1. Clustering performances in the NBA according to players’ anthropometric attributes and playing experience.
- Author
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Zhang, Shaoliang, Lorenzo, Alberto, Gómez, Miguel-Angel, Mateus, Nuno, Gonçalves, Bruno, and Sampaio, Jaime
- Subjects
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ANTHROPOMETRY , *PSYCHOLOGY of athletes , *ATHLETIC ability , *BASKETBALL , *BODY weight , *CLUSTER analysis (Statistics) , *DISCRIMINANT analysis , *STATISTICAL sampling , *STATURE - Abstract
The aim of this study was: (i) to group basketball players into similar clusters based on a combination of anthropometric characteristics and playing experience; and (ii) explore the distribution of players (included starters and non-starters) from different levels of teams within the obtained clusters. The game-related statistics from 699 regular season balanced games were analyzed using a two-step cluster model and a discriminant analysis. The clustering process allowed identifying five different player profiles: Top height and weight (HW) with low experience, TopHW-LowE; Middle HW with middle experience, MiddleHW-MiddleE; Middle HW with top experience, MiddleHW-TopE; Low HW with low experience, LowHW-LowE; Low HW with middle experience, LowHW-MiddleE. Discriminant analysis showed that TopHW-LowE group was highlighted by two-point field goals made and missed, offensive and defensive rebounds, blocks, and personal fouls; whereas the LowHW-LowE group made fewest passes and touches. The players from weaker teams were mostly distributed in LowHW-LowE group, whereas players from stronger teams were mainly grouped in LowHW-MiddleE group; and players that participated in the finals were allocated in the MiddleHW-MiddleE group. These results provide alternative references for basketball staff concerning the process of evaluating performance. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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