The model missed the final outcome (Guangdong Mingtu win 1–0).
The model had projected Shanghai Second at 39.0%, but the full-time result went the other way.
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 Over 2.5 Under 2.5 (1 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Shanghai Second Guangdong Mingtu ✖ Incorrect
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-0 ✔ Correct
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Guangdong Mingtu | 31.5% | 43.7% | -12.2 pp | Market Higher |
| Draw | 29.5% | 31.8% | -2.2 pp | Aligned |
| Shanghai Second | 39.0% | 24.5% | +14.4 pp | Model Edge |
The statistical model estimates Shanghai Second's win probability at 39.0%, compared with the closing market's implied probability of 24.5%, a difference of 14.4 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 result was Guangdong Mingtu win 1–0.
Market Assessment
The statistical fair estimate is materially higher than the market on Shanghai Second.
- The model may see a slower-scoring or closer matchup than the market.
- Monitor line movement before kickoff — not a betting recommendation.
Post Match Insights
What worked
- Exact score 1–0 fell within the model's highlighted bins
What failed
- Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
- Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (1 goals)
Market lesson
The closing market differed from the model on Shanghai Second by 14.4 percentage points (24.6% vs model 39.0%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 12, 2026 · 11:31 UTC Forecast generated
- Model 1X2 · Guangdong Mingtu 31.5% · Draw 29.5% · Shanghai Second 39.0%
- xG · Guangdong Mingtu 1.22 — Shanghai Second 1.38
-
Sep 12, 2026 · 11:04 UTC Opening odds snapshot PRE30
- 1X2 odds · Guangdong Mingtu 2.07 · Draw 2.85 · Shanghai Second 3.69
- Implied 1X2 · Guangdong Mingtu 43.7% · Draw 31.8% · Shanghai Second 24.5%
- Bookmaker · Pinnacle
-
Sep 12, 2026 · 11:31 UTC Closing snapshot recorded PRE1
- 1X2 odds · Guangdong Mingtu 2.07 · Draw 2.85 · Shanghai Second 3.69
- Implied 1X2 · Guangdong Mingtu 43.7% · Draw 31.8% · Shanghai Second 24.5%
- Bookmaker · Pinnacle
-
Sep 12, 2026 · 11:30 UTC Kickoff
-
FT Full-time result Guangdong Mingtu win · 1–0
-
FT Prediction missed 1X2 lean did not match 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 (14 pp)
- Statistical edge detected
- 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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