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Player stats 23/24

Brighton v Olympique de Marseille

Your slip follows you between games.

How often each Brighton and Olympique de Marseille 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 Brighton v Olympique de Marseille: Simon Adingra (Brighton) leads the home side for 1+ shots on target — 6 of 10 (60%). 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.

Brighton
Kaoru MitomaM 100%10 of 10 Pro 🔒
João PedroF 90%9 of 10 Pro 🔒
Simon AdingraM 80%8 of 10 Pro 🔒
Pascal GroßM 80%8 of 10 Pro 🔒
Billy GilmourM 80%8 of 10 Pro 🔒
Facundo BuonanotteM 60%6 of 10 Pro 🔒
Lewis DunkD 60%6 of 10 Pro 🔒
Evan FergusonF 60%6 of 10 Pro 🔒
Olympique de Marseille
Amine HaritF 70%7 of 10 Pro 🔒
VitinhaF 60%6 of 10 Pro 🔒
Jordan VeretoutM 60%6 of 10 Pro 🔒
Iliman NdiayeF 60%6 of 10 Pro 🔒

Brighton
Simon AdingraM 60%6 of 10 Pro 🔒
Kaoru MitomaM 60%6 of 10 Pro 🔒
Olympique de Marseille
No Olympique de Marseille player in this window.

Brighton
Simon AdingraM 60%6 of 10 Pro 🔒
Kaoru MitomaM 60%6 of 10 Pro 🔒
Olympique de Marseille
No Olympique de Marseille player in this window.

Brighton
Billy GilmourM 80%8 of 10 Pro 🔒
Carlos BalebaM 70%7 of 10 Pro 🔒
James MilnerM 70%7 of 10 Pro 🔒
Simon AdingraM 60%6 of 10 Pro 🔒
Joël VeltmanD 60%6 of 10 Pro 🔒
Igor JúlioD 60%6 of 10 Pro 🔒
Olympique de Marseille
Renan LodiM 80%8 of 10 Pro 🔒
Chancel MbembaD 70%7 of 10 Pro 🔒
Geoffrey KondogbiaM 70%7 of 10 Pro 🔒
Jordan VeretoutM 60%6 of 10 Pro 🔒
Iliman NdiayeF 60%6 of 10 Pro 🔒
Leonardo BalerdiD 60%6 of 10 Pro 🔒
Azzedine OunahiM 60%6 of 10 Pro 🔒

Brighton
Facundo BuonanotteM 90%9 of 10 Pro 🔒
João PedroF 70%7 of 10 Pro 🔒
Evan FergusonF 70%7 of 10 Pro 🔒
Joël VeltmanD 60%6 of 10 Pro 🔒
Billy GilmourM 60%6 of 10 Pro 🔒
Kaoru MitomaM 60%6 of 10 Pro 🔒
Jan Paul van HeckeD 60%6 of 10 Pro 🔒
Olympique de Marseille
Amine HaritF 100%10 of 10 Pro 🔒
Renan LodiM 80%8 of 10 Pro 🔒
Azzedine OunahiM 80%8 of 10 Pro 🔒
Ismaïla SarrF 70%7 of 10 Pro 🔒
Iliman NdiayeF 60%6 of 10 Pro 🔒
Geoffrey KondogbiaM 60%6 of 10 Pro 🔒

Brighton
Joël VeltmanD 60%6 of 10 Pro 🔒
Olympique de Marseille
Amine HaritF 60%6 of 10 Pro 🔒

Brighton
No Brighton player in this window.
Olympique de Marseille
Amine HaritF 60%6 of 10 Pro 🔒

Brighton
James MilnerM 90%9 of 10 Pro 🔒
Carlos BalebaM 80%8 of 10 Pro 🔒
Simon AdingraM 70%7 of 10 Pro 🔒
Joël VeltmanD 70%7 of 10 Pro 🔒
Pascal GroßM 70%7 of 10 Pro 🔒
Jan Paul van HeckeD 70%7 of 10 Pro 🔒
Igor JúlioD 60%6 of 10 Pro 🔒
Billy GilmourM 60%6 of 10 Pro 🔒
Olympique de Marseille
Amir MurilloD 86%6 of 7 Pro 🔒
Jonathan ClaussM 80%8 of 10 Pro 🔒
Geoffrey KondogbiaM 80%8 of 10 Pro 🔒
VitinhaF 70%7 of 10 Pro 🔒
Ismaïla SarrF 70%7 of 10 Pro 🔒
Renan LodiM 70%7 of 10 Pro 🔒
Leonardo BalerdiD 70%7 of 10 Pro 🔒
Azzedine OunahiM 70%7 of 10 Pro 🔒
Chancel MbembaD 60%6 of 10 Pro 🔒

Brighton
Carlos BalebaM 60%6 of 10 Pro 🔒
Olympique de Marseille
Leonardo BalerdiD 70%7 of 10 Pro 🔒

Brighton
Simon AdingraM 30%3 of 10 Stats only
Olympique de Marseille
Pierre-Emerick AubameyangF 40%4 of 10 Stats only

Brighton
Pascal GroßM 40%4 of 10 Stats only
Olympique de Marseille
Pierre-Emerick AubameyangF 40%4 of 10 Stats only

Brighton
Jason SteeleG 60%6 of 10 Stats only
Olympique de Marseille
No Olympique de Marseille player in this window.

🔒 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
José María Sánchez Martínez refereed this match

10 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.