Liverpool’s home pressure and steady chance creation should meet Brighton’s lively attacking threat in an open contest. Despite capable defenses, both sides have enough firepower to turn the match into a sustained, end-to-end goal spectacle.
Match GoalsOver 3.5
Nejlepší tip
OBÁ SKÓRUJÍ
55%
Přesný výsledek
Výborná
1-1
12%
7.50
Výborná
1-0
9.6%
13.00
2-1
9%
10.00
0-1
7.9%
17.00
1-2
7.5%
13.00
2-0
7.2%
15.00
0-0
6.4%
17.00
2-2
5.6%
12.00
143%
2.15TOP
X25%
3.60
232%
3.25
1X68%
X257%
1275%
Combined Bet Builder
3 legs
Liverpool’s 1.71 xG at home, combined with Brighton’s 1.39, points to a lively contest with over 2.5 goals in reach. The home side’s edge should carry them to victory, while Isak is a credible anytime-scorer pick in a match offering chances at both ends.
1Match WinnerLiverpool FC
2Match GoalsOver 3.5
3GoalscorersAnytime
Confirmed XI4-4-2
1
Alisson
33
Araujo
5
Jacquet
4
Dijk
6
Kerkez
38
Gravenberch
10
Allister
7
Wirtz
18
Gakpo
29
Barcola
9
Isak
Impact Player Hot Head
Liverpool FC27 hráči
52.9/ 99Průměrný
Nejlepší
1Trey NyoniMID75
2Curtis JonesMID74
3Hugo EkitikéFWD74
Brighton & Hove Albion33 hráči
53.5/ 99Průměrný
Nejlepší
1Michael SvobodaDEF92
2Luka VuskovicDEF80
3Stefanos TzimasFWD66
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
Federico Chiesa Liverpool FC
90
2
Charalampos KostoulasBrighton & Hove Albion
89
3
Lewis KoumasLiverpool FC
71
4
Hugo EkitikéLiverpool FC
65
5
Alexander IsakLiverpool FC
63
Zeď
Nejlepší obránci
1
Michael SvobodaBrighton & Hove Albion
99
2
Virgil van Dijk Liverpool FC
69
3
Luka VuskovicBrighton & Hove Albion
68
4
Pascal StruijkBrighton & Hove Albion
66
5
Igor JulioBrighton & Hove Albion
63
Kontrola
Nejlepší tvůrci hry
1
Curtis JonesLiverpool FC
87
2
Dominik SzoboszlaiLiverpool FC
67
3
Trey NyoniLiverpool FC
64
4
Pascal GroßBrighton & Hove Albion
61
5
Florian WirtzLiverpool FC
59
Zlobivci
Nejpravděpodobnější žlutá karta
1
Federico Chiesa Liverpool FC
1
Agresivita 99
2
Lewis Dunk Brighton & Hove Albion
1
Agresivita 27
3
Charalampos KostoulasBrighton & Hove Albion
2
Agresivita 67
4
Promise David Brighton & Hove Albion
16
Agresivita 82
5
Ronald AraujoLiverpool FC
19
Agresivita 45
Žebříček síly
Nejsilnější celkově
1
Michael SvobodaBrighton & Hove Albion
92
2
Luka VuskovicBrighton & Hove Albion
80
3
Trey NyoniLiverpool FC
75
4
Curtis JonesLiverpool FC
74
5
Hugo EkitikéLiverpool FC
74
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Liverpool FC vs Brighton & Hove Albion 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 Liverpool FC vs Brighton & Hove Albion 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 Liverpool 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 Liverpool FC vs Brighton & Hove Albion 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 Liverpool 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.