· Europa League
Omonia Nicosia
ATT
6/10
DEF
7/10
vs
Benfica
10/10
ATT
7/10
DEF
Запланирован· Thu 22 Oct · 19:00

ИИ-анализ матча

Benfica’s +96% attacking power is the key driver, while Omonia’s +24% boost gives the hosts a credible route to contribute. Both defenses rate above average, but the combined attacking threat should create enough chances to overcome that resistance, making Over 2.5 the logical expectation.

Match GoalsOver 2.5
Лучший выбор
ОБЕ ЗАБЬЮТ
57%
Точный счёт
Отличная
1-1
11.7%
11.00
Отличная
0-1
9%
9.00
1-2
8.9%
9.00
2-1
7.7%
23.00
1-0
7.7%
26.00
0-2
6.8%
7.50
0-0
5.9%
19.00
2-2
5.9%
21.00
133%
8.50
X25%
6.00
242%
1.30TOP
1X58%
X267%
1275%

Экспресс

3 выборов

Benfica’s explosive attack should keep Omonia’s sturdy defence under pressure, but the hosts have enough bite to answer and get both teams to score. With chances building at both ends and Benfica likely driving the corner count, this has the feel of an open, end-to-end night that can clear over two and a half goals and over eight and a half corners.

1Both Teams to ScoreYes
2Match GoalsOver 3.5
3Corners Over/UnderOver 8.5
Confirmed XI4-4-2
40
Fabiano
77
Nego
93
Duverne
37
Satka
29
Balkovec
14
Maric
74
Andreou
11
Costa
7
Montnor
17
Tănase
9
Kakoullis
Impact Player Hot Head
Omonia Nicosia31 игроков
50.6/ 99Средний
Лучшие
1Stefan SimicDEF73
2FabianoGK70
3Francis UzohoGK66
Benfica35 игроков
53.7/ 99Средний
Лучшие
1Franjo IvanovićFWD97
2Manu Silva MID87
3AnísioFWD86
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
AnísioBenfica
99
2
Franjo IvanovićBenfica
99
3
Vangelis PavlidisBenfica
83
4
Dodi LukébakioBenfica
75
5
Jhon Durán Benfica
74
Стена
Лучшие защитники
1
Senou CoulibalyOmonia Nicosia
81
2
Nikolas PanagiotouOmonia Nicosia
66
3
Fotis KitsosOmonia Nicosia
65
4
Andreas ChristouOmonia Nicosia
62
5
Lubomir SatkaOmonia Nicosia
62
Контроль
Лучшие плеймейкеры
1
Fredrik AursnesBenfica
84
2
Diogo Ferreira PriosteBenfica
82
3
Manu Silva Benfica
80
4
Enzo BarrenecheaBenfica
73
5
Muamer TankovicOmonia Nicosia
70
Хулиганы
Склонны к карточкам
1
Florin TănaseOmonia Nicosia
1
2
Tomás AraújoBenfica
1
3
Gianluca PrestianniBenfica
1
4
Senou CoulibalyOmonia Nicosia
13
5
João PalhinhaBenfica
19
Рейтинг силы
Сильнейшие в целом
1
Franjo IvanovićBenfica
97
2
Manu Silva Benfica
87
3
AnísioBenfica
86
4
Diogo Ferreira PriosteBenfica
77
5
Stefan SimicOmonia Nicosia
73

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for Omonia Nicosia vs Benfica 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 Omonia Nicosia vs Benfica 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 Omonia Nicosia 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 Omonia Nicosia vs Benfica 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 Omonia Nicosia 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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