Abstract
There is scarce research into the use of Strive Sense3 smart compression shorts to measure external load with accelerometry and muscle load (i.e., muscle activations) with surface electromyography in basketball. Sixteen external load and muscle load variables were measured from 15 National Collegiate Athletic Association Division I men’s basketball players with 1137 session records. The data were analyzed for player positions of Centers (n = 4), Forwards (n = 4), and Guards (n = 7). Nonparametric bootstrapping was used to find significant differences between training and game sessions. Significant differences were found in all variables except Number of Jumps and all muscle load variables for Guards, and all variables except Muscle Load for Forwards. For Centers, the Average Speed, Average Max Speed, and Total Hamstring, Glute, Left, and Right Muscle variables were significantly different (p < 0.05). Principal component analysis was conducted on the external load variables. Most of the variance was explained within two principal components (70.4% in the worst case). Variable loadings of principal components for each position were similar during training but differed during games, especially for the Forward position. Measuring muscle activation provides additional information in which the demands of each playing position can be differentiated during training and competition.
Highlights
This paper aims to present the use of a novel, commercially available athlete monitoring system, the Strive Sense3 (Strive), to measure external load and muscle activation during a season of training and competition for a National Collegiate Athletic Association (NCAA) Division I men’s basketball team
When comparing measures taken between training and games, Centers were found to have significantly different speeds and muscle activations, Forwards were found to have significant differences across all measures except Muscle Load, and Guards were found to have significant differences for Muscle Load and all external load variables except
These findings suggest that each position in basketball has its own unique external load and muscle activity profile, and that training regimens can be adapted to match these demands in competition
Summary
Load monitoring of athletes during training and competition has seen tremendous growth due to the introduction of wearables to the market [1]. Despite this increase, coaches and practitioners have expressed frustration and a lack of trust with some of these technologies due to inconsistent data reporting, poor comfort and fit, and lack of transparency in data calculations [1,2,3]. Load monitoring is reported in terms of external and internal loads using both biomechanical and physiological metrics [4]. Methodologies found in the literature include heart rate monitoring, blood lactate concentration, rating of perceived exertion (RPE) surveys, accelerometers/inertial measurement units (IMUs), global positioning systems, local positioning systems, and optical camera systems
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