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. 2021 May 15;21(10):3441.
doi: 10.3390/s21103441.

Assessment of the Multi-Location External Workload Profile in the Most Common Movements in Basketball

Carlos D Gómez-Carmona  1 , Sebastián Feu  1 , José Pino-Ortega  2 , Sergio J Ibáñez  1
Affiliations

Assessment of the Multi-Location External Workload Profile in the Most Common Movements in Basketball

Carlos D Gómez-Carmona et al. Sensors (Basel). .

Abstract

The present study analyzed the multi-location external workload profile in basketball players using a previously validated test battery and compared the demands among anatomical locations. A basketball team comprising 13 semi-professional male players was evaluated in five tests (abilities/skills/tests): (a) aerobic, linear movement, 30-15 IFT; (b) lactic anaerobic, acceleration and deceleration, 16.25 m RSA (c) alactic anaerobic, curvilinear movement, 6.75 m arc (d) elastic, jump, Abalakov test (e) physical-conditioning, small-sided game, 10' 3 vs.3 10 × 15 m. PlayerLoadRT was evaluated at six anatomical locations simultaneously (interscapular line, lumbar region, knees and ankles) by six WIMU PROTM inertial devices attached to the player using an ad hoc integral suit. Statistical analysis was composed of an ANOVA of repeated measures and partial eta squared effect sizes. Significant differences among anatomical locations were found in all tests with higher values in the location nearer to ground contact (p < 0.01). However, differences between lower limb locations were only found in curvilinear movements, with a higher workload in the outside leg (p < 0.01). Additionally, high between-subject variability was found in team players, especially at lower limb locations. In conclusion, multi-location evaluation in sports movements will make it possible to establish an individual external workload profile and design specific strategies for training and injury prevention programs.

Keywords: accelerometry; human body; impacts; inertial devices; microtechnology; team sports.

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Conflict of interest statement

This work has been developed in the Training Optimization and Sports Performance Research Group (GOERD) of the Sports Science Faculty of the University of Extremadura. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. None of the authors has a conflict of interest to declare, and all authors were involved in the study design, data collection, and interpretation, and contributed to the writing of the manuscript.

Figures

Figure 1
Figure 1
Scatter dots plot with mean (black line), whiskers (standard deviation) and dots (basketball players) to represent the multi-location external workload profile of semi-professional male basketball players in curvilinear movements ((A) left and (B) right direction) and speed changes ((C) acceleration and (D) deceleration). * Statistical differences (p < 0.05); ND: no statistical differences.
Figure 2
Figure 2
Scatter dots plot with mean (black line), whiskers (standard deviation) and dots (basketball players) to represent the multi-location external workload profile of semi-professional male basketball players in (A) jumps, (B) linear movements and (C) small-sided games. * Statistical differences (p < 0.05); ND: no statistical differences.
See this image and copyright information in PMC

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