· Primera Nacional
Nueva Chicago
ATT
4/10
DEF
5/10
vs
San Martin de San Juan
5/10
ATT
5/10
DEF
Planlandı· Mon 26 Oct · 16:00
En iyi tahmin
Alt 2.5
72%
Doğru skor
Mükemmel
1-0
15.8%
6.00
Mükemmel
0-0
15.7%
5.00
1-1
13.4%
5.50
0-1
13.2%
6.50
2-0
8%
12.00
2-1
6.7%
12.00
1-2
5.6%
12.00
0-2
5.6%
12.00
138%
2.75TOP
X32%
2.70
229%
2.80
1X70%
X261%
1267%
Probable XI4-4-2
Masuero
Palazzo
Arroyo
Gissi
Machuca
Ruiz
González
Méndez
Roldán
Barros
Cardozo
Impact Player Hot Head
Kadrolar henüz açıklanmadı — aşağıda tam kadro analizi
Nueva Chicago35 oyuncu
51.3/ 99Orta
En İyiler
1Leo OrtizDEF74
2Lucas AmbrogioFWD74
3Alan RuizMID71
San Martin de San Juan28 oyuncu
52.0/ 99Orta
En İyiler
1Bruno JuncosFWD98
2Gabriel HachenMID80
3Nicolás PazDEF79
Nueva Chicago44
PlayerGenel DereceEtkiAgresyonDisiplin
Leo Ortiz74863673
Lucas Ambrogio74994518
Alan Ruiz71999523
Roman Zalazar70737650
Sebastián Cocimano67623891
Diego Joel Barros61693950
G. Paz60787129
Guillermo Ferracutti60524673
Maximiliano Rogoski59705731
Dylan Gissi57813435
Gabriel Vega57512689
Matías Bergara57595250
F. Moreno56645146
San Martin de San Juan37
PlayerGenel DereceEtkiAgresyonDisiplin
Bruno Juncos98999991
Gabriel Hachen80995455
Nicolás Paz79956450
Nicolás Iachetti75606489
Ramiro Rumbolo71804961
Nazareno Fúnez71705273
Guillermo Acosta 69644778
Manuel Cocca59725243
Facundo Nadalín58436763
Nicolás Pelaitay 58327478
Sebastián González55794727
Sebastián Jaurena53633449
Sebastián Díaz5253950
Oyuncu sıralamaları
Keskin nişancılar
En büyük gol tehdidi
1
Lucas AmbrogioNueva Chicago
99
2
Bruno JuncosSan Martin de San Juan
99
3
Matías RomeroNueva Chicago
72
4
Maximiliano RogoskiNueva Chicago
70
5
Nazareno FúnezSan Martin de San Juan
70
Duvar
En iyi savunmacılar
1
Nicolás PazSan Martin de San Juan
95
2
Leo OrtizNueva Chicago
86
3
Dylan GissiNueva Chicago
81
4
G. PazNueva Chicago
78
5
Roman ZalazarNueva Chicago
73
Kontrol
En iyi oyun kurucular
1
Alan RuizNueva Chicago
99
2
Gabriel HachenSan Martin de San Juan
99
3
Ramiro RumboloSan Martin de San Juan
80
4
Sebastián GonzálezSan Martin de San Juan
79
5
Nazareno PetreccaNueva Chicago
70
Yaramaz çocuklar
Kart görme olasılığı en yüksek
1
Alejo GonzálezNueva Chicago
1
2
Emanuel Aguilera San Martin de San Juan
1
3
Diego MercadoSan Martin de San Juan
1
4
Matías RomeroNueva Chicago
10
5
Lucas AmbrogioNueva Chicago
18
Güç sıralaması
Genel olarak en güçlüler
1
Bruno JuncosSan Martin de San Juan
98
2
Gabriel HachenSan Martin de San Juan
80
3
Nicolás PazSan Martin de San Juan
79
4
Nicolás IachettiSan Martin de San Juan
75
5
Leo OrtizNueva Chicago
74

Sıkça Sorulan Sorular

Our Poisson model calculates the probability of every possible scoreline for Nueva Chicago vs San Martin de San Juan 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 Nueva Chicago vs San Martin de San Juan 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 Nueva Chicago 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 Nueva Chicago vs San Martin de San Juan 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 Nueva Chicago 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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