· Liga Profesional de Fútbol
Estudiantes de Río Cuarto
ATT
2/10
DEF
4/10
1:2
Gimnasia La Plata
7/10
ATT
5/10
DEF
Конец
Лучший выбор
Меньше 2.5
71%
Точный счёт47′
Отличная
0-1
18.5%
6.00
Отличная
0-0
15.5%
7.50
1-1
12.4%
6.00
0-2
11.1%
8.00
1-0
10.4%
10.00
1-2
7.4%
9.00
0-3
4.4%
17.00
2-1
4.1%
15.00
121%
4.84
X31%
3.27
249%
2.05TOP
1X52%
X280%
1270%
xG — Ожидаемые голы
Estudiantes de Río Cuarto
Estudiantes de Río Cuarto ожид.
Gimnasia La Plata
Gimnasia La Plata ожид.
goal
за 15 мин
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Estudiantes de Río Cuarto
Gimnasia La Plata
Confirmed XI5-3-2
38
Herrera
14
Gonzalez
6
Antonini
30
Ojeda
29
Quiroga
23
Rodríguez
10
González
5
Cabrera
17
Alanís
77
Hesar
11
Garnerone
Impact Player Hot Head
Estudiantes de Río Cuarto40 игроков
50.1/ 99Средний
Лучшие
1Siro Rosané MID78
2Nicolás TalponeMID72
3Gonzalo MaffiniDEF70
Gimnasia La Plata38 игроков
52.9/ 99Средний
Лучшие
1Juan CortazzoDEF71
2Manuel PanaroFWD70
3Maximiliano Zalazar FWD70
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Maximiliano Zalazar Gimnasia La Plata
99
2
Franco TorresGimnasia La Plata
94
3
Manuel PanaroGimnasia La Plata
84
4
Facundo GallardoEstudiantes de Río Cuarto
81
5
Joaquín RiveroEstudiantes de Río Cuarto
63
Стена
Лучшие защитники
1
Juan CortazzoGimnasia La Plata
99
2
Germán ContiGimnasia La Plata
98
3
Renzo Giampaoli Gimnasia La Plata
93
4
Gonzalo MaffiniEstudiantes de Río Cuarto
78
5
Enzo MartínezGimnasia La Plata
72
Контроль
Лучшие плеймейкеры
1
Alejandro CabreraEstudiantes de Río Cuarto
89
2
Lucas Castro Gimnasia La Plata
75
3
Ignacio MiramónGimnasia La Plata
72
4
Nacho FernándezGimnasia La Plata
68
5
Francesco Lo CelsoEstudiantes de Río Cuarto
64
Хулиганы
Склонны к карточкам
1
Javier FerreiraEstudiantes de Río Cuarto
1
2
Ramón ÁbilaEstudiantes de Río Cuarto
1
3
Franco TorresGimnasia La Plata
1
4
Maximiliano Zalazar Gimnasia La Plata
1
5
Nicolas Barros SchelottoGimnasia La Plata
7
Рейтинг силы
Сильнейшие в целом
1
Siro Rosané Estudiantes de Río Cuarto
78
2
Nicolás TalponeEstudiantes de Río Cuarto
72
3
Juan CortazzoGimnasia La Plata
71
4
Gonzalo MaffiniEstudiantes de Río Cuarto
70
5
Facundo GallardoEstudiantes de Río Cuarto
70

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for Estudiantes de Río Cuarto vs Gimnasia La Plata 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 Estudiantes de Río Cuarto vs Gimnasia La Plata 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 Estudiantes de Río Cuarto 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 Estudiantes de Río Cuarto vs Gimnasia La Plata 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 Estudiantes de Río Cuarto 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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