FOOTGolden Boot › Serie A
2026-27
Serie A Golden Boot 2026-27: AI race predictions
Who wins the Serie A Golden Boot 2026-27? The official scorer table plus 10,000 AI season simulations: win probabilities, projected final tallies and the record chase — updated after every round.
10 scorers on the official board · probabilities from 10,000 season simulations · kick-off switches to your time zone
| # | Player | Team | Goals | Assists | Apps | Left | Proj. | Win % |
|---|---|---|---|---|---|---|---|---|
| 1 | Antonio Raimondo | Frosinone Calcio | 7 | 0 | 8 | 4 | 10.0 | 27% |
| 2 | Gustavo Varela | AC Monza | 7 (1P) | 1 | 7 | 4 | 9.8 | 22% |
| 3 | Donyell Malen | AS Roma | 6 | 1 | 7 | 4 | 9.8 | 26% |
| 4 | Nikola Krstović | Atalanta BC | 6 | 1 | 8 | 4 | 8.7 | 9% |
| 5 | Marcus Thuram-Ulien | FC Internazionale Milano | 5 | 2 | 8 | 4 | 8.0 | 6% |
| 6 | Anastasios Douvikas | Como 1907 | 5 | 0 | 8 | 4 | 7.8 | 4% |
| 7 | Lautaro Martínez | FC Internazionale Milano | 4 | 0 | 6 | 4 | 7.2 | 3% |
| 8 | Adrien Rabiot | AC Milan | 4 | 3 | 7 | 5 | 7.0 | 2% |
| 9 | Daniel Maldini | Cagliari Calcio | 4 (1P) | 0 | 8 | 4 | 5.5 | <1% |
| 10 | Hakan Çalhanoğlu | FC Internazionale Milano | 3 (1P) | 0 | 6 | 4 | 5.8 | <1% |
All-time single-season record: 36 goals — Gonzalo Higuaín, 2015-16.
How the projections work
The Footalytics AI engine simulates the rest of the season 10,000 times. Machine-rated opponent strength weights every remaining fixture, Bayesian calibration keeps small samples honest, injuries and rotation are priced in as uncertainty — refreshed automatically after every round by the same engine that grades every match prediction in public.
Assumptions: scoring rates from this season's official scorer table, opponent strength from team ratings, an appearance probability per game, and no January transfers. Probabilities are model projections, not facts — the table itself is official data.