FPLBench

The brief

The problem

Fantasy football models are easy to evaluate badly. Statistics from the same gameweek can leak the answer, double gameweeks can contaminate each other's history, and a live score can still change while FPL reviews it. Most published models are graded on data they could not have had at the deadline.

Our approach

The data pipeline shifts every performance feature so a row only sees what was known before its first fixture, including in double gameweeks. FPL's post-match expected points are kept as a baseline and never used for training. LightGBM models predict minutes and points, and a calibrated classifier predicts the new defensive-contribution bonus. The weekly forecast is committed to git before the deadline, and a guard rejects later overwrites. Scores are written only after FPL marks the gameweek finished and data-checked. A transfer planner picks moves for the model's own FPL team. Injured, suspended or doubtful players (flagged below 75%) can never start or be bought. The bench is ordered by simulating 4,000 scenarios under FPL's autosub rules, because the bench scored 9, 17, 14, 25 and 16 points in the first five gameweeks.