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Player stats 22/23

SSC Napoli v Sampdoria

Your slip follows you between games.

How often each SSC Napoli and Sampdoria 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 SSC Napoli v Sampdoria: Victor Osimhen (SSC Napoli) leads the home side for 1+ shots on target — 9 of 10 (90%); Manolo Gabbiadini (Sampdoria) tops the visitors on 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 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.

SSC Napoli
Victor OsimhenF 100%10 of 10 Pro 🔒
Piotr ZielińskiM 90%9 of 10 Pro 🔒
Giacomo RaspadoriF 90%9 of 10 Pro 🔒
Giovanni Di LorenzoD 80%8 of 10 Pro 🔒
Frank AnguissaM 70%7 of 10 Pro 🔒
Eljif ElmasF 70%7 of 10 Pro 🔒
Sampdoria
Manolo GabbiadiniM 80%8 of 10 Pro 🔒
Mehdi LérisF 80%8 of 10 Pro 🔒
Fabio QuagliarellaF 70%7 of 10 Pro 🔒

SSC Napoli
Victor OsimhenF 90%9 of 10 Pro 🔒
Sampdoria
No Sampdoria player in this window.

SSC Napoli
Victor OsimhenF 80%8 of 10 Pro 🔒
Sampdoria
No Sampdoria player in this window.

SSC Napoli
Victor OsimhenF 90%9 of 10 Pro 🔒
Sampdoria
Manolo GabbiadiniM 60%6 of 10 Pro 🔒

SSC Napoli
Piotr ZielińskiM 80%8 of 10 Pro 🔒
Frank AnguissaM 80%8 of 10 Pro 🔒
Mário RuiD 80%8 of 10 Pro 🔒
Amir RrahmaniD 70%7 of 10 Pro 🔒
Victor OsimhenF 70%7 of 10 Pro 🔒
Eljif ElmasF 60%6 of 10 Pro 🔒
Sampdoria
Mehdi LérisF 100%10 of 10 Pro 🔒
Tomás RincónM 90%9 of 10 Pro 🔒
Bruno AmioneD 80%8 of 10 Pro 🔒
Manolo GabbiadiniM 70%7 of 10 Pro 🔒
Koray GünterD 60%6 of 10 Pro 🔒
Nicola MurruD 60%6 of 10 Pro 🔒
Lorenzo MalagridaM 60%3 of 5 Pro 🔒

SSC Napoli
No SSC Napoli player in this window.
Sampdoria
Tomás RincónM 60%6 of 10 Pro 🔒
Mehdi LérisF 60%6 of 10 Pro 🔒

SSC Napoli
Frank AnguissaM 90%9 of 10 Pro 🔒
Mário RuiD 90%9 of 10 Pro 🔒
Stanislav LobotkaM 70%7 of 10 Pro 🔒
Giovanni Di LorenzoD 70%7 of 10 Pro 🔒
Victor OsimhenF 60%6 of 10 Pro 🔒
Giacomo RaspadoriF 60%6 of 10 Pro 🔒
Sampdoria
Manolo GabbiadiniM 80%8 of 10 Pro 🔒
Mehdi LérisF 80%8 of 10 Pro 🔒
Bruno AmioneD 80%8 of 10 Pro 🔒
Fabio QuagliarellaF 60%6 of 10 Pro 🔒
Tommaso AugelloM 60%6 of 10 Pro 🔒

SSC Napoli
Frank AnguissaM 60%6 of 10 Pro 🔒
Sampdoria
Manolo GabbiadiniM 70%7 of 10 Pro 🔒

SSC Napoli
Giovanni Di LorenzoD 90%9 of 10 Pro 🔒
Mário RuiD 90%9 of 10 Pro 🔒
Stanislav LobotkaM 70%7 of 10 Pro 🔒
Frank AnguissaM 60%6 of 10 Pro 🔒
Eljif ElmasF 60%6 of 10 Pro 🔒
Sampdoria
Tomás RincónM 80%8 of 10 Pro 🔒
Mehdi LérisF 80%8 of 10 Pro 🔒
Bruno AmioneD 80%8 of 10 Pro 🔒
Alessandro ZanoliD 70%7 of 10 Pro 🔒
Manolo GabbiadiniM 60%6 of 10 Pro 🔒

SSC Napoli
Giovanni Di LorenzoD 60%6 of 10 Pro 🔒
Mário RuiD 60%6 of 10 Pro 🔒
Sampdoria
Mehdi LérisF 70%7 of 10 Pro 🔒

SSC Napoli
Victor OsimhenF 40%4 of 10 Stats only
Sampdoria
No Sampdoria player in this window.

SSC Napoli
No SSC Napoli player in this window.
Sampdoria
Martin TurkG 100%3 of 3 Stats only

SSC Napoli
No SSC Napoli player in this window.
Sampdoria
Martin TurkG 100%3 of 3 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-31% cards vs the league average
Ermanno Feliciani refereed this match 2.90cards a gameleague 4.19 42games
Ermanno Feliciani'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.