Lille’s home ambition should create sustained pressure, while Lens bring the sharper attacking edge and enough threat to punish openings. With both sides capable of generating chances, this rivalry appears poised to deliver an open, goal-rich contest.
Match GoalsOver 2.5
Лучший выбор
ОБЕ ЗАБЬЮТ
54%
Точный счёт
Отличная
1-1
12.3%
7.00
Отличная
0-1
10.2%
11.00
1-2
8.9%
10.00
1-0
8.5%
10.00
2-1
7.4%
9.50
0-2
7.4%
15.00
0-0
7%
15.00
2-2
5.4%
12.00
131%
2.30
X26%
3.60
243%
2.75TOP
1X57%
X269%
1274%
Экспресс
4 выборов
Lille’s third-place standing and defense rated 22% above average make the home side or draw the logical platform, while Lens’ attack power is 67% above average and gives Hamza Igamane a credible scoring route. Combined xG is 2.61 and projected corners total 9.36, supporting Over 2.5 goals and Over 8.5 corners.
1Double ChanceLOSC Lille or Draw
2Match GoalsOver 2.5
3GoalscorersAnytime
4Corners Over/UnderOver 8.5
Confirmed XI4-5-1
1
Özer
38
Goffi
3
Ngoy
4
Alexsandro
15
Perraud
21
André
6
Bentaleb
8
Mbappé
17
Mukau
10
Haraldsson
9
Giroud
Impact Player Hot Head
LOSC Lille34 игроков
49.8/ 99Средний
Лучшие
1Noah EdjoumaFWD93
2Alexsandro DEF87
3Ayase UedaFWD77
Lens36 игроков
53.3/ 99Средний
Лучшие
1Rayan FofanaFWD84
2Mamadou SangaréMID72
3Odsonne ÉdouardFWD69
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Noah EdjoumaLOSC Lille
99
2
Rayan FofanaLens
80
3
Junior KadileLens
73
4
Gaëtan PerrinLOSC Lille
72
5
Ayase UedaLOSC Lille
70
Стена
Лучшие защитники
1
Alexsandro LOSC Lille
87
2
Isaac CossierLOSC Lille
77
3
Chancel MbembaLOSC Lille
73
4
Ismaëlo GaniouLens
58
5
Jonathan GraditLens
57
Контроль
Лучшие плеймейкеры
1
Nabil BentalebLOSC Lille
81
2
Mamadou SangaréLens
80
3
Benjamin André LOSC Lille
69
4
Mezian SoaresLens
59
5
Adrien ThomassonLens
57
Хулиганы
Склонны к карточкам
1
Aïssa MandiLOSC Lille
1
Агрессия 25
2
Maxima GoffiLOSC Lille
1
Агрессия 58
3
Nathan NgoyLOSC Lille
1
Агрессия 26
4
Maurits KjærgaardLOSC Lille
1
Агрессия 37
5
Gaëtan PerrinLOSC Lille
1
Агрессия 99
Рейтинг силы
Сильнейшие в целом
1
Noah EdjoumaLOSC Lille
93
2
Alexsandro LOSC Lille
87
3
Rayan FofanaLens
84
4
Ayase UedaLOSC Lille
77
5
Soriba DiaouneLOSC Lille
75
Часто задаваемые вопросы
Our Poisson model calculates the probability of every possible scoreline for LOSC Lille vs Lens 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 LOSC Lille vs Lens 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 LOSC Lille 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 LOSC Lille vs Lens 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 LOSC Lille 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.