Applying principal component analysis to identify underlying factors of key performance indicators from microsensor data in basketball games

Ujaković, Filip; Kozinc, Žiga; Pleša, Jernej; Šarabon, Nejc

ENG

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Naslov:	Applying principal component analysis to identify underlying factors of key performance indicators from microsensor data in basketball games
Avtorji:	ID Ujaković, Filip (Avtor) ID Kozinc, Žiga (Avtor) ID Pleša, Jernej (Avtor) ID Šarabon, Nejc (Avtor)
Datoteke:	https://doi.org/10.1177/17479541261485107 https://journals.sagepub.com/doi/10.1177/17479541261485107 RAZ_Ujakovic_Filip_2026.pdf (324,97 KB) MD5: 2043559924F17655A9DC3F75B4DEE02B To gradivo ima še več datotek. Celoten seznam je na voljo spodaj.
Jezik:	Angleški jezik
Vrsta gradiva:	Članek v reviji
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	FVZ - Fakulteta za vede o zdravju
Opis:	The present study applied Principal Component Analysis (PCA) to complex microsensor data from 28 elite professional male basketball players across 122 games (1205 player/game samples) during two basketball seasons to reduce data dimensionality and identify underlying factors related to player load and movement intensity. External load was quantified using T7 Catapult monitoring devices, capturing 18 inertial measurement unit (IMU)-derived variables. PCA with varimax orthogonal rotation successfully extracted four distinct principal components (PC) with eigenvalues >1, collectively explaining 77.95% of the total variance. These components were interpreted as: PC 1 (33.43% variance), dominated by high-intensity acceleration and change of direction and representing high-intensity linear and multi-directional movements; PC 2 (19.27% variance), defined by deceleration measures, reflecting eccentric braking performance; PC 3 (15.49% variance) capturing overall accumulated mechanical workload; and PC 4 (9.76% variance) representing jumping frequency. In conclusion, PCA effectively reduced 18 highly correlated microsensor variables into four distinct, uncorrelated factors that encapsulate the main physical demands of elite basketball game-play, providing a more pragmatic and holistic framework for performance interpretation and subsequent tailoring of training prescription and monitoring over time. The extraction of these four factors provides a diagnostic framework for load profiling in elite basketball; however, as these results originate from a single-team observational design, future research is required to confirm the cross-contextual stability of this mechanical structure.
Ključne besede:	basketball, measurement, loading
Status publikacije:	V tisku
Verzija publikacije:	Objavljena publikacija
Datum objave:	17.09.2026
Leto izida:	2026
Št. strani:	str. 1-10
PID:	20.500.12556/RUP-23643
UDK:	796.323
ISSN pri članku:	2048-397X
DOI:	10.1177/17479541261485107
COBISS.SI-ID:	291697155
Datum objave v RUP:	20.09.2026
Število ogledov:	250
Število prenosov:	10
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Gradivo je del revije

Naslov:	International journal of sports science & coaching
Založnik:	Multi-Science Publishing
ISSN:	2048-397X
COBISS.SI-ID:	525537561

Gradivo je financirano iz projekta

Financer:	ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:	P5-0443
Naslov:	Kineziologija za učinkovitost in preventivo mišično-skeletnih poškodb v športu

Licence

Licenca:	CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna

Povezava:	http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:	To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:	Slovenski jezik
Ključne besede:	košarka, meritve, obremenitev

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