France
Who's most likely to win the Ligue 1Golden 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 Ligue 1 final standings probabilities.
| Player | NT | G | xG | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|---|
 E. Lepaul | 🇫🇷 | 20 | 20.0 | 100.0 | ||||
 M. Greenwood | 🏴 | 16 | 16.0 | 100.0 | ||||
 J. Panichelli | 🇦🇷 | 16 | 16.0 | 100.0 | ||||
 F. Balogun | 🇺🇸 | 13 | 13.0 | 100.0 | ||||
 O. Édouard | 🇫🇷 | 12 | 12.0 | 100.0 | ||||
 W. Saïd | 🇫🇷 | 12 | 12.0 | |||||
 L. Sinayoko | 🇲🇱 | 12 | 12.0 | |||||
 P. Šulc | 🇨🇿 | 11 | 11.0 | |||||
 B. Barcola | 🇫🇷 | 11 | 11.0 | |||||
 F. Thauvin | 🇫🇷 | 11 | 11.0 |
