How predictions work
The technical layer, without taking over the homepage.
FPL Copilot blends historical FPL scoring, recent player form, and fixture context to generate weekly player projections. This page gives a recruiter-friendly view of the model inputs, evaluation snapshot, and data freshness without turning the whole app into a technical dashboard.
Inputs
Recent FPL performance, fixture difficulty, ownership, price, minutes, and rolling player form all help shape the weekly predictions.
Model flow
The app ingests FPL data, refreshes its warehouse tables, trains the latest model, and stores scored predictions for the recommendation and optimizer flows.
Why it matters
Predictions are most useful for tie-breakers: captaincy calls, shortlists, differentials, and budget-efficient squad construction.
Model status
A compact view of prediction freshness and whether you are looking at live storage or a saved snapshot.
Prediction gameweek
Pending
Not available yet
Model version
Pending
Waiting for training metadata
Last ingestion
Pending
Not available yet
Serving mode
Pending
Live data path available.
Evaluation snapshot
Lower MAE and RMSE are better. These compare the baseline against the trained model on held-out gameweeks.
Baseline MAE
RMSE pending
Pending
Model MAE
RMSE pending
Pending
Validation gameweeks
Train rows: 0 ยท Validation rows: 0
Pending