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Measuring Lateral Shuffle and Side Cut Performance

Overview of attention for article published in Journal of Strength & Conditioning Research, November 2013
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Article details
Title
Measuring Lateral Shuffle and Side Cut Performance
Published in
Journal of Strength & Conditioning Research, November 2013
DOI 10.1519/jsc.0b013e31828a2c2b
Pubmed ID
Authors
Abstract

Lateral shuffle and side cut (SSC) movements are defensive basketball movements where movement speed is critical to performance. The purpose of this study was to compare SSC data obtained using timing lights with motion capture system data and to determine the most appropriate method for measuring SSC performance. Shuffle time data were recorded using both timing lights and a motion capture system while 9 male subjects performed 2 different SSC movement sets, with and without controlling for arm movements, which may influence performance times. Shuffle and side cut times and SSC displacements were used to calculate mean shuffle velocity for each trial. The SEs for the motion capture system were estimated for SSC times (± 4.2 milliseconds; ~0.24% of mean shuffle time) and velocities (± 5.5 mm · s; ~0.24% of mean shuffle velocity), respectively, indicating high levels of precision. Timing light movement time variability was significantly higher during the uncontrolled (SD = 42 milliseconds) when compared with the controlled (SD = 9 milliseconds, p < 0.001) condition, indicating a significant reduction in variability by controlling non-performance-related variability such as arm movement. A significant positive correlation was found between SSC time and SSC displacement (r = 0.42) indicating that performance times were dependent on displacement. Furthermore, the variance in motion-captured SSC velocity was significantly smaller than the variance in velocity determined using timing lights (p < 0.05). We concluded that motion-captured SSC velocity data reduced systematic errors and non-performance-related movement variability and, therefore, was better able to reflect true performance. As true performance variability in human movement provides important information, the presented method for calculating SSC velocity in this study is recommended for assessing SSC performance.

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The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Canada 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 7 19%
Student > Bachelor 6 17%
Student > Master 6 17%
Other 3 8%
Lecturer > Senior Lecturer 2 6%
Other 5 14%
Unknown 7 19%
Readers by discipline
Readers by discipline Count As %
Sports and Recreations 20 56%
Agricultural and Biological Sciences 2 6%
Engineering 2 6%
Business, Management and Accounting 1 3%
Nursing and Health Professions 1 3%
Other 3 8%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 February 2014.
All research outputs
#21,118,985
of 34,151,039 outputs
Outputs from Journal of Strength & Conditioning Research
#4,991
of 7,345 outputs
Outputs of similar age
#161,893
of 262,313 outputs
Outputs of similar age from Journal of Strength & Conditioning Research
#93
of 109 outputs
Altmetric has tracked 34,151,039 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,345 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.1. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,313 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.