Statistics / Football / Slovenia. 1. SNL

Slovenia Slovenia 1. SNL Statistics (66)

Predictions

1. SNL 2025/26 Season Overview

07-18
100%
05-23
  • League goals trend: Average goals per match 3.07
  • Home win rate: About 49%
  • Away win rate: About 33%
  • BTTS rate (both teams to score): About 59%
  • Over 2.5 average hit rate: About 64%
  • Most attacking teams: Celje
  • Best defensive teams: Celje
May 17
15:30
Olimpija Ljubljana Olimpija Ljubljana
Radomlje Radomlje
80%
May 17
13:00
Mura Mura
Maribor Maribor
80%
May 16
18:15
Aluminij Aluminij
Primorje Primorje
48%
May 16
15:30
Celje Celje
Koper Koper
72%
May 10
13:00
Primorje Primorje
Mura Mura
55%
May 09
15:30
Koper Koper
Aluminij Aluminij
63%
May 09
13:00
Bravo Bravo
Radomlje Radomlje
80%
May 03
15:30
Radomlje Radomlje
Maribor Maribor
80%
May 03
13:00
63%
May 02
18:15
Celje Celje
Bravo Bravo
53%
May 02
15:30
Olimpija Ljubljana Olimpija Ljubljana
Primorje Primorje
46%
Apr 26
18:15
Bravo Bravo
Maribor Maribor
46%
Apr 26
15:30
Celje Celje
Aluminij Aluminij
27%
Apr 26
13:00
Primorje Primorje
Radomlje Radomlje
53%
Apr 25
18:15
Koper Koper
Olimpija Ljubljana Olimpija Ljubljana
53%
Apr 19
15:30
Aluminij Aluminij
Bravo Bravo
63%
Apr 19
13:00
55%
Apr 18
18:15
Maribor Maribor
Primorje Primorje
61%
Apr 18
15:30
Radomlje Radomlje
Koper Koper
42%
Apr 16
15:00
Aluminij Aluminij
Mura Mura
80%
Apr 15
16:30
Celje Celje
Olimpija Ljubljana Olimpija Ljubljana
61%
Apr 15
14:30
Bravo Bravo
Primorje Primorje
80%
Apr 14
16:00
Koper Koper
Maribor Maribor
61%
Apr 11
18:15
Radomlje Radomlje
Celje Celje
55%
Apr 11
15:30
72%
Apr 11
13:00
Olimpija Ljubljana Olimpija Ljubljana
Aluminij Aluminij
80%
Apr 10
15:30
Primorje Primorje
Koper Koper
32%
Apr 04
18:15
Celje Celje
Maribor Maribor
63%
Apr 04
15:30
Bravo Bravo
Koper Koper
82%
Apr 04
13:00
Mura Mura
Olimpija Ljubljana Olimpija Ljubljana
48%
Apr 03
15:30
Aluminij Aluminij
Radomlje Radomlje
72%
Mar 22
16:30
Celje Celje
Primorje Primorje
35%
Mar 21
19:15
Olimpija Ljubljana Olimpija Ljubljana
Bravo Bravo
72%
Mar 21
16:30
Mura Mura
Radomlje Radomlje
61%
Mar 20
16:30
Aluminij Aluminij
Maribor Maribor
82%
Mar 15
19:15
Primorje Primorje
Aluminij Aluminij
61%
Mar 15
16:30
Koper Koper
Celje Celje
63%
Mar 14
16:30
Maribor Maribor
Mura Mura
46%
Mar 14
14:00
Radomlje Radomlje
Olimpija Ljubljana Olimpija Ljubljana
72%
Mar 09
16:30
Radomlje Radomlje
Bravo Bravo
54%
Mar 08
16:30
Aluminij Aluminij
Koper Koper
41%
Mar 08
14:00
Olimpija Ljubljana Olimpija Ljubljana
Maribor Maribor
47%
Mar 07
16:30
Mura Mura
Primorje Primorje
62%
Mar 05
16:30
Aluminij Aluminij
Celje Celje
82%
Mar 01
16:30
Bravo Bravo
Celje Celje
62%
Mar 01
14:00
47%
Feb 28
16:30
Maribor Maribor
Radomlje Radomlje
70%
Feb 28
14:00
Primorje Primorje
Olimpija Ljubljana Olimpija Ljubljana
54%
Feb 22
14:00
Maribor Maribor
Bravo Bravo
62%
Feb 21
16:30
Radomlje Radomlje
Primorje Primorje
82%
Feb 21
14:00
Olimpija Ljubljana Olimpija Ljubljana
Koper Koper
41%
Feb 16
16:30
Bravo Bravo
Aluminij Aluminij
82%
Feb 15
16:30
Koper Koper
Radomlje Radomlje
70%
Feb 15
14:00
Primorje Primorje
Maribor Maribor
54%
Feb 14
14:00
36%
Feb 08
17:00
Maribor Maribor
Koper Koper
62%
Feb 08
14:00
Olimpija Ljubljana Olimpija Ljubljana
Celje Celje
62%
Feb 08
12:00
Mura Mura
Aluminij Aluminij
41%
Feb 07
14:00
Primorje Primorje
Bravo Bravo
53%
Feb 05
14:00
Aluminij Aluminij
Olimpija Ljubljana Olimpija Ljubljana
71%
Feb 04
16:30
Celje Celje
Radomlje Radomlje
62%
Feb 03
19:00
54%
Feb 03
16:30
Koper Koper
Primorje Primorje
82%
Feb 01
14:00
Maribor Maribor
Celje Celje
41%
Jan 31
16:30
Koper Koper
Bravo Bravo
23%
Jan 31
14:00
Olimpija Ljubljana Olimpija Ljubljana
Mura Mura
62%

