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
Nejlepší tip
OBÁ SKÓRUJÍ
58%
Přesný výsledek
Výborná
1-1
10.8%
7.50
Výborná
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%
Combined Bet Builder
3 legs
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
Marseille33 hráči
52.9/ 99Průměrný
Nejlepší
1Faris MoumbagnaFWD93
2Pierre-Emile HøjbjergMID82
3Arthur VermeerenMID71
Toulouse27 hráči
51.2/ 99Průměrný
Nejlepší
1Julián VignoloFWD91
2Cristian Cásseres Jr.MID77
3Casper TengstedtFWD68
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
Faris MoumbagnaMarseille
99
2
Julián VignoloToulouse
96
3
Casper TengstedtToulouse
79
4
Keyliane AbdallahMarseille
76
5
Mason GreenwoodMarseille
75
Zeď
Nejlepší obránci
1
Nayef AguerdMarseille
73
2
CJ Egan-RileyMarseille
70
3
Charlie CresswellToulouse
69
4
Rasmus Nicolaisen Toulouse
67
5
Bamo MeïtéMarseille
63
Kontrola
Nejlepší tvůrci hry
1
Cristian Cásseres Jr.Toulouse
95
2
Pierre-Emile HøjbjergMarseille
93
3
Geoffrey KondogbiaMarseille
74
4
Niklas Schmidt Toulouse
74
5
Bilal NadirMarseille
73
Zlobivci
Nejpravděpodobnější žlutá karta
1
Facundo MedinaMarseille
1
Agresivita 52
2
Angel GomesMarseille
1
Agresivita 50
3
Quinten TimberMarseille
1
Agresivita 52
4
Mario SauerToulouse
1
Agresivita 67
5
Niklas Schmidt Toulouse
1
Agresivita 50
Žebříček síly
Nejsilnější celkově
1
Faris MoumbagnaMarseille
93
2
Julián VignoloToulouse
91
3
Pierre-Emile HøjbjergMarseille
82
4
Cristian Cásseres Jr.Toulouse
77
5
Arthur VermeerenMarseille
71
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for 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 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 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 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 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.