Rising Transfers · Methodology
How Rising Transfers Works
Eight in-depth explainers covering the data pipeline behind every Rising Transfers verdict, score, and recommendation. Read any one to understand the specific method; read all eight to understand the full analytical framework.
Per-90 stats explained
Why per-90 statistics are the standard unit of player performance evaluation, and how to read them correctly across different positions and leagues.
Read explainer →Player DNA matching
How RT finds genuinely similar footballers using style-vector matching across attacking, defensive, and creative dimensions — beyond position and price.
Read explainer →Transfer Truth Meter
A 0–100 reliability scale for transfer rumours. Source credibility, fee logic, squad need, and timeline plausibility evaluated together.
Read explainer →Transfer value assessment
Whether a reported fee is justified — comparing against market valuation, age trajectory, positional scarcity, and what similarly-profiled players cost.
Read explainer →AI verdict cards
How RT Make turns any player photo into a shareable verdict card in 8 seconds — vision recognition, topical event detection, angle templates, GPT-Image-2.
Read explainer →AI transfer analysis
How AI is changing football transfer analysis — multi-source data fusion, pattern recognition, and the gap between club tools and fan tools.
Read explainer →How to compare footballers
A data-driven framework for comparing players objectively — normalising for playing time, position context, and team system.
Read explainer →Football data analytics
How professional clubs use data analytics across recruitment, performance analysis, market valuation, and load management.
Read explainer →See it in action
Try the tools, not just the theory
Every method explained here is live on Rising Transfers — run a transfer rumour through the Lie Detector, browse player DNA matches, or generate a verdict card.