
The market is materially more optimistic about Zimbru 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) — 6 goals materialised
- 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 (6 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 Zimbru higher (52.4% vs model 37.5%, 14.9 pp), but the model's lean was validated (Zimbru win 4–2).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Aug 16, 2026 · 17:01 UTC Forecast generated
- Model 1X2 · Zimbru 37.6% · Draw 29.6% · Milsami Orhei 32.9%
- xG · Zimbru 1.35 — Milsami Orhei 1.25
-
Aug 16, 2026 · 16:32 UTC Opening odds snapshot PRE30
- 1X2 odds · Zimbru 1.69 · Draw 3.43 · Milsami Orhei 4.09
- Implied 1X2 · Zimbru 52.5% · Draw 25.9% · Milsami Orhei 21.7%
- Bookmaker · Pinnacle
-
Aug 16, 2026 · 17:01 UTC Closing snapshot recorded PRE1
- 1X2 odds · Zimbru 1.69 · Draw 3.43 · Milsami Orhei 4.09
- Implied 1X2 · Zimbru 52.5% · Draw 25.9% · Milsami Orhei 21.7%
- Bookmaker · Pinnacle
-
Aug 16, 2026 · 17:00 UTC Kickoff
-
FT Full-time result Zimbru win · 4–2
-
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: Warning
- Large market gap (15 pp)
- No strong statistical edge
- Market has already priced much of the edge
- Validation warning
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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Super Liga — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Sheriff Tiraspol | 13 | 8 | 4 | 1 | 28 |
| 2 | Zimbru | 13 | 8 | 2 | 3 | 26 |
| 3 | Petrocub | 13 | 7 | 3 | 3 | 24 |
| 4 | Dacia-Buiucani | 13 | 6 | 2 | 5 | 20 |
| 5 | Milsami Orhei | 13 | 4 | 5 | 4 | 17 |
| 6 | Politehnica UTM | 13 | 4 | 3 | 6 | 15 |
| 7 | Sireți | 13 | 0 | 7 | 6 | 7 |
| 8 | CSF Bălți | 13 | 1 | 2 | 10 | 5 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Sheriff Tiraspol | 13 | 32 | 10 | +22 | 28 |
| 2 | Zimbru | 13 | 27 | 12 | +15 | 26 |
| 3 | Petrocub | 13 | 24 | 13 | +11 | 24 |
| 4 | Politehnica UTM | 13 | 18 | 19 | -1 | 15 |
| 5 | Dacia-Buiucani | 13 | 17 | 16 | +1 | 20 |
| 6 | Milsami Orhei | 13 | 13 | 17 | -4 | 17 |
| 7 | CSF Bălți | 13 | 9 | 42 | -33 | 5 |
| 8 | Sireți | 13 | 8 | 19 | -11 | 7 |
