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

Radomlje vs Mura Statistics & Analysis

May 22, 2026 - 18:00
3 1.45
2 1.25
xG Accuracy: 53%
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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 Under 2.5 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Radomlje Radomlje ✔ Correct
  • Correct Score Insights 1-1, 2-1, 1-0, 1-2, 0-1 3-2 ✖ 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: Radomlje vs Mura
  • Kickoff: 2026-05-23 15:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Radomlje 1.45 — Mura 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 55.4% · Implied: 38.7% · Probability edge: +16.7 pts · Est. EV: +38.5%
  • BTTS (model): Yes 44.6% · No 55.4%
  • Correct score (top bin): 1-1 (11.6%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Correct score remains high-variance even when a line is most likely on paper.

Best Bet + Reason

The engine’s headline primary is: 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).

Edges shrink quickly if prices move; always re-check the number on your book.

FAQ

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

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.

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.

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

June 08, 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 34 23 5 6 74
2 Koper 34 20 7 7 67
3 Bravo 34 19 5 10 62
4 Olimpija Ljubljana 34 16 7 11 55
5 Maribor 34 15 8 11 53
6 Radomlje 34 13 6 15 45
7 Aluminij 34 10 6 18 36
8 Mura 34 8 7 19 31
9 Primorje 34 6 4 24 22
10 NK Domzale 18 3 3 12 12
# TEAM MP GS GC +/- PTS
1 Celje 34 85 32 +53 74
2 Koper 34 71 43 +28 67
3 Bravo 34 62 51 +11 62
4 Maribor 34 57 43 +14 53
5 Olimpija Ljubljana 34 50 40 +10 55
6 Radomlje 34 50 63 -13 45
7 Aluminij 34 42 61 -19 36
8 Mura 34 35 55 -20 31
9 Primorje 34 31 74 -43 22
10 NK Domzale 18 17 38 -21 12