Predictions / Football / Cambodia. C-League / Dangkor Senchey vs Svay Rieng

Prediction Audit: Dangkor Senchey vs Svay Rieng Prediction, Odds & AI Betting Tips

Sep 20, 2026 - 11:00
1 1.07
1 1.53
xG Accuracy: 85%

The model missed the final outcome (Draw 1–1).

The model had projected Svay Rieng at 46.3%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Svay Rieng Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-2, 0-2, 1-0 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Svay Rieng higher than the statistical model.

Largest probability gap: Svay Rieng -23.0 pp

Outcome Model Closing Market Difference Signal
Dangkor Senchey 25.0% 13.5% +11.5 pp Model Edge
Draw 28.7% 17.2% +11.5 pp Model Edge
Svay Rieng 46.3% 69.3% -23.0 pp Market Higher

The closing market estimates Svay Rieng's win probability at 69.3%, compared with the model's estimate of 46.3%, a difference of 23.0 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 result was Draw 1–1.

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–1 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • 1X2: model leaned Svay Rieng; match finished Draw

Market lesson

The closing market differed from the model on Svay Rieng by 23.0 percentage points (69.3% vs model 46.3%) — in this case the market view proved closer.

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Sep 20, 2026 · 11:02 UTC Forecast generated
    • Model 1X2 · Dangkor Senchey 24.9% · Draw 28.7% · Svay Rieng 46.3%
    • xG · Dangkor Senchey 1.07 — Svay Rieng 1.53
  2. Sep 20, 2026 · 10:32 UTC Opening odds snapshot PRE30
    • 1X2 odds · Dangkor Senchey 6.54 · Draw 5.12 · Svay Rieng 1.27
    • Implied 1X2 · Dangkor Senchey 13.5% · Draw 17.2% · Svay Rieng 69.3%
    • Bookmaker · Pinnacle
  3. Sep 20, 2026 · 11:02 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Dangkor Senchey 6.54 · Draw 5.12 · Svay Rieng 1.27
    • Implied 1X2 · Dangkor Senchey 13.5% · Draw 17.2% · Svay Rieng 69.3%
    • Bookmaker · Pinnacle
  4. Sep 20, 2026 · 11:00 UTC Kickoff
  5. FT Full-time result Draw · 1–1
  6. FT Prediction missed 1X2 lean did not match full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 51/100 · Moderate
  • Validation: Warning
  • Large market gap (23 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 14, 2026 · 01:12 UTC Snapshot ID: dp-8663669

Closing Odds 1.27
AI Fair Odds —
CLV Pending
Final Result Draw · Dangkor Senchey 1–1 Svay Rieng
Prediction ✖ Missed
Decision Grade F

Model 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.

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: C-League
  • Fixture: Dangkor Senchey vs Svay Rieng
  • Kickoff: 2026-09-20 11:00:00
  • 1X2 (model): Home 24.9% · Draw 28.7% · Away 46.3%
  • xG (showing): Dangkor Senchey 1.07 — Svay Rieng 1.53 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.1%, still below the +2.0% minimum for a headline / default stake (no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS No (Yes 53.0% · No 46.9%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes 53.0% · No 46.9%
  • Correct score (top bin): 1-1 (12.2%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: Wait

Outcome: Missed — Pre-match 1X2 lean did not match the full-time result.

Risk Factors Considered Before Kickoff

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Last Updated

September 30, 2026 (UTC)

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C-League C-League — Standings
# TEAM MP W D L PTS
1 Visakha 3 3 0 0 9
2 Svay Rieng 3 2 1 0 7
3 NagaWorld 3 2 1 0 7
4 Dangkor Senchey 3 1 2 0 5
5 Kompong Dewa 3 1 1 1 4
6 Kirivong Sok Sen Chey 3 1 0 2 3
7 Phnom Penh Crown 2 0 2 0 2
8 Angkor Tiger 3 0 2 1 2
9 Boeung Ket 2 0 1 1 1
10 Life Sihanoukville 2 0 0 2 0
11 National Defense 3 0 0 3 0
# TEAM MP GS GC +/- PTS
1 Visakha 3 10 2 +8 9
2 Dangkor Senchey 3 10 4 +6 5
3 Svay Rieng 3 8 1 +7 7
4 NagaWorld 3 8 6 +2 7
5 National Defense 3 5 15 -10 0
6 Phnom Penh Crown 2 4 4 0 2
7 Boeung Ket 2 4 5 -1 1
8 Angkor Tiger 3 3 4 -1 2
9 Kompong Dewa 3 2 2 0 4
10 Kirivong Sok Sen Chey 3 2 10 -8 3
11 Life Sihanoukville 2 0 3 -3 0