AI correctly predicted the Paide win.
The match finished 4–1, 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 (5 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Paide Paide ✔ Correct
- Correct Score Insights 1-0, 1-1, 2-0, 2-1, 0-0 4-1 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Paide | 50.3% | 58.0% | -7.7 pp | Market Higher |
| Draw | 28.0% | 21.6% | +6.4 pp | Model Higher |
| Nõmme United | 21.7% | 20.4% | +1.4 pp | Aligned |
The closing market estimates Paide's win probability at 58.0%, compared with the model's estimate of 50.3%, a difference of 7.7 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 (Paide win 4–1).
Market Assessment
The market and model broadly agree on Paide. 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) — 5 goals materialised
- Paide attacking xG significantly stronger (1.61 vs 0.99)
- 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 (5 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 Paide higher (58.0% vs model 50.3%, 7.7 pp), but the model's lean was validated (Paide win 4–1).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Aug 23, 2026 · 14:00 UTC Forecast generated
- Model 1X2 · Paide 50.2% · Draw 28.0% · Nõmme United 21.7%
- xG · Paide 1.61 — Nõmme United 0.99
-
Aug 23, 2026 · 13:31 UTC Opening odds snapshot PRE30
- 1X2 odds · Paide 1.60 · Draw 4.30 · Nõmme United 4.56
- Implied 1X2 · Paide 58.0% · Draw 21.6% · Nõmme United 20.4%
- Bookmaker · Pinnacle
-
Aug 23, 2026 · 14:00 UTC Closing snapshot recorded PRE1
- 1X2 odds · Paide 1.60 · Draw 4.30 · Nõmme United 4.56
- Implied 1X2 · Paide 58.0% · Draw 21.6% · Nõmme United 20.4%
- Bookmaker · Pinnacle
-
Aug 23, 2026 · 14:00 UTC Kickoff
-
FT Full-time result Paide win · 4–1
-
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
- Moderate model lean
- 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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Meistriliiga — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | FC Levadia Tallinn | 29 | 22 | 6 | 1 | 72 |
| 2 | Flora Tallinn | 29 | 18 | 1 | 10 | 55 |
| 3 | Paide | 29 | 15 | 6 | 8 | 51 |
| 4 | Kalju Nomme | 29 | 15 | 5 | 9 | 50 |
| 5 | Tammeka | 29 | 14 | 2 | 13 | 44 |
| 6 | Laagri | 29 | 11 | 2 | 16 | 35 |
| 7 | Vaprus | 29 | 10 | 4 | 15 | 34 |
| 8 | Kuressaare | 29 | 8 | 5 | 16 | 29 |
| 9 | Nõmme United | 29 | 9 | 1 | 19 | 28 |
| 10 | Trans Narva | 29 | 5 | 4 | 20 | 19 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | FC Levadia Tallinn | 29 | 81 | 21 | +60 | 72 |
| 2 | Flora Tallinn | 29 | 59 | 39 | +20 | 55 |
| 3 | Kalju Nomme | 29 | 52 | 27 | +25 | 50 |
| 4 | Paide | 29 | 48 | 36 | +12 | 51 |
| 5 | Nõmme United | 29 | 47 | 68 | -21 | 28 |
| 6 | Laagri | 29 | 40 | 47 | -7 | 35 |
| 7 | Vaprus | 29 | 39 | 57 | -18 | 34 |
| 8 | Tammeka | 29 | 37 | 47 | -10 | 44 |
| 9 | Kuressaare | 29 | 31 | 49 | -18 | 29 |
| 10 | Trans Narva | 29 | 22 | 65 | -43 | 19 |
