Statistics / Football / Romania. Liga I

Romania Romania Liga I Statistics (34)

Predictions

Liga I 2025/26 Season Overview

07-12
33%
03-07
  • League goals trend: Average goals per match 2.51
  • Home win rate: About 45%
  • Away win rate: About 29%
  • BTTS rate (both teams to score): About 51%
  • Over 2.5 average hit rate: About 46%
  • Most attacking teams: Universitatea Craiova
  • Best defensive teams: Universitatea Craiova
Romania Romania. Liga I (34)
xG Accuracy
May 18
17:30
AFC Hermannstadt AFC Hermannstadt
2 0.97 0 1.91
FCSB FCSB
45%
May 18
17:30
Farul Constanta Farul Constanta
0 1.49 1 1.16
Metaloglobus Metaloglobus
64%
May 18
17:30
Petrolul Ploiesti Petrolul Ploiesti
1 1.38 5 1.34
Oţelul Oţelul
33%
May 18
17:30
Unirea Slobozia Unirea Slobozia
0 1.33 1 1.23
Uta Arad Uta Arad
65%
May 17
17:30
Universitatea Craiova Universitatea Craiova
5 1.58 0 0.78
Universitatea Cluj Universitatea Cluj
32%
May 16
18:00
Dinamo Bucuresti Dinamo Bucuresti
0 1.60 0 0.97
CFR 1907 Cluj CFR 1907 Cluj
49%
May 16
15:30
Csikszereda Csikszereda
2 0.90 0 1.81
FC Botosani FC Botosani
45%
May 15
17:30
Arges Pitesti Arges Pitesti
2 0.85 2 1.11
Rapid Rapid
57%
May 11
18:00
FCSB FCSB
0 2.81 0 1.02
Unirea Slobozia Unirea Slobozia
35%
May 11
15:00
Metaloglobus Metaloglobus
2 1.13 2 1.24
AFC Hermannstadt AFC Hermannstadt
64%
May 10
16:00
Dinamo Bucuresti Dinamo Bucuresti
2 1.28 1 0.75
Arges Pitesti Arges Pitesti
77%
May 10
13:00
FC Botosani FC Botosani
1 1.54 1 0.93
Petrolul Ploiesti Petrolul Ploiesti
85%
May 09
18:00
Universitatea Cluj Universitatea Cluj
1 1.05 0 1.37
Rapid Rapid
68%
May 09
15:00
Oţelul Oţelul
3 1.82 2 1.24
Farul Constanta Farul Constanta
59%
May 08
18:00
CFR 1907 Cluj CFR 1907 Cluj
0 0.89 0 1.41
Universitatea Craiova Universitatea Craiova
53%
May 08
15:00
Uta Arad Uta Arad
1 1.71 0 0.71
Csikszereda Csikszereda
68%
May 04
17:30
Rapid Rapid
1 1.70 2 0.86
CFR 1907 Cluj CFR 1907 Cluj
60%
May 04
14:30
Unirea Slobozia Unirea Slobozia
2 1.42 2 1.15
AFC Hermannstadt AFC Hermannstadt
68%
May 03
18:00
Universitatea Craiova Universitatea Craiova
2 1.31 1 0.83
Dinamo Bucuresti Dinamo Bucuresti
79%
May 03
15:15
Petrolul Ploiesti Petrolul Ploiesti
1 1.05 1 1.03
Uta Arad Uta Arad
98%
May 02
17:30
Universitatea Cluj Universitatea Cluj
1 1.15 0 0.89
Arges Pitesti Arges Pitesti
75%
May 02
14:30
Farul Constanta Farul Constanta
1 1.20 1 1.48
FC Botosani FC Botosani
83%
May 02
12:00
Oţelul Oţelul
2 2.06 2 1.16
Metaloglobus Metaloglobus
78%
May 01
17:30
Csikszereda Csikszereda
1 0.77 0 2.99
FCSB FCSB
41%
Apr 27
17:30
Arges Pitesti Arges Pitesti
0 0.85 1 1.14
Universitatea Craiova Universitatea Craiova
76%
Apr 27
14:30
Metaloglobus Metaloglobus
1 1.27 1 1.44
Unirea Slobozia Unirea Slobozia
82%
Apr 26
18:00
Dinamo Bucuresti Dinamo Bucuresti
3 1.17 1 1.09
Rapid Rapid
59%
Apr 26
11:00
Uta Arad Uta Arad
0 1.32 0 1.05
Farul Constanta Farul Constanta
52%
Apr 25
17:30
CFR 1907 Cluj CFR 1907 Cluj
1 1.32 0 1.21
Universitatea Cluj Universitatea Cluj
66%
Apr 25
12:00
FC Botosani FC Botosani
1 1.67 1 1.27
Oţelul Oţelul
77%
Apr 24
17:30
FCSB FCSB
3 2.10 1 0.87
Petrolul Ploiesti Petrolul Ploiesti
75%
Apr 24
14:30
AFC Hermannstadt AFC Hermannstadt
0 1.55 0 0.85
Csikszereda Csikszereda
52%
Apr 20
17:30
Farul Constanta Farul Constanta
2 0.77 3 2.30
FCSB FCSB
59%
Apr 20
14:30
FC Botosani FC Botosani
3 2.37 2 0.88
Metaloglobus Metaloglobus
62%