Slovenia 1. SNL Betting & Prediction Guides

Want to understand how AI identifies value in Slovenia 1. SNL matches? Explore our strategy guides:

1. SNL Predictions FAQ

Q1: What is the probability structure and upset pattern in the Slovenia 1. SNL for the 2025/26 season?
Slovenia 1. SNL is structurally more volatile than typical top-flight competitions due to a significant 17% gap between home (48%) and away (31%) win rates. Unlike more balanced European leagues, the 2025/26 season shows a pronounced home-field bias that dictates the odds landscape. This creates an environment where mid-table hosts frequently upend higher-ranked visitors, as the home advantage often outweighs raw squad depth.

While the 48% home win rate suggests stability for favorites, the high-scoring nature of the league introduces variance. With 3.19 goals per game, matches rarely stagnate, meaning lead changes are common. Remember that probability does not equal certainty; long-term EV and disciplined risk management are essential when navigating these frequent momentum shifts.
Q2: How does the 2025/26 Slovenia 1. SNL compare to other leagues regarding Over/Under and BTTS structures?
The Slovenia 1. SNL stands out as an offensive outlier compared to most European leagues, defined by an aggressive 65% Over 2.5 rate. This isn't just a result of top-heavy blowouts but a league-wide commitment to transition play. The 2025/26 data reveals that 62% of matches see both teams score, indicating that even defensive-minded clubs struggle to maintain clean sheets in this high-tempo environment.

This statistical profile suggests that the "Under" is a rare bird in Slovenia, as the 3.19 goals per game average pushes lines higher than in more conservative competitions. Analysts should focus on team-specific defensive lapses rather than assuming a low-scoring grind. However, even with these strong trends, probability is never a guarantee; sustainable success requires prioritizing long-term value.
Q3: How does the 2025/26 statistical profile of the Slovenia 1. SNL shape its odds structure and analytical edges?
Because the Slovenia 1. SNL features a massive 65% Over 2.5 rate and 3.19 goals per game, the odds for goal-heavy outcomes are often heavily compressed. This forces a search for value in the 1X2 market, where the 17% home-away win gap creates inflated prices on away teams. While the 48% home win rate is dominant, the high BTTS frequency (62%) means home favorites rarely win comfortably, often leaving the door open for late-game volatility.

Analytical models find edges by identifying matches where the high scoring rate masks defensive improvements in specific squads. When the league average is so skewed toward goals, a rare defensive masterclass can yield significant returns against the grain. Always acknowledge that probability ≠ certainty; navigating these specific patterns requires a focus on long-term EV and professional risk management.
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