This derby screams goals: Botafogo’s surging attack meets Vasco’s leaky back line, while Botafogo’s own fragile defense invites dangerous counters. With both sides inclined forward and momentum favoring attacking exchanges, the contest strongly tilts toward a multi-goal spectacle.
Match GoalsOver 2.5
Best Pick
Home Win
58%
Correct Score
Top
1-0
11.4%
10.00
Top
1-1
10.8%
6.50
2-0
10.4%
15.00
2-1
9.9%
10.00
3-0
6.3%
29.00
0-0
6.2%
12.00
3-1
6%
21.00
0-1
5.9%
9.50
158%
2.70TOP
X23%
3.40
219%
2.45
1X81%
X242%
1277%
Combined Bet Builder
3 legs
Botafogo’s aggressive edge against two shaky backlines points toward a lively derby, with the opening period already primed for a breakthrough. Vasco’s weaker attack still benefits from Botafogo’s fragile rear, inviting a response. With both sides prone to trading territory and pressure, repeated surges from wide areas should keep corners and goals flowing.
1Match GoalsOver 2.5
2First Half Over/UnderOver 0.5
3Corners Over/UnderOver 8.5
Confirmed XI4-4-2
12
Batista
2
Vitinho
5
Ferraresi
33
Monzón
13
Telles
8
Danilo
6
Medina
75
Huguinho
10
Montoro
90
Danilo
19
Cabral
Impact Player Hot Head
Botafogo-RJ52 players
51.0/ 99Average
Top Rated
1Lucas EmanuelFWD92
2Matheus MartinsFWD89
3Kadir BarriaFWD80
Vasco da Gama47 players
53.7/ 99Average
Top Rated
1Claudio SpinelliFWD92
2Facundo ColidioFWD89
3Santiago Sosa MID76
Player Rankings
Snipers
Top goal threats
1
Lucas EmanuelBotafogo-RJ
99
2
Facundo ColidioVasco da Gama
95
3
Kadir BarriaBotafogo-RJ
91
4
Claudio SpinelliVasco da Gama
91
5
Matheus MartinsBotafogo-RJ
86
Wall
Top defenders
1
Alexander BarbozaBotafogo-RJ
74
2
Nahuel Ferraresi Botafogo-RJ
70
3
Lucas FreitasVasco da Gama
64
4
MaiconVasco da Gama
63
5
Arthur ChavesBotafogo-RJ
56
Control
Top playmakers
1
Thiago MendesVasco da Gama
87
2
Óscar RomeroBotafogo-RJ
73
3
Marlon Freitas Botafogo-RJ
70
4
DaniloBotafogo-RJ
67
5
Domingos AndradeBotafogo-RJ
64
Bad Boys
Most likely to get booked
1
Mateo PonteBotafogo-RJ
1
Aggression 60
2
AllanBotafogo-RJ
1
Aggression 59
3
Patrick de PaulaBotafogo-RJ
1
Aggression 49
4
Joaquín CorreaBotafogo-RJ
1
Aggression 52
5
Philippe Coutinho Vasco da Gama
1
Aggression 20
Power Rankings
Strongest overall
1
Lucas EmanuelBotafogo-RJ
92
2
Claudio SpinelliVasco da Gama
92
3
Matheus MartinsBotafogo-RJ
89
4
Facundo ColidioVasco da Gama
89
5
Kadir BarriaBotafogo-RJ
80
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Botafogo-RJ vs Vasco da Gama 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 Vasco da Gama 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 Vasco da Gama 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.