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Player stats 23/24

Olympique de Marseille v Brighton

Your slip follows you between games.

How often each Olympique de Marseille and Brighton player has hit the lines bookmakers price — 1+ shots on target, 2+ shots, 1+ fouls, a card — across their recent matches. How hit rates work ↓

Going into Olympique de Marseille v Brighton: Ismaïla Sarr (Olympique de Marseille) leads the home side for 1+ shots on target — 7 of 10 (70%); Evan Ferguson (Brighton) tops the visitors on 7 of 10 (70%). Raw hit rates from recent matches, not odds.

Window
Last
What a window counts

Hit rates count the most recent completed games, newest first — reaching back into earlier seasons when the current one is short, and into games for a previous club, including in another league we cover.

Market
Line
Team
How hit rates and windows work

Each row's hit rate is the share of a player's games in the window where the bet would have landed. These are 25/26 figures from completed matches: Last N is their last N games; Season is their whole 25/26; H2H is only games against this opponent.

Olympique de Marseille
VitinhaF 100%10 of 10 Pro 🔒
Ismaïla SarrF 80%8 of 10 Pro 🔒
Iliman NdiayeF 80%8 of 10 Pro 🔒
Joaquín CorreaF 70%7 of 10 Pro 🔒
Jordan VeretoutM 60%6 of 10 Pro 🔒
Chancel MbembaD 60%6 of 10 Pro 🔒
Renan LodiD 60%6 of 10 Pro 🔒
Brighton
Solly MarchM 100%10 of 10 Pro 🔒
João PedroF 100%10 of 10 Pro 🔒
Kaoru MitomaM 90%9 of 10 Pro 🔒
Evan FergusonF 90%9 of 10 Pro 🔒
Danny WelbeckF 80%8 of 10 Pro 🔒
Ansu FatiM 80%8 of 10 Pro 🔒
Billy GilmourM 60%6 of 10 Pro 🔒

Olympique de Marseille
Ismaïla SarrF 70%7 of 10 Pro 🔒
VitinhaF 60%6 of 10 Pro 🔒
Brighton
Ansu FatiM 70%7 of 10 Pro 🔒
Solly MarchM 60%6 of 10 Pro 🔒
Kaoru MitomaM 60%6 of 10 Pro 🔒
João PedroF 60%6 of 10 Pro 🔒
Evan FergusonF 60%6 of 10 Pro 🔒

Olympique de Marseille
Ismaïla SarrF 70%7 of 10 Pro 🔒
Brighton
Evan FergusonF 70%7 of 10 Pro 🔒

Olympique de Marseille
Valentin RongierM 80%8 of 10 Pro 🔒
Renan LodiD 80%8 of 10 Pro 🔒
Joaquín CorreaF 70%7 of 10 Pro 🔒
Iliman NdiayeF 70%7 of 10 Pro 🔒
Leonardo BalerdiD 70%7 of 10 Pro 🔒
Jordan VeretoutM 60%6 of 10 Pro 🔒
Chancel MbembaD 60%6 of 10 Pro 🔒
Ismaïla SarrF 60%6 of 10 Pro 🔒
Brighton
Joël VeltmanD 90%9 of 10 Pro 🔒
Solly MarchM 80%8 of 10 Pro 🔒
Pascal GroßM 80%8 of 10 Pro 🔒
Kaoru MitomaM 60%6 of 10 Pro 🔒
Evan FergusonF 60%6 of 10 Pro 🔒

Olympique de Marseille
Leonardo BalerdiD 70%7 of 10 Pro 🔒
Brighton
No Brighton player in this window.

Olympique de Marseille
Ismaïla SarrF 100%10 of 10 Pro 🔒
Amine HaritM 70%7 of 10 Pro 🔒
Iliman NdiayeF 70%7 of 10 Pro 🔒
Leonardo BalerdiD 70%7 of 10 Pro 🔒
Jordan VeretoutM 60%6 of 10 Pro 🔒
Renan LodiD 60%6 of 10 Pro 🔒
Azzedine OunahiM 60%6 of 10 Pro 🔒
Brighton
Kaoru MitomaM 100%10 of 10 Pro 🔒
João PedroF 80%8 of 10 Pro 🔒
Solly MarchM 70%7 of 10 Pro 🔒
Ansu FatiM 70%7 of 10 Pro 🔒
Evan FergusonF 70%7 of 10 Pro 🔒
Joël VeltmanD 60%6 of 10 Pro 🔒
Danny WelbeckF 60%6 of 10 Pro 🔒

Olympique de Marseille
Ismaïla SarrF 60%6 of 10 Pro 🔒
Brighton
João PedroF 60%6 of 10 Pro 🔒

Olympique de Marseille
Jonathan ClaussD 100%10 of 10 Pro 🔒
Jordan VeretoutM 90%9 of 10 Pro 🔒
Chancel MbembaD 90%9 of 10 Pro 🔒
Valentin RongierM 90%9 of 10 Pro 🔒
Renan LodiD 80%8 of 10 Pro 🔒
Leonardo BalerdiD 60%6 of 10 Pro 🔒
Brighton
Solly MarchM 90%9 of 10 Pro 🔒
Pascal GroßM 90%9 of 10 Pro 🔒
João PedroF 80%8 of 10 Pro 🔒
Mahmoud DahoudM 70%7 of 10 Pro 🔒
Joël VeltmanD 60%6 of 10 Pro 🔒
Jan Paul van HeckeD 60%6 of 10 Pro 🔒

Olympique de Marseille
Jonathan ClaussD 60%6 of 10 Pro 🔒
Leonardo BalerdiD 60%6 of 10 Pro 🔒
Brighton
No Brighton player in this window.

Olympique de Marseille
Ismaïla SarrF 30%3 of 10 Stats only
Brighton
Pascal GroßM 30%3 of 10 Stats only
Ansu FatiM 30%3 of 10 Stats only
João PedroF 30%3 of 10 Stats only
Evan FergusonF 30%3 of 10 Stats only

Olympique de Marseille
Iliman NdiayeF 30%3 of 10 Stats only
Brighton
Kaoru MitomaM 40%4 of 10 Stats only

Olympique de Marseille
Pau LópezG 60%6 of 10 Stats only
Brighton
Jason SteeleG 60%6 of 10 Stats only

🔒 Model is the paid layer — the model's +EV verdict on each line, per fixture in the tool. The hit rates here are free.

Tick players above to build your own slip — it follows you across games, and you can share it from the tray below.

New to these markets? The player stats guide explains what each line means and how to read a hit rate, and the glossary defines the terms.

Match officials
Mykola Balakin refereed this match

7 matches on record — too few to quote a card rate against. See the record

Form is only half the picture. A player hitting a line 5 of 5 can still be poor value if the true chance is lower than the streak suggests. The SharpXI tool pairs every one of these with the model's real probability — and flags the runs it doesn't back, so you're not chasing a streak about to regress. That honest verdict is the layer we're building into the tool.

Hit rates are raw recent form from public match data, for context — not a prediction or a guarantee. 18+ — please gamble responsibly.