Aston Villa’s home momentum and sharper attack should eventually crack Viking’s defensive wall, but the visitors have enough threat to make their mark rather than simply absorb pressure. With Villa pushing forward and spaces opening in a lively contest, both teams to score looks the most natural outcome.
Both Teams to ScoreYes
Best Pick
BTTS
65%
Correct Score
Top
1-1
10%
13.00
Top
2-1
8.9%
10.00
1-2
7.6%
34.00
2-2
6.8%
19.00
1-0
6.6%
13.00
2-0
5.8%
9.50
0-1
5.6%
41.00
3-1
5.2%
10.00
144%
1.22TOP
X23%
6.50
233%
12.00
1X67%
X256%
1277%
Combined Bet Builder
5 legs
Aston Villa’s 2.44 xG and 0.88 first-half xG point to an early breakthrough and a strong route to over 2.5 goals. Viking’s 1.02 xG gives both teams to score a credible path, while their defensive resilience may keep Villa pressing and drive corners beyond 8.5. Tammy Abraham is well placed to cap Villa’s expected attacking pressure with an anytime goal.
1Match GoalsOver 2.5
2Both Teams to ScoreYes
3First Half Over/UnderOver 0.5
4Corners Over/UnderOver 9.5
5GoalscorersAnytime
Confirmed XI3-5-2
1
Suzuki
2
Cash
3
Lindelöf
14
Torres
26
Bogarde
44
Manzambi
6
Barkley
8
Kamara
7
McGinn
19
Mbaye
11
Jackson
Impact Player Hot Head
Aston Villa FC30 players
48.7/ 99Average
Top Rated
1Ibrahim MbayeFWD91
2Ross Barkley MID69
3João GomesMID68
Viking FK32 players
51.2/ 99Average
Top Rated
1Henrik FalchenerDEF77
2Henrik HeggheimDEF73
3Erik Botheim FWD69
Player Rankings
Snipers
Top goal threats
1
Ibrahim MbayeAston Villa FC
98
2
Ollie WatkinsAston Villa FC
78
3
Erik Botheim Viking FK
70
4
Nicolas JacksonAston Villa FC
62
5
Nick D'AgostinoViking FK
58
Wall
Top defenders
1
Henrik FalchenerViking FK
99
2
Gianni Stensness Viking FK
75
3
Anders BærtelsenViking FK
72
4
Sondre BjørsholViking FK
71
5
Viljar VevatneViking FK
70
Control
Top playmakers
1
Henrik BjørdalViking FK
65
2
Ross Barkley Aston Villa FC
64
3
João GomesAston Villa FC
61
4
Leon GoretzkaAston Villa FC
58
5
Boubacar KamaraAston Villa FC
57
Bad Boys
Most likely to get booked
1
Nicolas JacksonAston Villa FC
1
Aggression 30
2
Edvin AustbøViking FK
1
Aggression 31
3
Lamare BogardeAston Villa FC
4
Aggression 75
4
Ruben AlteViking FK
10
Aggression 35
5
Alejandro GarnachoAston Villa FC
11
Aggression 25
Power Rankings
Strongest overall
1
Ibrahim MbayeAston Villa FC
91
2
Henrik FalchenerViking FK
77
3
Henrik HeggheimViking FK
73
4
Ross Barkley Aston Villa FC
69
5
Erik Botheim Viking FK
69
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Aston Villa FC vs Viking FK 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 Aston Villa FC vs Viking FK 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 Aston Villa FC 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 Aston Villa FC vs Viking FK 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 Aston Villa FC 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.