Over 8.5 corners looks the logical call: Bayern’s attack is a constant corner threat, boasting +54% corner-winning power, while Arsenal also win corners often. Both defenses are stronger than average at limiting concessions, but Bayern’s relentless pressure and Arsenal’s ability to attack should keep the game stretched and generate enough set-piece action to clear the line.
Corners Over/UnderOver 8.5
Лучший выбор
Больше 2.5
76%
Точный счёт
Отличная
2-1
8.7%
9.50
Отличная
3-1
8.1%
15.00
2-0
7.1%
13.00
3-0
6.7%
21.00
1-1
6.2%
7.00
4-1
5.7%
29.00
2-2
5.3%
11.00
1-0
5.1%
12.00
170%
2.25TOP
X16%
3.60
214%
3.00
1X86%
X230%
1284%
Экспресс
3 выборов
Bayern’s 1.96 xG and explosive attack should drive the scoring, while Arsenal’s 1.34 xG gives both teams to score a strong foundation. Their combined 3.30 xG supports over 2.5 goals, and 8.48 expected corners sits just below the line; Bayern’s constant corner threat should help push the total over 8.5.
1Match GoalsOver 3.5
2Both Teams to ScoreYes
3Corners Over/UnderOver 8.5
Confirmed XI4-5-1
40
Urbig
27
Laimer
2
Upamecano
4
Tah
19
Davies
8
Bischof
45
Pavlovic
42
Karl
34
Saibari
14
Díaz
9
Kane
Impact Player Hot Head
FC Bayern München32 игроков
52.2/ 99Средний
Лучшие
1Harry Kane FWD89
2Aleksandar PavlovicMID87
3Tom BischofMID84
Arsenal25 игроков
54.2/ 99Средний
Лучшие
1Declan RiceMID74
2Bruno GuimarãesMID72
3Gabriel Jesus FWD70
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Harry Kane FC Bayern München
99
2
Gabriel Jesus Arsenal
99
3
Bukayo Saka Arsenal
68
4
Gabriel MartinelliArsenal
68
5
Luis DíazFC Bayern München
65
Стена
Лучшие защитники
1
Deniz OfliFC Bayern München
56
2
Gabriel MagalhãesArsenal
56
3
Jonathan TahFC Bayern München
47
4
Min-jae KimFC Bayern München
46
5
Piero HincapiéArsenal
45
Контроль
Лучшие плеймейкеры
1
Aleksandar PavlovicFC Bayern München
99
2
Joshua Kimmich FC Bayern München
99
3
Tom BischofFC Bayern München
99
4
Declan RiceArsenal
91
5
Bruno GuimarãesArsenal
80
Хулиганы
Склонны к карточкам
1
Gabriel Jesus Arsenal
1
Агрессия 64
2
Gabriel MartinelliArsenal
1
Агрессия 52
3
Jonathan TahFC Bayern München
10
Агрессия 42
4
Myles Lewis-SkellyArsenal
19
Агрессия 47
5
Joshua Kimmich FC Bayern München
25
Агрессия 25
Рейтинг силы
Сильнейшие в целом
1
Harry Kane FC Bayern München
89
2
Aleksandar PavlovicFC Bayern München
87
3
Tom BischofFC Bayern München
84
4
Declan RiceArsenal
74
5
Luis DíazFC Bayern München
72
Часто задаваемые вопросы
Our Poisson model calculates the probability of every possible scoreline for FC Bayern München vs Arsenal 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 FC Bayern München vs Arsenal 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 FC Bayern München 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 FC Bayern München vs Arsenal 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 FC Bayern München 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.