Bundesliga per 90 stats 2025/2026
Every Bundesliga player's season divided by the minutes he played, which is the only basis a regular and a substitute can be compared on.
Ranked from 270 minutes played.
Harry Kane leads on expected goal involvement per 90 minutes with 1.17, over 2382 minutes played.
Showing 351–391 of 391 players
| # | Player | Club | Min | G/90 | A/90 | xG/90 | xA/90 | xGI/90 |
|---|---|---|---|---|---|---|---|---|
| 349 | Benedikt Gimber | 1. FC Heidenheim | 1,448 | 0.00 | 0.00 | 0.02 | 0.02 | 0.04 |
| 349 | Niklas Süle | Borussia Dortmund | 487 | 0.00 | 0.18 | 0.01 | 0.04 | 0.04 |
| 349 | Bruno Ogbus | SC Freiburg | 1,186 | 0.00 | 0.00 | 0.03 | 0.02 | 0.04 |
| 349 | Moritz Jenz | VfL Wolfsburg | 1,789 | 0.05 | 0.00 | 0.03 | 0.01 | 0.04 |
| 349 | El Chadaille Bitshiabu | RB Leipzig | 672 | 0.00 | 0.00 | 0.02 | 0.02 | 0.04 |
| 356 | Adam Dźwigała | FC St. Pauli | 1,295 | 0.07 | 0.07 | 0.01 | 0.02 | 0.03 |
| 356 | Finn Jeltsch | VfB Stuttgart | 1,512 | 0.00 | 0.06 | 0.01 | 0.02 | 0.03 |
| 356 | Jenson Seelt | VfL Wolfsburg | 696 | 0.00 | 0.00 | 0.02 | 0.00 | 0.03 |
| 356 | Ameen Al-Dakhil | VfB Stuttgart | 368 | 0.00 | 0.00 | 0.01 | 0.01 | 0.03 |
| 360 | Warmed Omari | Hamburger SV | 1,607 | 0.00 | 0.06 | 0.01 | 0.02 | 0.02 |
| 360 | Rav van den Berg | 1. FC Köln | 1,138 | 0.00 | 0.08 | 0.01 | 0.01 | 0.02 |
| 362 | Finn Dahmen | FC Augsburg | 2,970 | 0.00 | 0.00 | 0.01 | 0.00 | 0.01 |
| 362 | Daniel Fernandes | Hamburger SV | 2,970 | 0.00 | 0.00 | 0.01 | 0.00 | 0.01 |
| 362 | Maximilian Rosenfelder | SC Freiburg | 507 | 0.00 | 0.00 | 0.00 | 0.01 | 0.01 |
| 365 | Kamil Grabara | VfL Wolfsburg | 3,270 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| — | Alexander Nübel | VfB Stuttgart | 3,060 | 0.00 | 0.03 | — | 0.00 | — |
| — | Carl Klaus | 1. FC Union Berlin | 329 | 0.00 | 0.00 | — | 0.00 | — |
| — | Daniel Batz | 1. FSV Mainz 05 | 1,890 | 0.00 | 0.00 | — | 0.00 | — |
| — | Diant Ramaj | 1. FC Heidenheim | 2,790 | 0.00 | 0.03 | — | 0.00 | — |
| — | Dominique Heintz | 1. FC Köln | 398 | 0.00 | 0.00 | — | 0.02 | — |
| — | Frank Feller | 1. FC Heidenheim | 270 | 0.00 | 0.00 | — | 0.00 | — |
| — | Frederik Rønnow | 1. FC Union Berlin | 2,641 | 0.00 | 0.00 | — | 0.01 | — |
| — | Gregor Kobel | Borussia Dortmund | 3,060 | 0.00 | 0.00 | — | 0.00 | — |
| — | Janis Blaswich | Bayer 04 Leverkusen | 930 | 0.00 | 0.00 | — | 0.00 | — |
| — | Jonas Urbig | FC Bayern München | 1,110 | 0.00 | 0.00 | — | 0.00 | — |
| — | Jordy Makengo | SC Freiburg | 1,189 | 0.00 | 0.08 | — | 0.08 | — |
| — | Kauã Santos | Eintracht Frankfurt | 1,085 | 0.00 | 0.00 | — | 0.00 | — |
| — | Lasse Riess | 1. FSV Mainz 05 | 291 | 0.00 | 0.00 | — | 0.00 | — |
| — | Maarten Vandevoordt | RB Leipzig | 1,051 | 0.00 | 0.00 | — | 0.00 | — |
| — | Manuel Neuer | FC Bayern München | 1,860 | 0.00 | 0.00 | — | 0.00 | — |
| — | Mark Flekken | Bayer 04 Leverkusen | 2,130 | 0.00 | 0.00 | — | 0.00 | — |
| — | Marvin Schwäbe | 1. FC Köln | 3,060 | 0.00 | 0.00 | — | 0.01 | — |
| — | Michael Zetterer | Eintracht Frankfurt | 1,975 | 0.00 | 0.00 | — | 0.00 | — |
| — | Mio Backhaus | SV Werder Bremen | 2,880 | 0.00 | 0.00 | — | 0.00 | — |
| — | Moritz Nicolas | Borussia M'gladbach | 3,060 | 0.00 | 0.00 | — | 0.00 | — |
| — | Nikola Vasilj | FC St. Pauli | 3,060 | 0.00 | 0.00 | — | 0.00 | — |
| — | Noah Atubolu | SC Freiburg | 3,060 | 0.00 | 0.00 | — | 0.01 | — |
| — | Oliver Baumann | TSG Hoffenheim | 3,060 | 0.00 | 0.00 | — | 0.01 | — |
| — | Péter Gulácsi | RB Leipzig | 2,009 | 0.00 | 0.00 | — | 0.00 | — |
| — | Robin Zentner | 1. FSV Mainz 05 | 877 | 0.00 | 0.00 | — | 0.01 | — |
| — | Timo Hübers | 1. FC Köln | 669 | 0.00 | 0.00 | — | 0.01 | — |
- under 90 minutes
About these figures What each column counts, and which feed it was counted from. Show Hide
- Min
- Minutes played.
- G/90
- Goals per 90 minutes played.
- A/90
- Assists per 90 minutes played.
- xG/90
- Expected goals per 90 minutes played.
- xA/90
- Expected assists per 90 minutes played.
- xGI/90
- Expected goal involvement per 90 minutes played.
Appearances, minutes, goals, assists and shots on this page are summed over the Bundesliga matches we hold per-player figures for — the same matches the expected figures are summed over, so the two can be read against each other.
Learn how xgEdge calculates these figures →