The In the realm of professional sports, the "Moneyball" theory reveals market inefficiencies where player value is systematically undervalued. This theory provides novel insights for sports clubs to utilize data analytics in reducing the cost of winning and enhancing team performance. Addressing the challenge of player efficiency evaluation in the NBA, this study constructs a value scoring model inspired by the Moneyball concept. Specifically, player performance sta-tistics are analyzed using principal component analysis to extract com-prehen-sive efficiency indicators, while residual regression quantifies the devia-tion be-tween players' actual performance and their intrinsic efficiency levels. Results demonstrate that the proposed model effectively evaluates players' competitive capabilities, identifying both undervalued and overvalued individu-als. Under-valued players exhibit significantly higher on-court contributions relative to salary expectations, characterized by well-rounded technical profi-ciency and holistic efficiency. Conversely, overvalued players underperform their salary benchmarks, often relying excessively on isolated statistical metrics while demonstrating subpar overall efficiency.
Read full abstract- All Solutions
Editage
One platform for all researcher needs
Paperpal
AI-powered academic writing assistant
R Discovery
Your #1 AI companion for literature search
Mind the Graph
AI tool for graphics, illustrations, and artwork
Journal finder
AI-powered journal recommender
Unlock unlimited use of all AI tools with the Editage Plus membership.
Explore Editage Plus - Support
Overview
131 Articles
Published in last 50 years
Articles published on Salary Expectations
Authors
Select Authors
Journals
Select Journals
Duration
Select Duration
131 Search results
Sort by Recency