OpenFPL: An open-source forecasting method rivaling state-of-the-art Fantasy Premier League services

TL;DR

OpenFPL is an open-source forecasting tool for Fantasy Premier League that uses public data to achieve accuracy comparable to commercial services, aiding players in strategic decision-making.

Contribution

This paper introduces OpenFPL, an open-source, data-driven forecasting method that rivals proprietary commercial services in accuracy for Fantasy Premier League predictions.

Findings

OpenFPL matches commercial forecast accuracy on 2024-25 data.

It outperforms commercial benchmarks for high-return players.

Effective across 1-, 2-, and 3-week forecast horizons.

Abstract

Fantasy Premier League engages the football community in selecting the Premier League players who will perform best from gameweek to gameweek. Access to accurate performance forecasts gives participants an edge over competitors by guiding expectations about player outcomes and reducing uncertainty in squad selection. However, high-accuracy forecasts are currently limited to commercial services whose inner workings are undisclosed and that rely on proprietary data. This paper aims to democratize access to highly accurate forecasts of player performance by presenting OpenFPL, an open-source Fantasy Premier League forecasting method developed exclusively from public data. Comprising position-specific ensemble models optimized on Fantasy Premier League and Understat data from four previous seasons (2020-21 to 2023-24), OpenFPL achieves accuracy comparable to a leading commercial service when tested prospectively on data from the 2024-25 season. OpenFPL also surpasses the commercial benchmark for high-return players ($>$ 2 points), which are most influential for rank gains. These findings hold across one-, two-, and three-gameweek forecast horizons, supporting long-term planning of transfers and strategies while also informing final-day decisions.