AI correctly predicted the FK Zalgiris Vilnius win.
The match finished 3–2, 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 (5 goals) ✖ Incorrect
- Both Teams To Score BTTS No Yes ✖ Incorrect
- 1X2 FK Zalgiris Vilnius FK Zalgiris Vilnius ✔ Correct
- Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-2 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| FK Zalgiris Vilnius | 36.1% | 28.2% | +7.9 pp | Model Higher |
| Draw | 29.6% | 27.0% | +2.7 pp | Aligned |
| Kauno Žalgiris | 34.2% | 44.8% | -10.6 pp | Market Higher |
The closing market estimates Kauno Žalgiris's win probability at 44.8%, compared with the model's estimate of 34.2%, a difference of 10.6 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 model's directional lean matched the result (FK Zalgiris Vilnius win 3–2).
Market Assessment
The market is materially more optimistic about Kauno Žalgiris 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) — 5 goals materialised
What failed
- Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (5 goals)
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced FK Zalgiris Vilnius higher (46.7% vs model 36.1%, 10.6 pp), but the model's lean was validated (FK Zalgiris Vilnius win 3–2).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 16, 2026 · 15:44 UTC Forecast generated
- Model 1X2 · FK Zalgiris Vilnius 36.1% · Draw 29.7% · Kauno Žalgiris 34.2%
- xG · FK Zalgiris Vilnius 1.32 — Kauno Žalgiris 1.28
-
Sep 16, 2026 · 15:14 UTC Opening odds snapshot PRE30
- 1X2 odds · FK Zalgiris Vilnius 3.29 · Draw 3.44 · Kauno Žalgiris 2.07
- Implied 1X2 · FK Zalgiris Vilnius 28.2% · Draw 27.0% · Kauno Žalgiris 44.8%
- Bookmaker · Pinnacle
-
Sep 16, 2026 · 15:44 UTC Closing snapshot recorded PRE1
- 1X2 odds · FK Zalgiris Vilnius 3.29 · Draw 3.44 · Kauno Žalgiris 2.07
- Implied 1X2 · FK Zalgiris Vilnius 28.2% · Draw 27.0% · Kauno Žalgiris 44.8%
- Bookmaker · Pinnacle
-
Sep 16, 2026 · 15:45 UTC Kickoff
-
FT Full-time result FK Zalgiris Vilnius win · 3–2
-
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 (11 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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A Lyga — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Kauno Žalgiris | 28 | 14 | 9 | 5 | 51 |
| 2 | Suduva Marijampole | 28 | 13 | 11 | 4 | 50 |
| 3 | TransINVEST Vilnius | 28 | 13 | 6 | 9 | 45 |
| 4 | FK Zalgiris Vilnius | 28 | 13 | 5 | 10 | 44 |
| 5 | Banga | 28 | 11 | 8 | 9 | 41 |
| 6 | Džiugas Telšiai | 28 | 10 | 8 | 10 | 38 |
| 7 | Panevėžys | 28 | 9 | 5 | 14 | 32 |
| 8 | Hegelmann Litauen | 29 | 4 | 14 | 11 | 26 |
| 9 | Šiauliai | 29 | 3 | 8 | 18 | 17 |
| 10 | FK Trakai | 0 | 0 | 0 | 0 | 0 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Kauno Žalgiris | 28 | 56 | 20 | +36 | 51 |
| 2 | TransINVEST Vilnius | 28 | 43 | 35 | +8 | 45 |
| 3 | FK Zalgiris Vilnius | 28 | 41 | 34 | +7 | 44 |
| 4 | Suduva Marijampole | 28 | 39 | 25 | +14 | 50 |
| 5 | Džiugas Telšiai | 28 | 36 | 40 | -4 | 38 |
| 6 | Banga | 28 | 32 | 28 | +4 | 41 |
| 7 | Hegelmann Litauen | 29 | 31 | 48 | -17 | 26 |
| 8 | Panevėžys | 28 | 29 | 43 | -14 | 32 |
| 9 | Šiauliai | 29 | 24 | 58 | -34 | 17 |
| 10 | FK Trakai | 0 | 0 | 0 | 0 | 0 |