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Player stats 26/27

FC Bayern München v Hamburger SV

Your slip follows you between games.

How often each FC Bayern München and Hamburger SV 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 FC Bayern München v Hamburger SV on Sat 3 Apr: Michael Olise (FC Bayern München) leads the home side for 1+ shots on target — 9 of 10 (90%); Fábio Vieira (Hamburger SV) tops the visitors on 6 of 10 (60%). Raw hit rates from recent matches, not odds.

Predicted line-up — not the team sheet Our best guess at the shape, from recent selections. Team sheets usually land about an hour before kick-off.
What sits behind these numbers

Line-ups aren't confirmed, so the players shown are a likely XI from each club's recent selections — injuries and suspensions are filtered out where we know them. Hit rates are their recent form, not a forecast for this match.

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.

FC Bayern München
Jamal MusialaM 100%10 of 10 Pro 🔒
Serge GnabryF 100%10 of 10 Pro 🔒
Michael OliseF 100%10 of 10 Pro 🔒
Ismael SaibariM 100%4 of 4 Pro 🔒
Harry KaneF 90%9 of 10 Pro 🔒
Lennart KarlM 90%9 of 10 Pro 🔒
Luis DíazF 90%9 of 10 Pro 🔒
Tom BischofM 70%7 of 10 Pro 🔒
Sacha BoeyD 60%6 of 10 Pro 🔒
Hamburger SV
Patson DakaF 90%9 of 10 Pro 🔒
Fábio VieiraF 90%9 of 10 Pro 🔒
Terem MoffiF 80%8 of 10 Pro 🔒
Albert GrønbækF 70%7 of 10 Pro 🔒
Otto StangeF 60%6 of 10 Pro 🔒
Nicolás CapaldoD 60%6 of 10 Pro 🔒

FC Bayern München
Jamal MusialaM 80%8 of 10 Pro 🔒
Harry KaneF 80%8 of 10 Pro 🔒
Serge GnabryF 80%8 of 10 Pro 🔒
Luis DíazF 70%7 of 10 Pro 🔒
Michael OliseF 70%7 of 10 Pro 🔒
Hamburger SV
Patson DakaF 70%7 of 10 Pro 🔒

FC Bayern München
Harry KaneF 60%6 of 10 Pro 🔒
Michael OliseF 60%6 of 10 Pro 🔒
Hamburger SV
Patson DakaF 60%6 of 10 Pro 🔒

FC Bayern München
Michael OliseF 90%9 of 10 Pro 🔒
Harry KaneF 80%8 of 10 Pro 🔒
Lennart KarlM 60%6 of 10 Pro 🔒
Luis DíazF 60%6 of 10 Pro 🔒
Hamburger SV
Fábio VieiraF 60%6 of 10 Pro 🔒

FC Bayern München
Hiroki ItōD 70%7 of 10 Pro 🔒
Luis DíazF 70%7 of 10 Pro 🔒
Sacha BoeyD 70%7 of 10 Pro 🔒
Konrad LaimerD 60%6 of 10 Pro 🔒
Dayot UpamecanoD 60%6 of 10 Pro 🔒
Hamburger SV
Nicolás CapaldoD 90%9 of 10 Pro 🔒
Nicolai RembergM 80%8 of 10 Pro 🔒
Miro MuheimD 80%8 of 10 Pro 🔒
Bilal NadirM 70%7 of 10 Pro 🔒
Jordan TorunarighaD 60%6 of 10 Pro 🔒
Warmed OmariD 60%6 of 10 Pro 🔒

FC Bayern München
No FC Bayern München player in this window.
Hamburger SV
Nicolás CapaldoD 70%7 of 10 Pro 🔒

FC Bayern München
Michael OliseF 80%8 of 10 Pro 🔒
Jamal MusialaM 60%6 of 10 Pro 🔒
Nathaniel BrownD 60%6 of 10 Pro 🔒
Hamburger SV
Fábio VieiraF 100%10 of 10 Pro 🔒
Zakaria El OuahdiD 100%3 of 3 Pro 🔒
Miro MuheimD 90%9 of 10 Pro 🔒
Albert GrønbækF 80%8 of 10 Pro 🔒
Patson DakaF 80%8 of 10 Pro 🔒
Nicolai RembergM 60%6 of 10 Pro 🔒
Otto StangeF 60%6 of 10 Pro 🔒
Nicolás CapaldoD 60%6 of 10 Pro 🔒

FC Bayern München
Michael OliseF 60%6 of 10 Pro 🔒
Hamburger SV
Fábio VieiraF 90%9 of 10 Pro 🔒
Zakaria El OuahdiD 67%2 of 3 Pro 🔒
Miro MuheimD 60%6 of 10 Pro 🔒

FC Bayern München
Konrad LaimerD 90%9 of 10 Pro 🔒
Dayot UpamecanoD 80%8 of 10 Pro 🔒
Nathaniel BrownD 70%7 of 10 Pro 🔒
Joshua KimmichM 70%7 of 10 Pro 🔒
Jonathan TahD 60%6 of 10 Pro 🔒
Kim Min-jaeD 60%6 of 10 Pro 🔒
Hamburger SV
Nicolás CapaldoD 90%9 of 10 Pro 🔒
Albert GrønbækF 80%8 of 10 Pro 🔒
Miro MuheimD 80%8 of 10 Pro 🔒
Jordan TorunarighaD 80%8 of 10 Pro 🔒
Fábio VieiraF 70%7 of 10 Pro 🔒
Warmed OmariD 70%7 of 10 Pro 🔒
Zakaria El OuahdiD 67%2 of 3 Pro 🔒
Nicolai RembergM 60%6 of 10 Pro 🔒
Sebastiaan BornauwD 60%6 of 10 Pro 🔒

FC Bayern München
Dayot UpamecanoD 80%8 of 10 Pro 🔒
Nathaniel BrownD 70%7 of 10 Pro 🔒
Hamburger SV
Nicolás CapaldoD 70%7 of 10 Pro 🔒
Albert GrønbækF 60%6 of 10 Pro 🔒

FC Bayern München
No FC Bayern München player in this window.
Hamburger SV
Nicolás CapaldoD 70%7 of 10 Pro 🔒

FC Bayern München
Harry KaneF 60%6 of 10 Stats only
Michael OliseF 60%6 of 10 Stats only
Jamal MusialaM 30%3 of 10 Stats only
Serge GnabryF 30%3 of 10 Stats only
Hamburger SV
No Hamburger SV player in this window.

FC Bayern München
Konrad LaimerD 40%4 of 10 Stats only
Jamal MusialaM 30%3 of 10 Stats only
Lennart KarlM 30%3 of 10 Stats only
Alphonso DaviesD 30%3 of 10 Stats only
Hamburger SV
Albert GrønbækF 30%3 of 10 Stats only

FC Bayern München
No FC Bayern München player in this window.
Hamburger SV
Daniel FernandesG 70%7 of 10 Stats only

FC Bayern München
No FC Bayern München player in this window.
Hamburger SV
Daniel FernandesG 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

Not appointed yet — referees are usually confirmed two to three days before kick-off. See the referee panel

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.