Benfica’s commanding attacking profile and expected territorial pressure point toward a lively afternoon, with Alverca’s vulnerable defensive shape offering openings. The visitors may contribute little, but sustained home pressure should carry the contest beyond the low-scoring threshold.
Match GoalsOver 2.5
Nejlepší tip
Domácí výhra
70%
Přesný výsledek
Výborná
2-0
12.4%
7.00
Výborná
1-0
11.2%
9.50
2-1
9.6%
10.00
3-0
9.2%
7.50
1-1
8.6%
15.00
3-1
7.1%
11.00
4-0
5.1%
10.00
0-0
5.1%
23.00
170%
1.17TOP
X18%
7.50
212%
13.00
1X88%
X230%
1282%
Combined Bet Builder
3 legs
Benfica’s fierce attack should keep Alverca pinned back and the corners piling up, but their leaky defence leaves the visitors a route to strike. With Benfica creating chance after chance and both sides capable of finding the net, a lively, high-scoring contest looks the likely script—both teams to score, goals over the line and corners to follow.
1Both Teams to ScoreYes
2Match GoalsOver 3.5
3Corners Over/UnderOver 8.5
Confirmed XI4-5-1
24
Soares
6
Bah
44
Araújo
2
Lenglet
26
Dahl
8
Aursnes
36
Palhinha
27
Silva
10
Sudakov
25
Prestianni
14
Pavlidis
Impact Player Hot Head
SL Benfica FC30 hráči
55.0/ 99Průměrný
Nejlepší
1Manu Silva MID91
2Franjo IvanovićFWD88
3AnísioFWD86
Alverca28 hráči
49.1/ 99Průměrný
Nejlepší
1Zé RafaelMID72
2Matheus França FWD72
3Vasco MoreiraMID67
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
AnísioSL Benfica FC
99
2
Jhon Durán SL Benfica FC
95
3
Franjo IvanovićSL Benfica FC
85
4
Vangelis PavlidisSL Benfica FC
82
5
Dodi LukébakioSL Benfica FC
74
Zeď
Nejlepší obránci
1
Yaya BojangAlverca
68
2
Sergi Gómez SolàAlverca
61
3
Alessandro CircatiSL Benfica FC
54
4
José NetoSL Benfica FC
51
5
Steven BaseyaAlverca
51
Kontrola
Nejlepší tvůrci hry
1
Manu Silva SL Benfica FC
87
2
Fredrik AursnesSL Benfica FC
81
3
Zé RafaelAlverca
74
4
Enzo BarrenecheaSL Benfica FC
69
5
João PalhinhaSL Benfica FC
69
Zlobivci
Nejpravděpodobnější žlutá karta
1
Gianluca PrestianniSL Benfica FC
1
Agresivita 50
2
Jhon Durán SL Benfica FC
1
Agresivita 99
3
Yaya BojangAlverca
1
Agresivita 25
4
Nabil TouaiziAlverca
1
Agresivita 26
5
Tomás AraújoSL Benfica FC
7
Agresivita 38
Žebříček síly
Nejsilnější celkově
1
Manu Silva SL Benfica FC
91
2
Franjo IvanovićSL Benfica FC
88
3
AnísioSL Benfica FC
86
4
João RegoSL Benfica FC
74
5
Bruma SL Benfica FC
73
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for SL Benfica FC vs Alverca 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 SL Benfica FC vs Alverca 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 SL Benfica 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 SL Benfica FC vs Alverca 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 SL Benfica 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.