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Player stats · 25/26

Oxford United v Southampton

Your slip follows you between games.

How often each Oxford United and Southampton 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 Oxford United v Southampton: Adam Armstrong (Southampton) tops the visitors for 1+ shots on target — 8 of 10 (80%). Raw hit rates from recent matches, not odds.

Window
Last
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.

1+ shots

Oxford United
Southampton
Adam ArmstrongF 90%9 of 10 Pro 🔒
Leo ScienzaF 90%9 of 10 Pro 🔒
Tom FellowsM 80%8 of 10 Pro 🔒
Ryan ManningM 70%7 of 10 Pro 🔒
Finn AzazF 70%7 of 10 Pro 🔒
Jay RobinsonF 60%6 of 10 Pro 🔒
Cameron ArcherF 60%6 of 10 Pro 🔒

2+ shots

Oxford United
No Oxford United player in this window.
Southampton
Adam ArmstrongF 80%8 of 10 Pro 🔒
Leo ScienzaF 70%7 of 10 Pro 🔒
Finn AzazF 60%6 of 10 Pro 🔒

3+ shots

Oxford United
No Oxford United player in this window.
Southampton
Adam ArmstrongF 80%8 of 10 Pro 🔒

1+ shots on target

Oxford United
No Oxford United player in this window.
Southampton
Adam ArmstrongF 80%8 of 10 Pro 🔒
Leo ScienzaF 80%8 of 10 Pro 🔒
Finn AzazF 60%6 of 10 Pro 🔒

2+ shots on target

Oxford United
No Oxford United player in this window.
Southampton
Adam ArmstrongF 70%7 of 10 Pro 🔒

1+ fouls committed

Oxford United
Southampton
Flynn DownesM 80%8 of 10 Pro 🔒
Adam ArmstrongF 70%7 of 10 Pro 🔒
Caspar JanderM 60%6 of 10 Pro 🔒
Jay RobinsonF 60%6 of 10 Pro 🔒

2+ fouls committed

Oxford United
No Oxford United player in this window.
Southampton
Flynn DownesM 60%6 of 10 Pro 🔒

1+ fouls won

Oxford United
Tyler GoodrhamM 70%7 of 10 Pro 🔒
Nik PrelecF 70%7 of 10 Pro 🔒
Ciaron BrownD 60%6 of 10 Pro 🔒
Jack CurrieD 60%6 of 10 Pro 🔒
Filip KrastevM 60%6 of 10 Pro 🔒
Will LankshearF 60%6 of 10 Pro 🔒
Southampton
Leo ScienzaF 100%10 of 10 Pro 🔒
Ryan ManningM 90%9 of 10 Pro 🔒
Finn AzazF 80%8 of 10 Pro 🔒
Caspar JanderM 70%7 of 10 Pro 🔒
Tom FellowsM 70%7 of 10 Pro 🔒
Flynn DownesM 70%7 of 10 Pro 🔒

2+ fouls won

Oxford United
No Oxford United player in this window.
Southampton
Leo ScienzaF 90%9 of 10 Pro 🔒

3+ fouls won

Oxford United
No Oxford United player in this window.
Southampton
Leo ScienzaF 80%8 of 10 Pro 🔒

1+ goals

Oxford United
No Oxford United player in this window.
Southampton
Adam ArmstrongF 50%5 of 10 Stats only
Finn AzazF 50%5 of 10 Stats only
Leo ScienzaF 30%3 of 10 Stats only

1+ assists

Oxford United
No Oxford United player in this window.
Southampton
Adam ArmstrongF 30%3 of 10 Stats only
Finn AzazF 30%3 of 10 Stats only
Tom FellowsM 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
Leigh Doughty refereed this match 4.54cards/game 1.13×vs league 72games
Leigh Doughty'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.