· Primera B Nacional
San Martín de Tucumán
ATT
6/10
DEF
5/10
vs
Colegiales
3/10
ATT
5/10
DEF
Запланирован· Sun 1 Nov · 21:30
Лучший выбор
Меньше 2.5
66%
Точный счёт
Отличная
1-0
19.3%
6.00
Отличная
2-0
14.7%
11.00
0-0
12.7%
5.00
1-1
10.4%
6.00
2-1
8%
13.00
3-0
7.5%
29.00
0-1
6.8%
6.00
3-1
4%
34.00
162%
2.70TOP
X25%
2.63
213%
2.75
1X87%
X238%
1275%
Probable XI4-4-2
Sand
Paz
Cabrera
López
López
Graneros
Cisneros
Carabajal
Soraire
Veliez
Borasi
Impact Player Hot Head
Составы ещё не объявлены — полный анализ игроков ниже
San Martín de Tucumán35 игроков
43.2/ 99Средний
Лучшие
1Nicolás CastroMID79
2Gonzalo RodríguezFWD70
3Alan CisnerosMID64
Colegiales33 игроков
45.1/ 99Средний
Лучшие
1Leo OrtizDEF74
2Elias OcampoMID73
3Gonzalo Leandro BaglivoMID71
San Martín de Tucumán43
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Nicolás Castro79655890
Gonzalo Rodríguez70774061
Alan Cisneros64642391
Facundo Pons62656946
Elías López61377072
Juan Bautista Valdez60458756
Kevin López59656844
Tiago Penalba58465767
B. Borasi56456872
Guillermo Sebastian Rodríguez52414967
Nahuel Manganelli4949950
Matias Garcia48604536
Darío Sand4645950
Colegiales44
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Leo Ortiz74843674
Elias Ocampo73595289
Gonzalo Leandro Baglivo71972850
Mauro Albertengo67574891
J. Mamani61526472
Tomás Perri57536161
Ezequiel Adriel Aguirre Quirós56485167
Federico Marín55268580
Franco Zicarelli55872822
Emilio Di Fulvio51517650
Nicolas Toloza51595829
Lucas Juárez48493556
Gastón Cortés46483950
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Gonzalo RodríguezSan Martín de Tucumán
77
2
Facundo PonsSan Martín de Tucumán
65
3
Nicolas TolozaColegiales
59
4
Mauro AlbertengoColegiales
57
5
D. DiellosSan Martín de Tucumán
56
Стена
Лучшие защитники
1
Leo OrtizColegiales
84
2
F. RiveroColegiales
75
3
Ezequiel Adriel Aguirre QuirósColegiales
48
4
Gastón CortésColegiales
48
5
Tiago PenalbaSan Martín de Tucumán
46
Контроль
Лучшие плеймейкеры
1
Gonzalo Leandro BaglivoColegiales
97
2
Franco ZicarelliColegiales
87
3
Kevin LópezSan Martín de Tucumán
65
4
Nicolás CastroSan Martín de Tucumán
65
5
Alan CisnerosSan Martín de Tucumán
64
Хулиганы
Склонны к карточкам
1
G. CarabajalSan Martín de Tucumán
1
2
Jorge Emanuel JuárezSan Martín de Tucumán
1
3
Leonardo Gastón MonroySan Martín de Tucumán
1
4
Santiago BriñoneSan Martín de Tucumán
1
5
D. DiellosSan Martín de Tucumán
1
Рейтинг силы
Сильнейшие в целом
1
Nicolás CastroSan Martín de Tucumán
79
2
Leo OrtizColegiales
74
3
Elias OcampoColegiales
73
4
Gonzalo Leandro BaglivoColegiales
71
5
Gonzalo RodríguezSan Martín de Tucumán
70

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for San Martín de Tucumán vs Colegiales 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 San Martín de Tucumán vs Colegiales 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 San Martín de Tucumán 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 San Martín de Tucumán vs Colegiales 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 San Martín de Tucumán 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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