A structured framework for cross-league player projection and transfer risk modeling.
Designed to explore predictive modeling, performance normalization, and probabilistic decision intelligence in professional football recruitment.
Cross-league player evaluation lacks standardized normalization, leading to distorted comparisons, inefficient scouting allocation, and mispriced transfer decisions.
Multi-source ingestion of match performance, availability data, tactical context, and league strength indicators.
Adjusts player metrics across league quality and team context to enable fair comparison.
Structured profiling of efficiency, adaptability, and consistency indicators.
Projects performance ranges in target league environments rather than deterministic outcomes.
Generates structured risk and projection insights to support transfer evaluation.
Preference for structured modeling over black-box prediction.
Outputs framed as confidence ranges rather than fixed projections.
Every projection incorporates performance variance and uncertainty.
The framework supports — not replaces — scouting expertise.