· Liga I
CFR Cluj
ATT
6/10
DEF
7/10
0:0
U. Cluj
6/10
ATT
6/10
DEF
Scheduled· Thu 8 Oct · 17:30
Best Pick
Under 2.5
53%
Correct Score
Top
1-0
12.1%
8.24
Top
1-1
12%
8.32
2-0
9.5%
10.49
2-1
9.4%
10.60
0-0
7.7%
12.95
0-1
7.6%
13.08
1-2
5.9%
16.82
3-0
5%
20.03
151%
1.97TOP
X25%
3.95
224%
4.19
1X76%
X249%
1275%
Probable XI4-4-2
Moreira
Radu
Țîrlea
Abeid
Kresic
Nalić
Ziblim
Păun
Fică
Ferenți
Cordea
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
CFR Cluj42 players
54.9/ 99Average
Top Rated
1Nicolae SulaFWD83
2Karlo MuharMID79
3Andrei CordeaFWD77
U. Cluj36 players
47.0/ 99Average
Top Rated
1Andrej FabryMID75
2Andrei CoubișDEF67
3Florent PouloloDEF67
CFR Cluj64
PlayerOverall RatingImpactAggressionDiscipline
Nicolae Sula83994550
Karlo Muhar79748567
Andrei Cordea77773491
Sergiu Buş72742591
Aly Abeid70565187
Viktor Kun70548669
Léo Bolgado69595279
Francisco Barrios67646661
Christopher Braun66488665
Alin Fică64584971
Ovidiu Perianu64386291
Meriton Korenica64516791
A. Nalić61605161
U. Cluj53
PlayerOverall RatingImpactAggressionDiscipline
Andrej Fabry75605191
Andrei Coubiș67782976
Florent Poulolo67704269
Dorin Codrea67538967
Iulian Cristea59573773
Taiwo Olakunle58624550
Edvinas Gertmonas5759950
Adams Friday56236491
Miguel Silva55395471
Jovo Lukic54564653
Marius Ștefănescu54616733
Neofytos Michail52523950
Elio Capradossi52692449
Player Rankings
Snipers
Top goal threats
1
Nicolae SulaCFR Cluj
99
2
Andrei CordeaCFR Cluj
77
3
Sergiu BuşCFR Cluj
74
4
Taiwo OlakunleU. Cluj
62
5
Marius ȘtefănescuU. Cluj
61
Wall
Top defenders
1
Marian HujaCFR Cluj
90
2
Andrei CoubișU. Cluj
78
3
Florent PouloloU. Cluj
70
4
Elio CapradossiU. Cluj
69
5
Jonathan CisséU. Cluj
69
Control
Top playmakers
1
Karlo MuharCFR Cluj
74
2
Francisco BarriosCFR Cluj
64
3
Ovidiu BicU. Cluj
62
4
A. NalićCFR Cluj
60
5
Andrej FabryU. Cluj
60
Bad Boys
Most likely to get booked
1
Marian HujaCFR Cluj
1
2
Dan NistorU. Cluj
1
3
Pedro PinhoU. Cluj
3
4
Alessandro MurgiaU. Cluj
9
5
Oucasse MendyU. Cluj
11
Power Rankings
Strongest overall
1
Nicolae SulaCFR Cluj
83
2
Karlo MuharCFR Cluj
79
3
Andrei CordeaCFR Cluj
77
4
Andrej FabryU. Cluj
75
5
Sergiu BuşCFR Cluj
72

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for CFR Cluj vs U. Cluj based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.

The Bet Builder combines multiple selections from the CFR Cluj vs U. Cluj match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.

xG (expected goals) measures the quality of scoring chances. If CFR Cluj has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).

Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for CFR Cluj vs U. Cluj without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.

A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives CFR Cluj a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.

AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.

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