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Profiling high performers in elite women's basketball: Functional roles and normative benchmarks from 10 seasons of Spanish First Division data.

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Bibliographic Details
Title: Profiling high performers in elite women's basketball: Functional roles and normative benchmarks from 10 seasons of Spanish First Division data.
Authors: Courel-Ibáñez J; Department of Physical Education and Sports, University of Granada, Faculty of Education and Sport Sciences, Melilla, Spain., Piñar López MI; Department of Physical Education and Sports, University of Granada, Faculty of Sport Sciences, Granada, Spain., Contreras-García JM; Department of Didactics of Mathematics, University of Granada, Granada, Spain., J Ibáñez S; Training Optimization and Sports Performance Research Group (GOERD), University of Extremadura, Faculty of Sport Sciences, Cáceres, Spain.
Source: Journal of sports sciences [J Sports Sci] 2025 Nov; Vol. 43 (22), pp. 2764-2775. Date of Electronic Publication: 2025 Sep 17.
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Routledge Country of Publication: England NLM ID: 8405364 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1466-447X (Electronic) Linking ISSN: 02640414 NLM ISO Abbreviation: J Sports Sci Subsets: MEDLINE
Imprint Name(s): Publication: 2007- : London : Routledge
Original Publication: [London, England] : Published by E. & F.N. Spon on behalf of the Society of Sports Sciences, [c1983-
MeSH Terms: Basketball*/physiology , Benchmarking* , Athletic Performance*/physiology, Humans ; Female ; Spain ; Adult ; Young Adult ; Principal Component Analysis ; Competitive Behavior/physiology ; Aptitude
Abstract: Despite significant advances in basketball analytics, professional women's leagues remain underrepresented in performance research. Understanding normative performance benchmarks in professional women's basketball is essential for informed player development, scouting, and tactical planning; however, this area remains underexplored. This study analysed ten seasons (2012-2022) of performance data from 609 players, Spain's top-tier women's league (LF Endesa). Principal Component Analysis (PCA) confirmed the adequacy of 15 key indicators normalized per minute. A two-step clustering approach identified six functional player profiles (Primary Post, Secondary Post, Playmaker, 3&D Specialist, Role Player and Versatile). Players were further stratified into high, mid, and low performers within each role using z -score tertiles. Linear mixed models revealed that High performers consistently outscored Low performers in key metrics such as 2-point and 3-point field goals made, assists, and defensive rebounds ( p  < 0.01). Convergent validity was supported by the overrepresentation of High performers among First Team selections and players from top-ranked teams. Normative values for each role and performance tier are presented, providing a valuable reference for talent identification and role-based benchmarking in professional women's basketball. Future research should integrate contextual variables and advanced tracking data to refine these classifications across broader competitive settings.
Contributed Indexing: Keywords: Team sports; female basketball; match analysis; performance analysis; talent identification
Entry Date(s): Date Created: 20250918 Date Completed: 20251024 Latest Revision: 20251024
Update Code: 20251024
DOI: 10.1080/02640414.2025.2555559
PMID: 40963288
Database: MEDLINE
Description
Abstract:Despite significant advances in basketball analytics, professional women's leagues remain underrepresented in performance research. Understanding normative performance benchmarks in professional women's basketball is essential for informed player development, scouting, and tactical planning; however, this area remains underexplored. This study analysed ten seasons (2012-2022) of performance data from 609 players, Spain's top-tier women's league (LF Endesa). Principal Component Analysis (PCA) confirmed the adequacy of 15 key indicators normalized per minute. A two-step clustering approach identified six functional player profiles (Primary Post, Secondary Post, Playmaker, 3&D Specialist, Role Player and Versatile). Players were further stratified into high, mid, and low performers within each role using z -score tertiles. Linear mixed models revealed that High performers consistently outscored Low performers in key metrics such as 2-point and 3-point field goals made, assists, and defensive rebounds ( p  &lt; 0.01). Convergent validity was supported by the overrepresentation of High performers among First Team selections and players from top-ranked teams. Normative values for each role and performance tier are presented, providing a valuable reference for talent identification and role-based benchmarking in professional women's basketball. Future research should integrate contextual variables and advanced tracking data to refine these classifications across broader competitive settings.
ISSN:1466-447X
DOI:10.1080/02640414.2025.2555559