AI correctly predicted the Lyra-Lierse Berlaar 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 Lyra-Lierse Berlaar Lyra-Lierse Berlaar ✔ 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 |
|---|---|---|---|---|
| Lyra-Lierse Berlaar | 36.1% | 32.8% | +3.3 pp | Aligned |
| Draw | 29.6% | 26.6% | +3.0 pp | Aligned |
| Heist | 34.2% | 40.5% | -6.3 pp | Market Higher |
The closing market estimates Heist's win probability at 40.5%, compared with the model's estimate of 34.2%, a difference of 6.3 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: PRE5.
After full time, the model's directional lean matched the result (Lyra-Lierse Berlaar win 3–2).
Market Assessment
The market and model broadly agree on Heist. 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
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 Lyra-Lierse Berlaar higher (42.4% vs model 36.1%, 6.3 pp), but the model's lean was validated (Lyra-Lierse Berlaar win 3–2).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 19, 2026 · 17:56 UTC Forecast generated
- Model 1X2 · Lyra-Lierse Berlaar 36.1% · Draw 29.7% · Heist 34.2%
- xG · Lyra-Lierse Berlaar 1.32 — Heist 1.28
-
Sep 19, 2026 · 17:32 UTC Opening odds snapshot PRE30
- 1X2 odds · Lyra-Lierse Berlaar 2.79 · Draw 3.44 · Heist 2.26
- Implied 1X2 · Lyra-Lierse Berlaar 32.8% · Draw 26.6% · Heist 40.5%
- Bookmaker · Pinnacle
-
Sep 19, 2026 · 17:56 UTC Closing snapshot recorded PRE5
- 1X2 odds · Lyra-Lierse Berlaar 2.79 · Draw 3.44 · Heist 2.26
- Implied 1X2 · Lyra-Lierse Berlaar 32.8% · Draw 26.6% · Heist 40.5%
- Bookmaker · Pinnacle
-
Sep 19, 2026 · 18:00 UTC Kickoff
-
FT Full-time result Lyra-Lierse Berlaar 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: 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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First Amateur Division — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Meux | 6 | 5 | 0 | 1 | 15 |
| 2 | RWDM | 5 | 5 | 0 | 0 | 15 |
| 3 | Tubize | 6 | 3 | 2 | 1 | 11 |
| 4 | Rochefort | 5 | 3 | 1 | 1 | 10 |
| 5 | Union Saint-Gilloise II | 6 | 2 | 2 | 2 | 8 |
| 6 | Albert Quévy-Mons | 5 | 2 | 1 | 2 | 7 |
| 7 | Onhaye | 6 | 2 | 0 | 4 | 6 |
| 8 | Sporting Charleroi II | 5 | 1 | 2 | 2 | 5 |
| 9 | Standard Liège II | 5 | 1 | 1 | 3 | 4 |
| 10 | Habay-la-Neuve | 5 | 1 | 1 | 3 | 4 |
| 11 | Olympic Charleroi | 5 | 1 | 1 | 3 | 4 |
| 12 | Flénu | 5 | 0 | 1 | 4 | 1 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Meux | 6 | 14 | 4 | +10 | 15 |
| 2 | Rochefort | 5 | 12 | 6 | +6 | 10 |
| 3 | Albert Quévy-Mons | 5 | 10 | 10 | 0 | 7 |
| 4 | Tubize | 6 | 9 | 8 | +1 | 11 |
| 5 | RWDM | 5 | 8 | 1 | +7 | 15 |
| 6 | Onhaye | 6 | 7 | 12 | -5 | 6 |
| 7 | Union Saint-Gilloise II | 6 | 6 | 6 | 0 | 8 |
| 8 | Standard Liège II | 5 | 5 | 3 | +2 | 4 |
| 9 | Habay-la-Neuve | 5 | 5 | 9 | -4 | 4 |
| 10 | Flénu | 5 | 5 | 13 | -8 | 1 |
| 11 | Sporting Charleroi II | 5 | 4 | 5 | -1 | 5 |
| 12 | Olympic Charleroi | 5 | 4 | 12 | -8 | 4 |
