인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Purpose: This study investigates non-linear performance geometry and multidimensional player archetypes in the Korean Basketball League (KBL) using Topological Data Analysis (TDA), overcoming the limitations of Euclidean clustering.
Methods: Advanced metrics of 186 KBL players (2025-2026) were preprocessed via Empirical Bayes Smoothing. Persistent Homology extracted topological invariants (H1, H2). A performance network was built using the UMAP-filtered Mapper algorithm. A Player Hybrid Index, integrating centrality metrics, was developed to evaluate soft-clustering characteristics.
Results: The Mapper network demonstrated a complete structural distinction from traditional K-means baseline. Soft clustering identified multi-node hybrid players as essential topological bridges. Notably, the Player Hybrid Index exhibited a significant negative correlation with traditional efficiency metrics like PER and Net Rating (r=-.31, p<.001). This statistical paradox proves hybrid players prioritize multidimensional balance and altruistic structural devotion over conventional stat volumes. Additionally, topological voids (H2=17) quantified unfulfilled tactical scarcity.
Conclusion: TDA provides a robust framework that preserves true performance geometry, capturing the invisible structural value of hybrid players overlooked by linear metrics. This offers an innovative approach for detecting strategic voids and tactical decision-making.
Methods: Advanced metrics of 186 KBL players (2025-2026) were preprocessed via Empirical Bayes Smoothing. Persistent Homology extracted topological invariants (H1, H2). A performance network was built using the UMAP-filtered Mapper algorithm. A Player Hybrid Index, integrating centrality metrics, was developed to evaluate soft-clustering characteristics.
Results: The Mapper network demonstrated a complete structural distinction from traditional K-means baseline. Soft clustering identified multi-node hybrid players as essential topological bridges. Notably, the Player Hybrid Index exhibited a significant negative correlation with traditional efficiency metrics like PER and Net Rating (r=-.31, p<.001). This statistical paradox proves hybrid players prioritize multidimensional balance and altruistic structural devotion over conventional stat volumes. Additionally, topological voids (H2=17) quantified unfulfilled tactical scarcity.
Conclusion: TDA provides a robust framework that preserves true performance geometry, capturing the invisible structural value of hybrid players overlooked by linear metrics. This offers an innovative approach for detecting strategic voids and tactical decision-making.
본문·목차
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