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Player stats · 23/24

Paris Saint-Germain v Borussia Dortmund

How often each Paris Saint-Germain and Borussia Dortmund 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 Paris Saint-Germain v Borussia Dortmund: Kylian Mbappé (Paris Saint-Germain) leads the home side for 1+ shots on target — 6 of 10 (60%); Niclas Füllkrug (Borussia Dortmund) tops the visitors on 9 of 10 (90%). 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.

Paris Saint-Germain
Bradley BarcolaF 100%10 of 10 Pro 🔒
Kylian MbappéF 90%9 of 10 Pro 🔒
Achraf HakimiD 80%8 of 10 Pro 🔒
Gonçalo RamosF 80%8 of 10 Pro 🔒
VitinhaM 70%7 of 10 Pro 🔒
Fabián RuizM 70%7 of 10 Pro 🔒
Borussia Dortmund
Niclas FüllkrugF 100%10 of 10 Pro 🔒
Karim AdeyemiM 90%9 of 10 Pro 🔒
Marcel SabitzerM 80%8 of 10 Pro 🔒
Ian MaatsenD 70%7 of 10 Pro 🔒
Marco ReusM 70%7 of 10 Pro 🔒
Julian RyersonD 60%6 of 10 Pro 🔒
Emre CanM 60%6 of 10 Pro 🔒
Felix NmechaM 60%6 of 10 Pro 🔒

Paris Saint-Germain
Kylian MbappéF 70%7 of 10 Pro 🔒
Borussia Dortmund
Karim AdeyemiM 60%6 of 10 Pro 🔒

Paris Saint-Germain
Kylian MbappéF 60%6 of 10 Pro 🔒
Gonçalo RamosF 60%6 of 10 Pro 🔒
Borussia Dortmund
Niclas FüllkrugF 90%9 of 10 Pro 🔒
Karim AdeyemiM 70%7 of 10 Pro 🔒
Marcel SabitzerM 60%6 of 10 Pro 🔒
Marco ReusM 60%6 of 10 Pro 🔒

Paris Saint-Germain
Lucas BeraldoD 60%6 of 10 Pro 🔒
Warren Zaïre-EmeryM 60%6 of 10 Pro 🔒
Bradley BarcolaF 60%6 of 10 Pro 🔒
Borussia Dortmund
Ian MaatsenD 80%8 of 10 Pro 🔒
Julian RyersonD 70%7 of 10 Pro 🔒
Niclas FüllkrugF 70%7 of 10 Pro 🔒
Emre CanM 60%6 of 10 Pro 🔒

Paris Saint-Germain
Kylian MbappéF 80%8 of 10 Pro 🔒
Marco AsensioF 70%7 of 10 Pro 🔒
Ousmane DembéléF 60%6 of 10 Pro 🔒
Borussia Dortmund
Julian RyersonD 80%8 of 10 Pro 🔒
Niclas FüllkrugF 70%7 of 10 Pro 🔒
Marcel SabitzerM 60%6 of 10 Pro 🔒
Marco ReusM 60%6 of 10 Pro 🔒
Felix NmechaM 60%6 of 10 Pro 🔒

Paris Saint-Germain
Gonçalo RamosF 60%6 of 10 Stats only
Kylian MbappéF 40%4 of 10 Stats only
Borussia Dortmund
Niclas FüllkrugF 30%3 of 10 Stats only
Karim AdeyemiM 30%3 of 10 Stats only

Paris Saint-Germain
Kylian MbappéF 40%4 of 10 Stats only
Bradley BarcolaF 40%4 of 10 Stats only
Nuno MendesD 30%3 of 10 Stats only
Ousmane DembéléF 30%3 of 10 Stats only
Marco AsensioF 30%3 of 10 Stats only
Borussia Dortmund
Julian BrandtM 30%3 of 10 Stats only

Paris Saint-Germain
Gianluigi DonnarummaG 90%9 of 10 Stats only
Borussia Dortmund
Gregor KobelG 60%6 of 10 Stats only

Paris Saint-Germain
Gianluigi DonnarummaG 90%9 of 10 Stats only
Borussia Dortmund
No Borussia Dortmund player in this window.

Paris Saint-Germain
Gianluigi DonnarummaG 70%7 of 10 Stats only
Borussia Dortmund
No Borussia Dortmund 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
Daniele Orsato refereed this match

13 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.