Germany
Who's most likely to win the BundesligaGolden Boot, from 1,000 Monte Carlo simulations. Each player's current goals-per-90 rate is projected forward over their team's remaining fixtures, with minutes-per-appearance scaling the expected workload to match their actual usage pattern.
See the wider season picture in our Bundesliga final standings probabilities.
| Player | NT | G | xG | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|---|
 H. Kane | 🏴 | 36 | 36.0 | 100.0 | ||||
 D. Undav | 🇩🇪 | 19 | 19.0 | 100.0 | ||||
 S. Guirassy | 🇬🇳 | 17 | 17.0 | 100.0 | ||||
 P. Schick | 🇨🇿 | 16 | 16.0 | 100.0 | ||||
 M. Olise | 🇫🇷 | 15 | 15.0 | 100.0 | ||||
 L. Díaz | 🇨🇴 | 15 | 15.0 | |||||
 A. Kramarić | 🇭🇷 | 14 | 14.0 | |||||
 C. Baumgartner | 🇦🇹 | 13 | 13.0 | |||||
 H. Tabaković | 🇨🇭 | 13 | 13.0 | |||||
 S. El Mala | 🇩🇪 | 13 | 13.0 |
