Cusco’s formidable home resistance should make life uncomfortable for the league leaders, but Sporting Cristal’s sharper attack is equipped to pierce that wall. Their own leaky defense offers Cusco a route back, setting up a tense exchange where both teams to score appears the most natural outcome.
Both Teams to ScoreYes
Лучший выбор
ОБЕ ЗАБЬЮТ
52%
Точный счёт
Отличная
1-1
11.7%
7.50
Отличная
1-0
11.3%
9.00
2-1
9.6%
8.50
2-0
9.2%
10.00
0-1
7.2%
13.00
0-0
6.9%
13.00
1-2
6.1%
13.00
3-1
5.2%
15.00
151%
1.90TOP
X25%
3.70
224%
3.60
1X76%
X249%
1275%
Экспресс
3 выборов
Cusco FC’s 1.61 xG edges Sporting Cristal’s 1.41, while their defense is 41% stronger than average—an important platform against the league leaders. Cristal’s defense is 5% weaker than average, giving Juan Manuel Tevez a clear route to score. The attacking numbers point to an open game, with Cusco’s home advantage likely driving a win and over 2.5 goals.
1Match WinnerCusco FC
2Match GoalsOver 2.5
3GoalscorersAnytime
Confirmed XI4-4-2
28
Diaz
21
Zevallos
8
Fuentes
2
Gamarra
3
Lagos
55
Montaño
88
Soto
10
Colman
7
Manzaneda
26
Silva
9
Callejo
Impact Player Hot Head
Cusco FC25 игроков
48.7/ 99Средний
Лучшие
1MiguelMID73
2Facundo CallejoFWD68
3Carlos MontañoMID65
Sporting Cristal36 игроков
51.6/ 99Средний
Лучшие
1Yoshimar Yotún MID71
2Leonardo DíazDEF70
3Juan Manuel CuestaFWD67
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Juan Manuel CuestaSporting Cristal
86
2
Facundo CallejoCusco FC
74
3
Michael HoyosSporting Cristal
67
4
Josemaría MellánSporting Cristal
65
5
Mateo RodríguezSporting Cristal
60
Стена
Лучшие защитники
1
Leonardo DíazSporting Cristal
79
2
Aldair FuentesCusco FC
69
3
Carlos GamarraCusco FC
65
4
Rafael LutigerSporting Cristal
64
5
Joao Stefhano Cuenca MelgarSporting Cristal
61
Контроль
Лучшие плеймейкеры
1
Iván ColmanCusco FC
87
2
Yoshimar Yotún Sporting Cristal
87
3
G. CarabajalCusco FC
82
4
Martín TávaraSporting Cristal
82
5
Gerson CastilloSporting Cristal
79
Хулиганы
Склонны к карточкам
1
Christofer GonzalesSporting Cristal
1
Агрессия 42
2
G. CarabajalCusco FC
3
Агрессия 34
3
Alejandro PósitoSporting Cristal
3
Агрессия 44
4
Luis AbramSporting Cristal
12
Агрессия 28
5
José ManzanedaCusco FC
14
Агрессия 54
Рейтинг силы
Сильнейшие в целом
1
MiguelCusco FC
73
2
Yoshimar Yotún Sporting Cristal
71
3
Leonardo DíazSporting Cristal
70
4
Facundo CallejoCusco FC
68
5
Juan Manuel CuestaSporting Cristal
67
Часто задаваемые вопросы
Our Poisson model calculates the probability of every possible scoreline for Cusco FC vs Sporting Cristal 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 Cusco FC vs Sporting Cristal 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 Cusco FC 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 Cusco FC vs Sporting Cristal 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 Cusco FC 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.