SciSports is proud to announce the release of the upgraded Estimated Transfer Value (ETV) model. This enhanced version leverages advanced Machine Learning techniques to provide unparalleled accuracy and market relevance, setting a new benchmark in predictive player transfer valuation.
A New Standard for Player Valuation
The ETV model has been a cornerstone of SciSports’ recruitment tools, used by clubs and platforms like FootballTransfers.com to estimate player values based on factors such as SciSkill, Potential, and contract duration. With ETV v2, we’ve significantly improved the model to better reflect recent developments in the transfer market and user feedback. Key enhancements include:
Higher accuracy
- Prediction error reduced from ±25% to ±10%, outperforming both the previous model and competitors.
Market alignment
- Adjusted for inflation, rising investments, and the growing commercialization of football.
Player-specific changes
- Increased ETV for young, high-potential players who are highly valued by clubs.
- Lower ETV for older players with limited resale potential.
Improved responsiveness
- Faster adaptation to player form, injuries, and trends by focusing on recent performance data (last 6–12 months).
Refined contract impact
- Smoother transitions in value based on contract changes, addressing user feedback on volatility.
Estimating transfer values in professional soccer
With ETV v2, SciSports reaffirms its position as the industry leader in data-driven player valuation. Clubs, analysts, and professionals can continue relying on our tools to make informed decisions in an ever-changing market landscape. Find more information about the foundations and intelligence behind SciSports’ Estimated Transfer Value model by reading the below whitepaper, written by SciSports’ Head of Data Science.
