Benfica’s +54% attacking edge points to a strong scoring platform, while Lech’s attack is still +8% above baseline—enough to threaten rather than simply defend. Despite both sides’ stronger-than-average defensive ratings, Benfica’s firepower should force an open contest, with chances for goals at both ends making Over 3.5 as clear favourite the most logical outcome.
Match GoalsOver 3.5
Nejlepší tip
Domácí výhra
62%
Přesný výsledek
Výborná
2-0
10.2%
8.00
Výborná
2-1
10%
11.00
1-0
10%
12.00
1-1
9.8%
17.00
3-0
6.9%
7.50
3-1
6.8%
11.00
0-0
4.9%
29.00
2-2
4.9%
29.00
162%
1.14TOP
X21%
9.00
217%
15.00
1X83%
X238%
1279%
Combined Bet Builder
3 legs
Benfica’s 2.18 xG and +54% attack power point to sustained pressure against Lech’s modest 0.89 xG threat. That attacking edge makes a Benfica win the likeliest outcome, with Pavlidis well placed to finish and the hosts’ firepower capable of driving the match beyond 3.5 goals.
1Match WinnerSL Benfica FC
2GoalscorersAnytime
3Match GoalsOver 3.5
Confirmed XI4-5-1
1
Trubin
6
Bah
3
Circati
44
Araújo
34
Karouani
8
Aursnes
16
Silva
27
Silva
30
Echeverri
21
Schjelderup
14
Pavlidis
Impact Player Hot Head
SL Benfica FC36 hráči
54.1/ 99Průměrný
Nejlepší
1Manu Silva MID94
2Franjo IvanovićFWD87
3AnísioFWD86
Lech Poznan24 hráči
53.7/ 99Průměrný
Nejlepší
1Yannick AgneroFWD77
2Radoslaw Murawski MID74
3Mikael Ishak FWD65
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
AnísioSL Benfica FC
99
2
Jhon Durán SL Benfica FC
98
3
Franjo IvanovićSL Benfica FC
84
4
Vangelis PavlidisSL Benfica FC
80
5
Mikael Ishak Lech Poznan
78
Zeď
Nejlepší obránci
1
Terry YegbeLech Poznan
63
2
João MoutinhoLech Poznan
57
3
Alessandro CircatiSL Benfica FC
54
4
Wojciech MonkaLech Poznan
54
5
José NetoSL Benfica FC
52
Kontrola
Nejlepší tvůrci hry
1
Manu Silva SL Benfica FC
92
2
Diogo Ferreira PriosteSL Benfica FC
90
3
Fredrik AursnesSL Benfica FC
79
4
João PalhinhaSL Benfica FC
73
5
Enzo BarrenecheaSL Benfica FC
69
Zlobivci
Nejpravděpodobnější žlutá karta
1
Gianluca PrestianniSL Benfica FC
1
Agresivita 49
2
Jhon Durán SL Benfica FC
1
Agresivita 99
3
Tomás AraújoSL Benfica FC
5
Agresivita 38
4
Wojciech MonkaLech Poznan
21
Agresivita 20
5
Henrique AraújoSL Benfica FC
25
Agresivita 9
Žebříček síly
Nejsilnější celkově
1
Manu Silva SL Benfica FC
94
2
Franjo IvanovićSL Benfica FC
87
3
AnísioSL Benfica FC
86
4
Diogo Ferreira PriosteSL Benfica FC
83
5
Yannick AgneroLech Poznan
77
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for SL Benfica FC vs Lech Poznan 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 Lech Poznan 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 Lech Poznan 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.