Marseille’s forceful home attack should create sustained pressure, while Toulouse bring enough forward threat to answer rather than merely absorb. With defensive vulnerabilities inviting mistakes, the match appears set for an open, chance-rich contest and likely goals beyond the modest threshold.
Match GoalsOver 2.5
Лучший выбор
ОБЕ ЗАБЬЮТ
58%
Точный счёт
Отличная
1-1
10.8%
7.50
Отличная
2-1
9.7%
8.50
1-0
9%
10.00
2-0
8.1%
11.00
1-2
6.4%
13.00
0-1
6%
15.00
2-2
5.8%
12.00
3-1
5.8%
13.00
152%
1.85TOP
X23%
3.80
225%
3.70
1X75%
X248%
1277%
Экспресс
3 выборов
Marseille’s 1.95 xG against Toulouse’s 1.05 points to a home edge and a likely three-plus-goal game. Toulouse’s +40% attack power could help drive the scoring total, but Marseille’s stronger overall outlook should prevail; Gouiri is a compelling anytime scorer to complete the builder.
1Match WinnerMarseille
2Match GoalsOver 2.5
3GoalscorersAnytime
Confirmed XI3-6-1
12
Lange
4
Egan-Riley
21
Aguerd
33
Emerson
22
Weah
6
Nadi
23
Højbjerg
77
Harit
8
Abdelli
14
Paixão
9
Gouiri
Impact Player Hot Head
Olympique Marseille33 игроков
52.9/ 99Средний
Лучшие
1Faris MoumbagnaFWD93
2Pierre-Emile HøjbjergMID82
3Arthur VermeerenMID71
Toulouse27 игроков
51.2/ 99Средний
Лучшие
1Julián VignoloFWD91
2Cristian Cásseres Jr.MID77
3Casper TengstedtFWD68
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Faris MoumbagnaOlympique Marseille
99
2
Julián VignoloToulouse
96
3
Casper TengstedtToulouse
79
4
Keyliane AbdallahOlympique Marseille
76
5
Mason GreenwoodOlympique Marseille
75
Стена
Лучшие защитники
1
Nayef AguerdOlympique Marseille
73
2
CJ Egan-RileyOlympique Marseille
70
3
Charlie CresswellToulouse
69
4
Rasmus Nicolaisen Toulouse
67
5
Bamo MeïtéOlympique Marseille
63
Контроль
Лучшие плеймейкеры
1
Cristian Cásseres Jr.Toulouse
95
2
Pierre-Emile HøjbjergOlympique Marseille
93
3
Geoffrey KondogbiaOlympique Marseille
74
4
Niklas Schmidt Toulouse
74
5
Bilal NadirOlympique Marseille
73
Хулиганы
Склонны к карточкам
1
Facundo MedinaOlympique Marseille
1
Агрессия 52
2
Angel GomesOlympique Marseille
1
Агрессия 50
3
Quinten TimberOlympique Marseille
1
Агрессия 52
4
Mario SauerToulouse
1
Агрессия 67
5
Niklas Schmidt Toulouse
1
Агрессия 50
Рейтинг силы
Сильнейшие в целом
1
Faris MoumbagnaOlympique Marseille
93
2
Julián VignoloToulouse
91
3
Pierre-Emile HøjbjergOlympique Marseille
82
4
Cristian Cásseres Jr.Toulouse
77
5
Arthur VermeerenOlympique Marseille
71
Часто задаваемые вопросы
Our Poisson model calculates the probability of every possible scoreline for Olympique Marseille vs Toulouse 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 Olympique Marseille vs Toulouse 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 Olympique Marseille 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 Olympique Marseille vs Toulouse 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 Olympique Marseille 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.