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Player stats 26/27

Atlético Madrid v FC Bayern München

Your slip follows you between games.

How often each Atlético Madrid and FC Bayern München 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 Atlético Madrid v FC Bayern München on Tue 3 Nov: Alejandro Grimaldo (Atlético Madrid) leads the home side for 1+ shots on target — 7 of 10 (70%); Michael Olise (FC Bayern München) tops the visitors on 9 of 10 (90%). 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.

Atlético Madrid
Alejandro GrimaldoD 100%10 of 10 Pro 🔒
Alexander SørlothF 90%9 of 10 Pro 🔒
Alex BaenaM 90%9 of 10 Pro 🔒
Jonathan DavidF 80%8 of 10 Pro 🔒
Ademola LookmanF 70%7 of 10 Pro 🔒
Cristian RomeroD 70%7 of 10 Pro 🔒
Kang-in LeeM 70%7 of 10 Pro 🔒
Julián AlvarezF 70%7 of 10 Pro 🔒
Marc PubillD 60%6 of 10 Pro 🔒
Giuliano SimeoneF 60%6 of 10 Pro 🔒
Pablo BarriosM 60%6 of 10 Pro 🔒
Rodrigo MendozaM 60%6 of 10 Pro 🔒
FC Bayern München
Jamal MusialaM 100%10 of 10 Pro 🔒
Ismael SaibariM 100%10 of 10 Pro 🔒
Serge GnabryF 100%10 of 10 Pro 🔒
Michael OliseF 100%10 of 10 Pro 🔒
Harry KaneF 90%9 of 10 Pro 🔒
Lennart KarlM 90%9 of 10 Pro 🔒
Tom BischofM 80%8 of 10 Pro 🔒
Luis DíazF 80%8 of 10 Pro 🔒
Sacha BoeyD 60%6 of 10 Pro 🔒

Atlético Madrid
Alejandro GrimaldoD 70%7 of 10 Pro 🔒
Alex BaenaM 70%7 of 10 Pro 🔒
Jonathan DavidF 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 🔒
Ismael SaibariM 70%7 of 10 Pro 🔒
Michael OliseF 70%7 of 10 Pro 🔒
Luis DíazF 60%6 of 10 Pro 🔒

Atlético Madrid
No Atlético Madrid player in this window.
FC Bayern München
Michael OliseF 70%7 of 10 Pro 🔒
Harry KaneF 60%6 of 10 Pro 🔒

Atlético Madrid
Alejandro GrimaldoD 70%7 of 10 Pro 🔒
Alex BaenaM 70%7 of 10 Pro 🔒
FC Bayern München
Michael OliseF 90%9 of 10 Pro 🔒
Harry KaneF 80%8 of 10 Pro 🔒
Ismael SaibariM 60%6 of 10 Pro 🔒
Lennart KarlM 60%6 of 10 Pro 🔒
Luis DíazF 60%6 of 10 Pro 🔒

Atlético Madrid
Marc PubillD 70%7 of 10 Pro 🔒
Rodrigo MendozaM 70%7 of 10 Pro 🔒
Marcos LlorenteD 70%7 of 10 Pro 🔒
Ademola LookmanF 70%7 of 10 Pro 🔒
Cristian RomeroD 70%7 of 10 Pro 🔒
Morten HjulmandM 70%7 of 10 Pro 🔒
Johnny CardosoM 70%7 of 10 Pro 🔒
Robin Le NormandD 60%6 of 10 Pro 🔒
Alex BaenaM 60%6 of 10 Pro 🔒
FC Bayern München
Hiroki ItōD 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 🔒
Luis DíazF 60%6 of 10 Pro 🔒

Atlético Madrid
Cristian RomeroD 80%8 of 10 Pro 🔒
Morten HjulmandM 80%8 of 10 Pro 🔒
Arnau OrtizF 80%4 of 5 Pro 🔒
Pablo BarriosM 70%7 of 10 Pro 🔒
Rodrigo MendozaM 60%6 of 10 Pro 🔒
Ademola LookmanF 60%6 of 10 Pro 🔒
Alex BaenaM 60%6 of 10 Pro 🔒
Kang-in LeeM 60%6 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 🔒
Luis DíazF 60%6 of 10 Pro 🔒

Atlético Madrid
No Atlético Madrid player in this window.
FC Bayern München
Michael OliseF 60%6 of 10 Pro 🔒

Atlético Madrid
Alejandro GrimaldoD 100%10 of 10 Pro 🔒
Marcos LlorenteD 90%9 of 10 Pro 🔒
Marc PubillD 80%8 of 10 Pro 🔒
Pablo BarriosM 80%8 of 10 Pro 🔒
Giuliano SimeoneF 70%7 of 10 Pro 🔒
Robin Le NormandD 70%7 of 10 Pro 🔒
Cristian RomeroD 70%7 of 10 Pro 🔒
Morten HjulmandM 70%7 of 10 Pro 🔒
Kang-in LeeM 70%7 of 10 Pro 🔒
Ademola LookmanF 60%6 of 10 Pro 🔒
KokeM 60%6 of 10 Pro 🔒
Johnny CardosoM 60%6 of 10 Pro 🔒
FC Bayern München
Konrad LaimerD 90%9 of 10 Pro 🔒
Dayot UpamecanoD 80%8 of 10 Pro 🔒
Joshua KimmichM 70%7 of 10 Pro 🔒
Tom BischofM 60%6 of 10 Pro 🔒
Nathaniel BrownD 60%6 of 10 Pro 🔒
Kim Min-jaeD 60%6 of 10 Pro 🔒

Atlético Madrid
Alejandro GrimaldoD 90%9 of 10 Pro 🔒
Giuliano SimeoneF 60%6 of 10 Pro 🔒
FC Bayern München
Dayot UpamecanoD 80%8 of 10 Pro 🔒
Nathaniel BrownD 60%6 of 10 Pro 🔒

Atlético Madrid
Jonathan DavidF 40%4 of 10 Stats only
Alejandro GrimaldoD 30%3 of 10 Stats only
Alex BaenaM 30%3 of 10 Stats only
FC Bayern München
Harry KaneF 50%5 of 10 Stats only
Michael OliseF 50%5 of 10 Stats only
Ismael SaibariM 40%4 of 10 Stats only
Jamal MusialaM 30%3 of 10 Stats only

Atlético Madrid
No Atlético Madrid player in this window.
FC Bayern München
Konrad LaimerD 40%4 of 10 Stats only
Jamal MusialaM 30%3 of 10 Stats only
Ismael SaibariM 30%3 of 10 Stats only
Lennart KarlM 30%3 of 10 Stats only
Alphonso DaviesD 30%3 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.