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Player stats 26/27

Atlético Madrid v Osasuna

Your slip follows you between games.

How often each Atlético Madrid and Osasuna 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 Osasuna: Ante Budimir (Osasuna) tops the visitors for 1+ shots on target — 8 of 10 (80%). 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 26/27 figures from completed matches: Last N is their last N games; Season is their whole 26/27; H2H is only games against this opponent.

Atlético Madrid
Alejandro GrimaldoD 100%10 of 10 Pro 🔒
Ademola LookmanF 80%8 of 10 Pro 🔒
Alex BaenaM 70%7 of 10 Pro 🔒
Kang-in LeeM 70%7 of 10 Pro 🔒
Cristian RomeroD 60%6 of 10 Pro 🔒
Jonathan DavidF 60%6 of 10 Pro 🔒
Osasuna
Ante BudimirF 100%10 of 10 Pro 🔒
Rubén GarcíaM 70%7 of 10 Pro 🔒
Lucas TorróM 60%6 of 10 Pro 🔒
Romain Del CastilloF 60%6 of 10 Pro 🔒

Atlético Madrid
Alejandro GrimaldoD 60%6 of 10 Pro 🔒
Osasuna
Ante BudimirF 60%6 of 10 Pro 🔒

Atlético Madrid
No Atlético Madrid player in this window.
Osasuna
Ante BudimirF 60%6 of 10 Pro 🔒

Atlético Madrid
No Atlético Madrid player in this window.
Osasuna
Ante BudimirF 80%8 of 10 Pro 🔒

Atlético Madrid
Marcos LlorenteD 90%9 of 10 Pro 🔒
Morten HjulmandM 80%8 of 10 Pro 🔒
Johnny CardosoM 80%8 of 10 Pro 🔒
Marc PubillD 60%6 of 10 Pro 🔒
Ademola LookmanF 60%6 of 10 Pro 🔒
Cristian RomeroD 60%6 of 10 Pro 🔒
Osasuna
Ante BudimirF 80%8 of 10 Pro 🔒
Enzo BoyomoD 70%7 of 10 Pro 🔒
Lucas TorróM 70%7 of 10 Pro 🔒
Jon MoncayolaM 70%7 of 10 Pro 🔒
Abel BretonesD 60%6 of 10 Pro 🔒
Asier OsambelaM 60%6 of 10 Pro 🔒
Jonathan DubasinF 60%3 of 5 Pro 🔒

Atlético Madrid
Morten HjulmandM 80%8 of 10 Pro 🔒
Arnau OrtizF 75%3 of 4 Pro 🔒
Marc PubillD 70%7 of 10 Pro 🔒
Ademola LookmanF 70%7 of 10 Pro 🔒
Johnny CardosoM 70%7 of 10 Pro 🔒
Cristian RomeroD 60%6 of 10 Pro 🔒
Alex BaenaM 60%6 of 10 Pro 🔒
Osasuna
Ante BudimirF 80%8 of 10 Pro 🔒
Romain Del CastilloF 80%8 of 10 Pro 🔒
Kike BarjaF 60%6 of 10 Pro 🔒

Atlético Madrid
No Atlético Madrid player in this window.
Osasuna
Ante BudimirF 60%6 of 10 Pro 🔒

Atlético Madrid
Marc PubillD 90%9 of 10 Pro 🔒
Alejandro GrimaldoD 90%9 of 10 Pro 🔒
Marcos LlorenteD 90%9 of 10 Pro 🔒
Morten HjulmandM 90%9 of 10 Pro 🔒
Giuliano SimeoneF 80%8 of 10 Pro 🔒
Robin Le NormandD 70%7 of 10 Pro 🔒
Cristian RomeroD 70%7 of 10 Pro 🔒
KokeM 70%7 of 10 Pro 🔒
Johnny CardosoM 70%7 of 10 Pro 🔒
Jonathan DavidF 60%6 of 10 Pro 🔒
Osasuna
Jon MoncayolaM 100%10 of 10 Pro 🔒
Enzo BoyomoD 80%8 of 10 Pro 🔒
Abel BretonesD 70%7 of 10 Pro 🔒
Rubén GarcíaM 70%7 of 10 Pro 🔒
Romain Del CastilloF 70%7 of 10 Pro 🔒
Iñigo ArguibideD 60%6 of 10 Pro 🔒
Lucas TorróM 60%6 of 10 Pro 🔒

Atlético Madrid
Alejandro GrimaldoD 90%9 of 10 Pro 🔒
Giuliano SimeoneF 60%6 of 10 Pro 🔒
Morten HjulmandM 60%6 of 10 Pro 🔒
Osasuna
Jon MoncayolaM 80%8 of 10 Pro 🔒

Atlético Madrid
Giuliano SimeoneF 30%3 of 10 Stats only
Ademola LookmanF 30%3 of 10 Stats only
Osasuna
Ante BudimirF 40%4 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-12% cards vs the league average
Francisco Hernandez Maeso refereed this match 4.26cards a gameleague 4.86 58games
Francisco Hernandez Maeso's card 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.