· Torneo Betplay
Tigres
ATT
4/10
DEF
6/10
0:0
Real Cartagena
6/10
ATT
6/10
DEF
Конец
Лучший выбор
Меньше 2.5
66%
Точный счёт47′
Отличная
1-1
13.5%
6.50
Отличная
1-0
13.2%
8.50
0-1
12.9%
7.50
0-0
12.5%
7.00
2-1
7.1%
13.00
1-2
6.9%
12.00
2-0
6.9%
13.00
0-2
6.6%
11.00
136%
2.82TOP
X30%
3.32
234%
2.91
1X66%
X264%
1270%
xG — Ожидаемые голы
Tigres
Tigres ожид.
Real Cartagena
Real Cartagena ожид.
goal
за 15 мин
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Tigres
Real Cartagena
Probable XI4-4-2
Mateus
Al-Haj
Caviedes
Viáfara
Carabalí
Cuadros
Fajardo
Caicedo
Ávila
Ibarra
Dawson
Impact Player Hot Head
Составы ещё не объявлены — полный анализ игроков ниже
Tigres29 игроков
58.4/ 99Сильный
Лучшие
1Jhon MartínezFWD82
2Jhon Alejandro Lopera GaviriaDEF81
3Wakner Stiwar MenaFWD80
Real Cartagena38 игроков
59.5/ 99Сильный
Лучшие
1F. MonteroFWD95
2Jarlan BarreraMID91
3Jhojan Camilo Nieva RoldánMID76
Tigres51
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Jhon Martínez82983950
Jhon Alejandro Lopera Gaviria81764691
Wakner Stiwar Mena80766878
Andrés Cuadros78638291
Miguel Alvarez76606991
Jesús Cano69466391
Ricardo Rosales67439991
Santiago Guzmán65407591
Duván Viáfara64494191
Jhon Fredys Rentería Cordoba6493961
Omar Preciado64533791
Yimmer Salas64513891
Santiago Rativa61485289
Real Cartagena48
PlayerОбщий РейтингВлияниеАгрессияДисциплина
F. Montero95956491
Jarlan Barrera91994289
Jhojan Camilo Nieva Roldán76694391
C. Paternina75624991
Marlon Balanta75586991
Gabriel Erazo75684191
Edison López74565991
Jhon Gamboa72772791
Guillermo Tegüé68574291
Luis Guevara67435891
J. Rodríguez66427091
Ronaldo Lora65425291
Mauro Manotas6474967
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Jhon MartínezTigres
98
2
F. MonteroReal Cartagena
95
3
Wakner Stiwar MenaTigres
76
4
Mauro ManotasReal Cartagena
74
5
Álvaro MeléndezReal Cartagena
60
Стена
Лучшие защитники
1
Jhon Fredys Rentería CordobaTigres
93
2
Jhon GamboaReal Cartagena
77
3
Jhon Alejandro Lopera GaviriaTigres
76
4
Dilan OrtízReal Cartagena
65
5
C. PaterninaReal Cartagena
62
Контроль
Лучшие плеймейкеры
1
Jarlan BarreraReal Cartagena
99
2
Jhojan Camilo Nieva RoldánReal Cartagena
69
3
Gabriel ErazoReal Cartagena
68
4
Andrés CuadrosTigres
63
5
Miguel AlvarezTigres
60
Хулиганы
Склонны к карточкам
1
Samuel Alejandro Flórez SeguraTigres
1
2
Jimmy CongoReal Cartagena
1
3
Kevin LópezTigres
50
4
Joseph RuízTigres
50
5
Brandón Andrés Mejía FajardoTigres
50
Рейтинг силы
Сильнейшие в целом
1
F. MonteroReal Cartagena
95
2
Jarlan BarreraReal Cartagena
91
3
Jhon MartínezTigres
82
4
Jhon Alejandro Lopera GaviriaTigres
81
5
Wakner Stiwar MenaTigres
80

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for Tigres vs Real Cartagena 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 Tigres vs Real Cartagena 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 Tigres 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 Tigres vs Real Cartagena 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 Tigres 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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