Luka Modrić of Real Madrid leads the FIFA Club World Cup expected goals charts in 2025, with 0.0 xG from 6 appearances. The boards here cover 672 players and sort on every column; expected goals for each club, with expected points, are on the FIFA Club World Cup xG table.
| # | Player | Team | Apps | Goals | xG | Goals minus xG |
|---|---|---|---|---|---|---|
| 1 | Luka Modrić | Real Madrid | 6 | 0 | 0.0 | 0.0 |
| 2 | Chung-yong Lee | Ulsan HD | 3 | 0 | 0.0 | 0.0 |
| 3 | Olivier Giroud | Los Angeles FC | 3 | 0 | 0.0 | 0.0 |
| 4 | Ander Herrera | Boca Juniors | 1 | 0 | 0.0 | 0.0 |
| 5 | Matteo Darmian | Inter | 4 | 0 | 0.0 | 0.0 |
| 6 | Serge Gnabry | FC Bayern München | 5 | 0 | 0.0 | 0.0 |
| 7 | Luis Suárez | Inter Miami | 4 | 1 | 0.0 | +1.0 |
| 8 | Harry Kane | FC Bayern München | 5 | 3 | 0.0 | +3.0 |
| 9 | Hugo Lloris | Los Angeles FC | 3 | 0 | 0.0 | 0.0 |
| 10 | Thibaut Courtois | Real Madrid | 6 | 0 | 0.0 | 0.0 |
| 11 | Manuel Lanzini | River Plate | 1 | 0 | 0.0 | 0.0 |
| 12 | Salomón Rondón | Pachuca | 3 | 0 | 0.0 | 0.0 |
| 13 | Nordin Amrabat | Wydad Casablanca | 3 | 0 | 0.0 | 0.0 |
| 14 | Nicolás Otamendi | Benfica | 4 | 1 | 0.0 | +1.0 |
| 15 | Henrikh Mkhitaryan | Inter | 4 | 0 | 0.0 | 0.0 |
| 16 | Nathan Aké | Manchester City | 2 | 0 | 0.0 | 0.0 |
| 17 | Trent Alexander-Arnold | Real Madrid | 5 | 0 | 0.0 | 0.0 |
| 18 | Ryan Kent | Seattle Sounders | 3 | 0 | 0.0 | 0.0 |
| 19 | Ángel Di María | Benfica | 4 | 4 | 0.0 | +4.0 |
| 20 | Kenedy | Pachuca | 3 | 0 | 0.0 | 0.0 |
| 21 | Guillermo Varela | Flamengo | 3 | 0 | 0.0 | 0.0 |
| 22 | Óscar Ustari | Inter Miami | 4 | 0 | 0.0 | 0.0 |
| 23 | Leroy Sané | FC Bayern München | 3 | 0 | 0.0 | 0.0 |
| 24 | İlkay Gündoğan | Manchester City | 4 | 2 | 0.0 | +2.0 |
| 25 | Tosin Adarabioyo | Chelsea | 4 | 1 | 0.0 | +1.0 |
| 26 | Albert Rusnák | Seattle Sounders | 3 | 1 | 0.0 | +1.0 |
| 27 | Lloyd Kelly | Juventus | 4 | 0 | 0.0 | 0.0 |
| 28 | Stefan de Vrij | Inter | 3 | 0 | 0.0 | 0.0 |
| 29 | Filip Kostić | Juventus | 2 | 0 | 0.0 | 0.0 |
| 30 | Jesús Corona | Monterrey | 3 | 1 | 0.0 | +1.0 |
| 31 | Alexander Sørloth | Atlético Madrid | 3 | 0 | 0.0 | 0.0 |
| 32 | M. Rayhi | Wydad Casablanca | 1 | 0 | 0.0 | 0.0 |
| 33 | Denzel Dumfries | Inter | 2 | 0 | 0.0 | 0.0 |
| 34 | Yaw Yeboah | Los Angeles FC | 2 | 0 | 0.0 | 0.0 |
| 35 | Bart Meijers | Wydad Casablanca | 3 | 0 | 0.0 | 0.0 |
| 36 | Teun Koopmeiners | Juventus | 4 | 1 | 0.0 | +1.0 |
| 37 | Thomas Müller | FC Bayern München | 5 | 2 | 0.0 | +2.0 |
| 38 | Manuel Neuer | FC Bayern München | 5 | 0 | 0.0 | 0.0 |
| 39 | Pascal Groß | Borussia Dortmund | 5 | 0 | 0.0 | 0.0 |
| 40 | Daniel Carvajal | Real Madrid | 1 | 0 | 0.0 | 0.0 |
| 41 | Niklas Süle | Borussia Dortmund | 4 | 0 | 0.0 | 0.0 |
| 42 | Leon Goretzka | FC Bayern München | 3 | 1 | 0.0 | +1.0 |
| 43 | Jonathan Tah | FC Bayern München | 5 | 0 | 0.0 | 0.0 |
| 44 | Antonio Rüdiger | Real Madrid | 5 | 0 | 0.0 | 0.0 |
| 45 | Genki Haraguchi | Urawa Reds | 2 | 0 | 0.0 | 0.0 |
| 46 | Julian Brandt | Borussia Dortmund | 5 | 0 | 0.0 | 0.0 |
| 47 | Yann Sommer | Inter | 4 | 0 | 0.0 | 0.0 |
| 48 | Luis Advíncula | Boca Juniors | 3 | 0 | 0.0 | 0.0 |
| 49 | Joshua Kimmich | FC Bayern München | 5 | 0 | 0.0 | 0.0 |
| 50 | Renato Sanches | Benfica | 3 | 1 | 0.0 | +1.0 |
Expected goals measure the quality of the chances a player gets, with every shot scored between 0 and 1 by how often shots like it are converted. A player's xG is those values added up, so the gap between the goals they scored and their xG shows whether they finished better or worse than their chances deserved. Underlying data is supplied by Sportmonks.
Expected goals measures the quality of the chances a player gets. Every shot is scored between 0 and 1 by how often shots like it are converted, and a player's xG is those values added up. A player on 8 xG has had chances a typical finisher would score about eight times from.
Goals minus xG. A positive number means the player has scored more than the quality of their chances suggested, a negative number means fewer. It is the quickest way to see who is finishing well and who is not.
Usually. Finishing skill is real but small and hard to sustain, so across a full season most players end up close to their expected goals. A large gap either way is more likely to close than to carry on, which makes it a guide rather than a guarantee.
Shot-level data is supplied by Sportmonks and updates after every finished match, usually within a few hours of full time. Each shot is credited to the player who took it. Providers train their models on different data, so our numbers will not match another site's exactly.