Corinthians look the likelier winners at home: they’re projected to create the clearer chances, while Mirassol’s blunt attack offers little to fear. Both defenses are sturdy, so patience may be needed, but Corinthians should have the edge in the decisive moments and find a way through.
Match WinnerCorinthians
En iyi tahmin
Alt 2.5
55%
Doğru skor
Mükemmel
1-1
12.7%
6.50
Mükemmel
1-0
11.8%
7.00
0-1
9%
13.00
2-1
8.9%
8.50
0-0
8.4%
10.00
2-0
8.2%
8.00
1-2
6.8%
15.00
0-2
4.9%
23.00
144%
1.75TOP
X27%
3.60
229%
4.75
1X71%
X256%
1273%
Kombine
3 seçim
Corinthians’ home pressure should keep the corners flowing, while Mirassol have enough threat to punish any defensive lapse. Though both attacks have been blunt, the open momentum of a tense contest points to both teams to score and goals clearing the three-goal mark, with sustained wing play likely to push corners beyond the line.
1Both Teams to ScoreYes
2Match GoalsOver 2.5
3Corners Over/UnderOver 8.5
Confirmed XI5-4-1
1
Souza
2
Matheuzinho
5
Ramalho
13
Henrique
26
Angileri
21
Bidu
49
Dias
7
Bidon
61
Dieguinho
8
Garro
9
Alberto
Impact Player Hot Head
Corinthians46 oyuncu
48.8/ 99Orta
En İyiler
1André CarrilloMID64
2Fausto VeraMID64
3Matheus PereiraMID62
Mirassol FC SP49 oyuncu
51.1/ 99Orta
En İyiler
1Zé Roberto FWD90
2Chico KimMID79
3Nathan FogaçaFWD78
Oyuncu sıralamaları
Keskin nişancılar
En büyük gol tehdidi
1
Zé Roberto Mirassol FC SP
99
2
Nathan FogaçaMirassol FC SP
91
3
Renato MarquesMirassol FC SP
65
4
Tiquinho SoaresMirassol FC SP
62
5
Talles MagnoCorinthians
54
Duvar
En iyi savunmacılar
1
GabrielMirassol FC SP
89
2
Luiz OtávioMirassol FC SP
79
3
Willian MachadoMirassol FC SP
73
4
Lucas OliveiraMirassol FC SP
71
5
Lucas GazalMirassol FC SP
67
Kontrol
En iyi oyun kurucular
1
Matheus PereiraCorinthians
85
2
Chico KimMirassol FC SP
79
3
José AldoMirassol FC SP
75
4
AllanCorinthians
73
5
Rodrigo GarroCorinthians
70
Yaramaz çocuklar
Kart görme olasılığı en yüksek
1
André RamalhoCorinthians
1
Agresiflik 32
2
CacáCorinthians
1
Agresiflik 25
3
Fabrizio AngileriCorinthians
1
Agresiflik 56
4
Gabriel PaulistaCorinthians
1
Agresiflik 26
5
Rodrigo GarroCorinthians
1
Agresiflik 40
Güç sıralaması
Genel olarak en güçlüler
1
Zé Roberto Mirassol FC SP
90
2
Chico KimMirassol FC SP
79
3
Nathan FogaçaMirassol FC SP
78
4
Lucas Mugni Mirassol FC SP
71
5
Lucas GazalMirassol FC SP
67
Sıkça Sorulan Sorular
Our Poisson model calculates the probability of every possible scoreline for Corinthians vs Mirassol FC SP 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 Corinthians vs Mirassol FC SP 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 Corinthians 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 Corinthians vs Mirassol FC SP 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 Corinthians 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.