· UEFA U21 Championship Qualification
Montenegro U21
ATT
5/10
DEF
4/10
vs
Armenia U21
5/10
ATT
3/10
DEF
Scheduled· Mon 5 Oct · 14:30
Best Pick
BTTS
60%
Correct Score
Top
1-1
10.6%
9.42
Top
2-1
9.6%
10.47
1-0
8.3%
11.98
2-0
7.5%
13.32
1-2
6.8%
14.81
2-2
6.1%
16.46
0-1
5.9%
16.94
3-1
5.7%
17.46
150%
2.01TOP
X23%
4.33
227%
3.69
1X73%
X250%
1277%
Probable XI4-4-2
Radanović
Djuric
Vukotić
Tomašević
Damjanović
Zekovic
Ćetković
Bajovic
Bulatovic
Kostic
Mrvaljević
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Montenegro U2123 players
45.6/ 99Average
Top Rated
1Andrej KosticFWD74
2Damjan DakicDEF72
3Dragan MiranovićMID69
Armenia U2123 players
43.3/ 99Average
Top Rated
1Artur GharibyanFWD57
2Mher TarloyanDEF56
3Karlen HovhannisyanMID55
Montenegro U2162
PlayerOverall RatingImpactAggressionDiscipline
Andrej Kostic74739756
Damjan Dakic72855850
Dragan Miranović69597961
Nemanja Carević55624550
Milan Roganovic50524550
Balša Vukotić48454952
Balša Radanović46453450
Andrija Bulatovic46454550
Kristijan Radunović46454550
Nenad Krivokapić46454550
Stefan Radojevic46454550
Velimir Ljutica45454550
Stefan Golubović45454550
Armenia U2138
PlayerOverall RatingImpactAggressionDiscipline
Artur Gharibyan57652850
Mher Tarloyan56693550
Karlen Hovhannisyan55516950
Edik Vardanyan55575350
Gor Matinyan48472850
Michel Ayvazyan47395256
Davit Davtyan46454550
Hayk Khachatryan46454550
Artem Bandikyan46454550
Narek Janoyan46454550
Vadim Harutyunyan46454550
Aram Aslanyan45454550
Artur Askaryan45434450
Player Rankings
Snipers
Top goal threats
1
Andrej KosticMontenegro U21
73
2
Artur GharibyanArmenia U21
65
3
Edik VardanyanArmenia U21
57
4
Stefan GolubovićMontenegro U21
45
5
Fin GeragusianArmenia U21
39
Wall
Top defenders
1
Damjan DakicMontenegro U21
85
2
Mher TarloyanArmenia U21
69
3
Stefan MelentijevićMontenegro U21
62
4
Milan RoganovicMontenegro U21
52
5
Balša VukotićMontenegro U21
45
Control
Top playmakers
1
Nemanja CarevićMontenegro U21
62
2
Dragan MiranovićMontenegro U21
59
3
Karlen HovhannisyanArmenia U21
51
4
Andrija BulatovicMontenegro U21
45
5
Kristijan RadunovićMontenegro U21
45
Bad Boys
Most likely to get booked
1
Stefan MelentijevićMontenegro U21
28
2
Petik ManukyanArmenia U21
37
3
Arayik EloyanArmenia U21
38
4
Hamlet SargsyanArmenia U21
46
5
Balša RadanovićMontenegro U21
50
Power Rankings
Strongest overall
1
Andrej KosticMontenegro U21
74
2
Damjan DakicMontenegro U21
72
3
Dragan MiranovićMontenegro U21
69
4
Artur GharibyanArmenia U21
57
5
Mher TarloyanArmenia U21
56

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Montenegro U21 vs Armenia U21 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 Montenegro U21 vs Armenia U21 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 Montenegro U21 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 Montenegro U21 vs Armenia U21 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 Montenegro U21 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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