Statistics / Football / Malaysia. Super League / Selangor vs Pdrm

Selangor vs Pdrm Statistics & Analysis

Selangor Selangor
May 17, 2026 - 12:15
6 1.45
0 1.25
xG Accuracy: 20%
Pdrm Pdrm
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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 Over 2.5 (6 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Selangor Selangor ✔ Correct
  • Correct Score Insights 2-0, 3-0, 2-1, 3-1, 1-0 6-0 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 23:07 UTC Snapshot ID: dp-1517751

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Selangor win · Selangor 6–0 Pdrm
Prediction ✔ Correct
Decision Grade A

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Super League
  • Fixture: Selangor vs Pdrm
  • Kickoff: 2026-05-16 13:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Selangor 1.45 — Pdrm 1.25 (total xG ≈ 2.7)
  • 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 Over 2.5 (Under 2.5 31.2% · Over 2.5 68.8%); BTTS No (Yes 44.2% · No 55.8%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 44.2% · No 55.8%
  • Correct score (top bin): 2-0 (10.9%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

Historical Recommendation

Historical Decision: AI–Market Conflict - No Primary Bet

Outcome: Validated — Pre-match lean validated against 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 16, 2026 (UTC)

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Back to Statistics
Super League Super League — Standings
# TEAM MP W D L PTS
1 Johor Darul Takzim FC 24 23 1 0 70
2 Kuching FA 24 16 5 3 53
3 Selangor 24 16 4 4 52
4 Kuala Lumpur FA 24 12 7 5 43
5 Terengganu 24 10 6 8 36
6 Imigresen 24 9 5 10 32
7 Negeri Sembilan 24 6 11 7 29
8 Penang 24 6 7 11 25
9 Sabah FA 24 5 8 11 23
10 DPMM FC 24 6 5 13 23
11 Melaka 24 4 7 13 19
12 Kelantan United 24 4 3 17 15
13 Pdrm 24 2 5 17 11
# TEAM MP GS GC +/- PTS
1 Johor Darul Takzim FC 24 117 10 +107 70
2 Selangor 24 59 20 +39 52
3 Kuching FA 24 45 14 +31 53
4 Kuala Lumpur FA 24 40 29 +11 43
5 Terengganu 24 39 34 +5 36
6 Negeri Sembilan 24 39 35 +4 29
7 Imigresen 24 38 43 -5 32
8 DPMM FC 24 30 57 -27 23
9 Sabah FA 24 29 44 -15 23
10 Penang 24 26 41 -15 25
11 Melaka 24 18 45 -27 19
12 Kelantan United 24 17 63 -46 15
13 Pdrm 24 17 79 -62 11