Romania Liga I Betting & Prediction Guides

Want to understand how AI identifies value in Romania Liga I matches? Explore our strategy guides:

Liga I Predictions FAQ

Q1: What defines the probability structure and upset potential in Romania Liga I for the 2025/26 season? ▼
Romania Liga I is structurally more volatile than typical top-flight competitions, characterized by a significant 14% gap between the 44% home win rate and the 30% away win rate. While many European leagues see a narrowing home advantage, the Romanian top tier remains a fortress-heavy environment where visitors struggle to dominate. This creates a landscape where favorites often falter on the road, making the high frequency of draws a critical factor for any analyst to weigh when assessing match outcomes.

Because probability never equates to certainty, identifying value requires looking beyond surface-level rankings. The league's tendency toward home dominance means that even mid-table sides often hold their ground against elite opposition. Success depends on managing risk and understanding that long-term EV is found by spotting when the odds overstate a traveling favorite’s chances. In this climate, a disciplined approach to bankroll management is essential to navigate the inherent unpredictability.
Q2: How do the BTTS and Over/Under 2.5 metrics characterize the goal-scoring environment in Romania Liga I for 2025/26? ▼
Romania Liga I is structurally lower-scoring than most Western European leagues, averaging 2.53 goals per game. Unlike high-octane divisions, this league leans toward tactical caution, evidenced by an Over 2.5 rate of just 47%. This suggests that matches are more likely to be decided by a single moment of brilliance or a defensive error rather than a flurry of scoring. The 51% BTTS rate further highlights a balanced but often stagnant offensive output, where clean sheets are nearly as common as both teams scoring.

This statistical profile forces analysts to prioritize defensive stability over raw attacking talent. When nearly 53% of matches stay under the 2.5-goal threshold, the margin for error in goal-line predictions is razor-thin. Analysts must account for this defensive identity while remembering that probability is not a guarantee. Long-term success requires a focus on team-specific defensive metrics and a rigorous risk management strategy to handle the league’s penchant for tight, low-scoring encounters.
Q3: How does the specific data profile of Romania Liga I in 2025/26 shape the odds structure and where can analytical models find edges? ▼
Because Romania Liga I features a 51% BTTS rate and a 47% Over 2.5 rate, the goal markets are remarkably balanced, creating tight lines where small edges exist in team-specific matchups. This parity means that minor tactical shifts can significantly move the true likelihood of a high-scoring game. With 2.53 goals per game, the odds remain centered, allowing models to find opportunities when the public overreacts to a single high-scoring outlier in a league that generally favors defensive structure.

The 14% home-away win gap also dictates the odds landscape, as the 44% home win rate often inflates away odds beyond their true probability. Analytical models can find edges by identifying robust traveling sides that the market undervalues due to the league’s general home bias. However, since probability does not ensure outcomes, maintaining a focus on long-term EV and strict risk management is vital. Navigating these compressed odds requires a deep understanding of how specific stadium atmospheres impact performance.
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