ATHLEMETRICS MACHINE LEARNING DATA
Analysis and predict football player performance metrics using machine learning models.


Why Do We Need Machine Learning Data?
- Enhance decision-making with predictive insights into player growth and performance.
- Gain a competitive edge over traditional scouting through objective, data-driven analysis.
- Optimize scouting, transfers, and performance evaluation with smarter, targeted insights.
Quick Access Flatform

Player Performance Prediction
We offer machine learning-driven predictions of individual player metrics, including contribution scores per 90 minutes, goalkeeping performance, duel effectiveness, passing and playmaking abilities.
Dynamic Skill Evolution
Our models track player performance trends over time, helping you predict future growth, peak seasons, or potential declines with data-driven accuracy.
Comparative Analytics
Compare players across leagues and seasons with normalized data, providing a deeper understanding of a player’s true performance level relative to peers.
Customizable Data Packages
We offer flexible datasets tailored to your needs — whether scouting, team optimization, or fantasy sports — with options for detailed player reports and visual insights.
Squad Compatibility Dashboard
See a “chemistry score” for any lineup based on positional coverage, playing styles, and historical synergy. Filter by formations to identify the highest-compatibility 11 for a given tactic. Drill down to see which player pairings or sub-units (e.g. midfield trio, back four) drive or detract from overall balanc
Tactical Scenario Simulator
Choose up to three alternative lineups and simulate expected possession, xG/xA, and defensive solidity under various opponent Adjust in-game variables (e.g. press intensity, width, midfield density) to see how score probabilities shift. Export pre-match PDF reports with side-by-side simulation results and recommended tactical tweaks.
Happy Clients,
Great Reviews
Learn about Athlemetrics from other users and start exploring sport data in your surroundings
Using machine learning predictions has completely transformed our scouting process. We can now identify promising young players before they appear on the radar of major clubs. It gives us a huge competitive advantage.
Naomi Matz, Botanist
The data-driven insights allow us to make smarter transfer decisions. Instead of relying solely on intuition, we now have objective metrics that predict a player’s future performance. It’s an invaluable tool for building a winning team.
Marvin Conte, Plants lover
As a fan, having access to machine learning-based player forecasts makes following football even more exciting. It’s fascinating to track players’ projected development and see how their careers unfold.