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
Migliore scelta
GOL DI ENTRAMBE
55%
Risultato esatto
Eccellente
1-1
12.2%
13.00
Eccellente
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%
1.17
1X64%
X262%
1274%
Combinata
3 selezioni
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
Jablonec31 giocatori
49.3/ 99Medio
Migliori
1Richard SedlacekMID84
2Dusan PavlovicDEF67
3Nelson OkekeMID66
Brighton & Hove Albion30 giocatori
55.1/ 99Forte
Migliori
1Michael SvobodaDEF90
2Luka VuskovicDEF77
3Charalampos KostoulasFWD70
Classifiche giocatori
Cecchini
Maggior minaccia di gol
1
Charalampos KostoulasBrighton & Hove Albion
98
2
Saidou Alioum MoubarakJablonec
73
3
Stefanos TzimasBrighton & Hove Albion
68
4
Jan ChramostaJablonec
65
5
Filip VechetaJablonec
61
Muro
Migliori difensori
1
Michael SvobodaBrighton & Hove Albion
96
2
Nemanja Tekijaski Jablonec
68
3
Dusan PavlovicJablonec
64
4
Luka VuskovicBrighton & Hove Albion
61
5
Filip NovakJablonec
59
Controllo
Migliori registi
1
Filip ZorvanJablonec
76
2
Richard SedlacekJablonec
75
3
Pascal GroßBrighton & Hove Albion
68
4
Nelson OkekeJablonec
57
5
Matt O'RileyBrighton & Hove Albion
54
Cattivi ragazzi
Più propensi ai cartellini
1
Samuel ObinayaJablonec
1
Aggressività 99
2
Saidou Alioum MoubarakJablonec
1
Aggressività 62
3
Lewis Dunk Brighton & Hove Albion
1
Aggressività 27
4
Charalampos KostoulasBrighton & Hove Albion
3
Aggressività 67
5
Jiri SlamaJablonec
8
Aggressività 68
Classifica potenza
Più forti in assoluto
1
Michael SvobodaBrighton & Hove Albion
90
2
Richard SedlacekJablonec
84
3
Luka VuskovicBrighton & Hove Albion
77
4
Charalampos KostoulasBrighton & Hove Albion
70
5
Stefanos TzimasBrighton & Hove Albion
70
Domande frequenti
Our Poisson model calculates the probability of every possible scoreline for 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 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 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 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 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.