Botafogo look the sharper side at home: their attack has real bite and creates the better chances, while Atlético-MG’s forward threat has been subdued. The visitors’ solid defense could frustrate them for spells, but Botafogo should keep knocking on the door and turn their attacking edge into the win.
Match WinnerBotafogo-RJ
Best Pick
BTTS
54%
Correct Score
Top
1-1
11.2%
7.00
Top
1-0
10.6%
9.00
2-1
9.8%
8.50
2-0
9.2%
11.00
0-1
6.5%
13.00
0-0
6.1%
13.00
1-2
6%
12.00
3-1
5.6%
15.00
153%
1.95TOP
X24%
3.60
223%
3.50
1X77%
X247%
1276%
Combined Bet Builder
3 legs
Botafogo’s 1.53 xG and attack power 24% above average point to sustained home threat, while its leaky defense should give Atlético-MG chances too. That balance supports an open game clearing 2.5 goals, with Botafogo or the draw the likelier result. Arthur Cabral is a credible anytime scorer in a match that appears set to offer opportunities.
1Double ChanceBotafogo-RJ or Draw
2Match GoalsOver 2.5
3GoalscorersAnytime
Confirmed XI4-4-2
12
Batista
2
Vitinho
5
Ferraresi
21
Marçal
13
Telles
75
Huguinho
6
Medina
22
Ziyech
10
Montoro
11
Martins
19
Cabral
Impact Player Hot Head
Botafogo-RJ52 players
52.2/ 99Average
Top Rated
1Lucas EmanuelFWD92
2Matheus MartinsFWD85
3Óscar RomeroMID77
Atlético-MG47 players
53.9/ 99Average
Top Rated
1AlexsanderMID83
2Cauã SoaresFWD79
3Cadu FWD72
Player Rankings
Snipers
Top goal threats
1
Lucas EmanuelBotafogo-RJ
99
2
Kadir BarriaBotafogo-RJ
87
3
Paulinho Atlético-MG
83
4
Cadu Atlético-MG
82
5
Matheus MartinsBotafogo-RJ
81
Wall
Top defenders
1
VitãoAtlético-MG
91
2
Nahuel Ferraresi Botafogo-RJ
69
3
Alexander BarbozaBotafogo-RJ
67
4
LyancoAtlético-MG
66
5
Iván RománAtlético-MG
62
Control
Top playmakers
1
Kevin CastañoAtlético-MG
83
2
AlexsanderAtlético-MG
76
3
Óscar RomeroBotafogo-RJ
73
4
Marlon Freitas Botafogo-RJ
71
5
Igor GomesAtlético-MG
70
Bad Boys
Most likely to get booked
1
Gabriel JustinoBotafogo-RJ
1
Aggression 44
2
Mateo PonteBotafogo-RJ
1
Aggression 57
3
Patrick de PaulaBotafogo-RJ
1
Aggression 49
4
Artur Botafogo-RJ
1
Aggression 27
5
Joaquín CorreaBotafogo-RJ
1
Aggression 43
Power Rankings
Strongest overall
1
Lucas EmanuelBotafogo-RJ
92
2
Matheus MartinsBotafogo-RJ
85
3
AlexsanderAtlético-MG
83
4
Cauã SoaresAtlético-MG
79
5
Óscar RomeroBotafogo-RJ
77
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Botafogo-RJ vs Atlético-MG 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 Botafogo-RJ vs Atlético-MG 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 Botafogo-RJ 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 Botafogo-RJ vs Atlético-MG 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 Botafogo-RJ 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.