· Super Lig
Beşiktaş
ATT
6/10
DEF
6/10
vs
İstanbul Başakşehir
6/10
ATT
6/10
DEF
Запланирован· Mon 26 Oct · 16:00

ИИ-анализ матча

Besiktas’ home ambition should drive sustained pressure, while Başakşehir bring enough attacking punch to make the contest two-sided. With both sides equipped to create chances, the match appears poised to open up and carry goals beyond the threshold.

Match GoalsOver 2.5
Лучший выбор
ОБЕ ЗАБЬЮТ
56%
Точный счёт
Отличная
1-1
11.2%
11.00
Отличная
1-0
10%
11.00
2-1
9.7%
9.00
2-0
8.6%
9.00
0-1
6.5%
26.00
1-2
6.3%
21.00
0-0
5.8%
23.00
3-1
5.6%
10.00
152%
1.33TOP
X24%
5.00
225%
7.00
1X76%
X249%
1277%

Экспресс

3 выборов

Besiktas’ home edge points to the strongest route: 1.55 xG overall and 1.03 xG before the break, compared with Başakşehir’s 0.99 and 0.46. That first-half chance gap supports Besiktas taking control early, while both attacks rate above average, making Over 2.5 a logical fit alongside a home win.

1Match WinnerBesiktas JK
2Match GoalsOver 2.5
3First Half WinnerBesiktas JK
Confirmed XI4-4-2
1
Nübel
62
Murillo
12
Agbadou
53
Topçu
33
Yılmaz
6
Özcan
18
Cerny
15
Olaitan
21
Miretti
19
Trossard
28
Vlahović
Impact Player Hot Head
Beşiktaş43 игроков
55.5/ 99Сильный
Лучшие
1Ernest PokuFWD84
2Jota SilvaFWD81
3Salih Özcan MID80
İstanbul Başakşehir29 игроков
49.4/ 99Средний
Лучшие
1Miguel CrespoMID73
2Eldor ShomurodovFWD71
3Hamza GürelerDEF68
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Cengiz ÜnderBeşiktaş
99
2
Ilhan FakiliBeşiktaş
99
3
Jota SilvaBeşiktaş
99
4
Ernest PokuBeşiktaş
96
5
Vaclav CernyBeşiktaş
83
Стена
Лучшие защитники
1
Hamza Gürelerİstanbul Başakşehir
81
2
Tayyip Talha Sanuç Beşiktaş
73
3
Tiago DjalóBeşiktaş
73
4
Felix UduokhaiBeşiktaş
68
5
Emirhan TopçuBeşiktaş
66
Контроль
Лучшие плеймейкеры
1
Orkun Kökçü Beşiktaş
94
2
Kartal YılmazBeşiktaş
84
3
Jakub Kaluzinskiİstanbul Başakşehir
79
4
Junior OlaitanBeşiktaş
75
5
Salih Özcan Beşiktaş
73
Хулиганы
Склонны к карточкам
1
Emirhan TopçuBeşiktaş
1
2
Ernest MuciBeşiktaş
1
3
Orkun Kökçü Beşiktaş
1
4
Dušan VlahovićBeşiktaş
1
5
Tammy AbrahamBeşiktaş
1
Рейтинг силы
Сильнейшие в целом
1
Ernest PokuBeşiktaş
84
2
Jota SilvaBeşiktaş
81
3
Salih Özcan Beşiktaş
80
4
Junior OlaitanBeşiktaş
79
5
Ilhan FakiliBeşiktaş
78

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for Beşiktaş vs İstanbul Başakşehir 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 Beşiktaş vs İstanbul Başakşehir 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 Beşiktaş 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 Beşiktaş vs İstanbul Başakşehir 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 Beşiktaş 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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