<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To aid the implementation of athlete surveillance systems relative to logistical circumstances, easy-to-access information that summarises the extent to which methods of acquiring data are used in practice to monitor athletes is required. In this scoping review, Social Network Analysis and Mining (SNAM) techniques were used to summarise and identify the most prevalent combinations of methods used to monitor athletes in research studying team, individual, field- and court-based sports (357 articles; SPORTDiscus, MEDLINE, CINHAL, and WebOfScience; 2014-2018 inc.) . The most prevalent combination in team and field-based sports were HR and/or sRPE (internal) and GPS, whereas in individual and court-based sports, internal methods (e.g., HR and sRPE) were most prevalent. In court-based sports, where external methods were occasionally collected in combination with internal methods of acquiring data, the use of accelerometers or inertial measuring units (ACC/IMU) were most prevalent. Whilst individual and court-based sports are less researched, this SNAM-based summary reveals that court-based sports may lead the way in using ACC/IMU to monitor athletes. Questionnaires and self-reported methods of acquiring data are common in all categories of sport. This scoping review provides coaches, sport-scientists and researchers with a data-driven visual resource to aid the selection of methods of acquiring data from athletes in all categories of sport relative to logistical circumstances. A guide on how to practically implement a surveillance system based on the visual summaries provided herein, is also presented.</p>
</abstract>

To aid the implementation of athlete surveillance systems relative to logistical circumstances, easy-to-access information that summarises the extent to which methods of acquiring data are used in practice to monitor athletes is required. In this scoping review, Social Network Analysis and Mining (SNAM) techniques were used to summarise and identify the most prevalent combinations of methods used to monitor athletes in research studying team, individual, field- and court-based sports (357 articles; SPORTDiscus, MEDLINE, CINHAL, and WebOfScience; 2014-2018 inc.) . The most prevalent combination in team and field-based sports were HR and/or sRPE (internal) and GPS, whereas in individual and court-based sports, internal methods (e.g., HR and sRPE) were most prevalent. In court-based sports, where external methods were occasionally collected in combination with internal methods of acquiring data, the use of accelerometers or inertial measuring units (ACC/IMU) were most prevalent. Whilst individual and court-based sports are less researched, this SNAM-based summary reveals that court-based sports may lead the way in using ACC/IMU to monitor athletes. Questionnaires and self-reported methods of acquiring data are common in all categories of sport. This scoping review provides coaches, sport-scientists and researchers with a data-driven visual resource to aid the selection of methods of acquiring data from athletes in all categories of sport relative to logistical circumstances. A guide on how to practically implement a surveillance system based on the visual summaries provided herein, is also presented.

A scoping review using social network analysis techniques to summarise the prevalance of methods used to acquire data for athlete survelliance in sport

International Journal of Computer Science in Sport

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

To aid the implementation of athlete surveillance systems relative to logistical circumstances, easy-to-access information that summarises the extent to which...

A scoping review using social network analysis techniques to summarise the prevalance of methods used to acquire data for athlete survelliance in sport

Published Online: Nov 28, 2021

Page range: 175 - 197

DOI: https://doi.org/10.2478/ijcss-2021-0011

Keywords
TRAINING LOAD, ATHLETE MONITORING, ACCELEROMETRY, CENTRALITY, FIEDLER VECTOR

© 2021 P. J. Watson et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A scoping review using social network analysis techniques to summarise the prevalance of methods used to acquire data for athlete survelliance in sport

Published Online: Nov 28, 2021

Page range: 175 - 197

DOI: https://doi.org/10.2478/ijcss-2021-0011

KeywordsTRAINING LOAD, ATHLETE MONITORING, ACCELEROMETRY, CENTRALITY, FIEDLER VECTOR

© 2021 P. J. Watson et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
TRAINING LOAD, ATHLETE MONITORING, ACCELEROMETRY, CENTRALITY, FIEDLER VECTOR