Statistics / Football / Slovenia. 1. SNL / Primorje vs Mura

Primorje vs Mura Statistics & Analysis

May 10, 2026 - 13:00
0 1.45
2 1.25
xG Accuracy: 55%
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

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

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: 1. SNL
  • Fixture: Primorje vs Mura
  • Kickoff: 2026-05-09 15:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Primorje 1.45 — Mura 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 68.4% · Implied: 41.9% · Probability edge: +26.6 pts · Est. EV: +53.9%
  • BTTS (model): Yes 31.6% · No 68.4%
  • Correct score (top bin): 1-1 (11.7%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

1X2 can look balanced even when side markets show clearer structure.

Best Bet + Reason

Primary angle highlighted on the page: BTTS No.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

Only one modest +EV edge is highlighted here; size cautiously and re-check if odds move.

FAQ

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Risk Factors

  • 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%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

May 17, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
1. SNL 1. SNLStandings
# TEAM MP W D L PTS
1 Celje 33 22 5 6 71
2 Koper 34 20 7 7 67
3 Bravo 33 18 5 10 59
4 Olimpija Ljubljana 32 15 7 10 52
5 Maribor 32 14 8 10 50
6 Radomlje 32 12 6 14 42
7 Aluminij 33 10 6 17 36
8 Mura 32 7 7 18 28
9 Primorje 33 6 4 23 22
10 NK Domzale 18 3 3 12 12
# TEAM MP GS GC +/- PTS
1 Celje 33 81 32 +49 71
2 Koper 34 71 43 +28 67
3 Bravo 33 60 50 +10 59
4 Maribor 32 53 41 +12 50
5 Olimpija Ljubljana 32 47 37 +10 52
6 Radomlje 32 46 59 -13 42
7 Aluminij 33 42 58 -16 36
8 Mura 32 31 51 -20 28
9 Primorje 33 31 70 -39 22
10 NK Domzale 18 17 38 -21 12