Accelerometry-Based External Load Indicators in Sport: Too Many Options, Same Practical Outcome?

Carlos D. Gómez-Carmona, José Pino-Ortega, Braulio Sánchez-Ureña, Sergio J. Ibáñez and Daniel Rojas-Valverde
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Carlos D. Gómez-Carmona: Optimization of Training and Sport Performance Research Group (GOERD), Sport Science Faculty, University of Extremadura, 10005 Caceres, Spain
José Pino-Ortega: Department of Physical Activity and Sport, International Excellence Campus “Mare Nostrum”, Sport Science Faculty, Universidad de Murcia, San Javier, 30720 Murcia, Spain
Braulio Sánchez-Ureña: Program of Exercise Science and Health (PROCESA), School of Human Movement Science and Quality of Life, Universidad Nacional, Heredia 86-3000, Costa Rica
Sergio J. Ibáñez: Optimization of Training and Sport Performance Research Group (GOERD), Sport Science Faculty, University of Extremadura, 10005 Caceres, Spain
Daniel Rojas-Valverde: Research Center of Sport and Health Diagnosis (CIDISAD), School of Human Movement Science and Quality of Life, Universidad Nacional, Heredia 86-3000, Costa Rica

IJERPH, 2019, vol. 16, issue 24, 1-13

Abstract: With the development of new microsensor technology to assess load in sports, some indicators of external load through accelerometry-based data have been created by sport technology companies. Thus, the study aim was to analyze the agreement between different accelerometry-based external load indicators (ABELIs) available in sport science. A U-16 male soccer team was assessed during three official matches, divided by periods, to obtain 3-D accelerometry data (x, y and z axes). An average of 1,420,000 data points was analyzed per axis per player. The ABELIs were calculated using this information, and the agreement between them was explored. The following ABELIs were considered after a literature review: AcelT, Player Load RT , PlayerLoad TM , Impulse Load, Player Load RE and Total Load. In order to compare ABELIs, two analyses were performed using: (1) absolute data; and (2) normalized and centered data (Z-scores). In absolute and centered data, very large to nearly perfect correlations (1st period: r > 0.803, p > 0.01; 2nd period: r > 0.919; p > 0.01) were found. Instead, very large differences were found in absolute values (bias = −579,226.6 to 285,931.1; t = −224.66 to 213.91, p < 0.01), and no differences in scaled and centered values (bias = 0; t = 1; p = 1). In conclusion, considering the different output (magnitude and units) among ABELIs, the standardization of a universal index to calculate accelerometer load is needed in order to make possible between-study comparison.

Keywords: accelerometers; load indexes; team sports; sport technology; monitoring (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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