Over 9.5 corners looks the logical lean: Jablonec’s attack generates 17% more corners than average, while Brighton’s defense is 5% weaker in this area. With the top-ranked side likely to carry momentum and keep Jablonec under pressure, both teams have routes to repeated wide attacks and clearances—setting up a lively corner count in this Conference League clash.
Corners Over/UnderOver 9.5
Best Pick
BTTS
55%
Correct Score
Top
1-1
12.2%
13.00
Top
1-0
9.1%
29.00
0-1
8.9%
9.50
2-1
8.4%
29.00
1-2
8.2%
10.00
0-0
6.7%
21.00
2-0
6.3%
51.00
0-2
5.9%
7.00
138%
12.00TOP
X26%
7.50
236%
1.18
1X64%
X262%
1274%
Combined Bet Builder
3 legs
Brighton’s powerful attack should set the tempo, while Jablonec’s home crowd can spur a reply despite the tough matchup. With both teams to score looking likely, sustained pressure at both ends points to a lively, high-scoring contest; Brighton’s chance creation and Jablonec’s share of the corner threat make over three and a half goals and over eight and a half corners a compelling fit.
1Both Teams to ScoreYes
2Match GoalsOver 3.5
3Corners Over/UnderOver 9.5
Confirmed XI4-5-1
1
Hanus
18
Cedidla
4
Tekijaski
15
Pavlovic
20
Slama
13
Sedlacek
6
Okeke
7
Chanturishvili
17
Moubarak
21
Polidar
9
Rusek
Impact Player Hot Head
FK Jablonec31 players
49.3/ 99Average
Top Rated
1Richard SedlacekMID84
2Dusan PavlovicDEF67
3Nelson OkekeMID66
Brighton & Hove Albion30 players
55.1/ 99Strong
Top Rated
1Michael SvobodaDEF90
2Luka VuskovicDEF77
3Charalampos KostoulasFWD70
Player Rankings
Snipers
Top goal threats
1
Charalampos KostoulasBrighton & Hove Albion
98
2
Saidou Alioum MoubarakFK Jablonec
73
3
Stefanos TzimasBrighton & Hove Albion
68
4
Jan ChramostaFK Jablonec
65
5
Filip VechetaFK Jablonec
61
Wall
Top defenders
1
Michael SvobodaBrighton & Hove Albion
96
2
Nemanja Tekijaski FK Jablonec
68
3
Dusan PavlovicFK Jablonec
64
4
Luka VuskovicBrighton & Hove Albion
61
5
Filip NovakFK Jablonec
59
Control
Top playmakers
1
Filip ZorvanFK Jablonec
76
2
Richard SedlacekFK Jablonec
75
3
Pascal GroßBrighton & Hove Albion
68
4
Nelson OkekeFK Jablonec
57
5
Matt O'RileyBrighton & Hove Albion
54
Bad Boys
Most likely to get booked
1
Samuel ObinayaFK Jablonec
1
Aggression 99
2
Saidou Alioum MoubarakFK Jablonec
1
Aggression 62
3
Lewis Dunk Brighton & Hove Albion
1
Aggression 27
4
Charalampos KostoulasBrighton & Hove Albion
3
Aggression 67
5
Jiri SlamaFK Jablonec
8
Aggression 68
Power Rankings
Strongest overall
1
Michael SvobodaBrighton & Hove Albion
90
2
Richard SedlacekFK Jablonec
84
3
Luka VuskovicBrighton & Hove Albion
77
4
Charalampos KostoulasBrighton & Hove Albion
70
5
Stefanos TzimasBrighton & Hove Albion
70
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for FK Jablonec 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 FK Jablonec 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 FK Jablonec 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 FK Jablonec 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 FK Jablonec 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.