· AFC Champions League Two
Al Jazira
ATT
5/10
DEF
5/10
vs
Muharraq
5/10
ATT
5/10
DEF
Запланирован· Wed 28 Oct · 16:00
Лучший выбор
ОБЕ ЗАБЬЮТ
53%
Точный счёт
Отличная
1-1
11.7%
7.50
Отличная
1-0
10.7%
6.00
2-1
9.6%
10.00
2-0
8.8%
7.00
0-1
7.1%
13.00
0-0
6.6%
8.00
1-2
6.4%
21.00
3-1
5.2%
17.00
150%
1.53TOP
X25%
3.60
225%
5.50
1X75%
X250%
1275%
Probable XI4-4-2
Alhammadi
Abdulrahman
Serrote
Lagrimi
Mendy
Ramadan
Mahmoud
Dennis
Sagna
Almemari
Bougma
Impact Player Hot Head
Составы ещё не объявлены — полный анализ игроков ниже
Al Jazira16 игроков
51.3/ 99Средний
Лучшие
1Anthony DennisMID72
2Mamadou CoulibalyMID68
3Kristjan AsllaniMID57
Muharraq21 игроков
52.9/ 99Средний
Лучшие
1Arthur RezendeMID73
2Abdulwahab Al MaloodMID72
3Facundo TobaresFWD69
Al Jazira47
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Anthony Dennis72606278
Mamadou Coulibaly68735361
Kristjan Asllani57614456
Abdallah Ramadan56634550
Willyan Rocha54544756
Khalifa Mubarak53514956
Mohammed Rabii52455161
Malcom Filipe Silva de Oliveira51494956
Talisca 50474756
Ersin Destanoğlu48473950
Rúben Amaral48454556
Ali Almemari47474550
Marcus Meloni45463950
Muharraq28
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Arthur Rezende73565391
Abdulwahab Al Malood72629167
Facundo Tobares69775050
Bruno Araújo dos Santos67436289
Husain Jameel63459961
Anderson Leite56485661
Waleed Al Hayam54655837
Vladan Đekić52523950
Amine Benaddi52534556
Juninho Piauiense52524656
Abdul Wahab Hanan51534650
Sayed Mohamed Jaffer49484550
Ahmed Bughammar49514550
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Facundo TobaresMuharraq
77
2
Juninho PiauienseMuharraq
52
3
Malcom Filipe Silva de OliveiraAl Jazira
49
4
Vinicius MelloAl Jazira
49
5
Ali AlmemariAl Jazira
47
Стена
Лучшие защитники
1
Waleed Al HayamMuharraq
65
2
Mohamed AlbannaMuharraq
55
3
Willyan RochaAl Jazira
54
4
Nermin Mujkic Al Jazira
53
5
Amine BenaddiMuharraq
53
Контроль
Лучшие плеймейкеры
1
Mamadou CoulibalyAl Jazira
73
2
Abdallah RamadanAl Jazira
63
3
Abdulwahab Al MaloodMuharraq
62
4
Kristjan AsllaniAl Jazira
61
5
Anthony DennisAl Jazira
60
Хулиганы
Склонны к карточкам
1
Mohamed YusufMuharraq
1
2
Vinicius MelloAl Jazira
7
3
Nermin Mujkic Al Jazira
26
4
Abdullah Al-KhalasiMuharraq
37
5
Waleed Al HayamMuharraq
37
Рейтинг силы
Сильнейшие в целом
1
Arthur RezendeMuharraq
73
2
Anthony DennisAl Jazira
72
3
Abdulwahab Al MaloodMuharraq
72
4
Facundo TobaresMuharraq
69
5
Mamadou CoulibalyAl Jazira
68

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for Al Jazira vs Muharraq 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 Al Jazira vs Muharraq 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 Al Jazira 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 Al Jazira vs Muharraq 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 Al Jazira 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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