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

Dangkor Senchey vs Svay Rieng Statistics & Analysis

Dangkor Senchey Dangkor Senchey
Sep 20, 2026 - 11:00
1 1.07
1 1.53
xG Accuracy: 85%
Svay Rieng Svay Rieng
Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

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 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

Validation Report

Immutable Snapshot

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

Closing Odds 1.27
AI Fair Odds —
CLV +0.0%
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%

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Dangkor Senchey (1X2), Draw (1X2) meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Draw (1X2) by about 11.6 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Dangkor Senchey (1X2) 24.9 13.5 +11.5
Draw (1X2) 28.7 17.2 +11.6
Svay Rieng (1X2) 46.3 69.3 -23.0
What this means

In plain terms: the model lands near 28.7% on Draw (1X2), while the closing snapshot implied about 17.2%. The difference — about 11.6 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Pinnacle

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
Dangkor Senchey (1X2) 6.54 6.54 0.0
Draw (1X2) 5.12 5.12 0.0
Svay Rieng (1X2) 1.27 1.27 0.0

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: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • 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 - No Primary Bet

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 29, 2026 (UTC)

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Back to Statistics
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