Quantifying cricket fast bowling volume, speed and perceived intensity zone using an Apple Watch and machine learning-Reference-Cited by-同舟云学术

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Quantifying cricket fast bowling volume, speed and perceived intensity zone using an Apple Watch and machine learning

Published:2021-11-10 Issue: Volume: Page:1-8
ISSN:0264-0414
Container-title:Journal of Sports Sciences
language:en
Short-container-title:Journal of Sports Sciences

Author:

McGrath Joseph W.¹²³,Neville Jonathon¹,Stewart Tom¹⁴,Clinning Hayley⁵,Thomas Bernd⁶,Cronin John¹^ORCID

Affiliation:

1. Sports Performance Research Institute New Zealand, AUT University, Auckland, New Zealand

2. Manukau Institute of Technology School of Sport, Auckland, New Zealand

3. Paramedicine and Emergency Management, School of Health Care Practice, Aut University, Auckland, New Zealand

4. Human Potential Centre, AUT University, Auckland, New Zealand

5. Independent Researcher, Auckland, New Zealand

6. Independent Researcher, Stuttgart, Germany

Funder

no funding

Publisher

Informa UK Limited

Subject

Physical Therapy, Sports Therapy and Rehabilitation,Orthopedics and Sports Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/02640414.2021.1993640

Reference27 articles.

2. Callaghan, S., Lockie, R., Andrews, W., Chipchase, R. & Nimphius, S. (2020). The relationship between inertial measurement unit-derived ‘force signatures’ and ground reaction forces during cricket pace bowling. Sports Biomechanics, 19(3), 307–321. https://doi.org/10.1080/14763141.2018.1465581

3. The relationship between fast bowling workload and injury in first-class cricketers: a pilot study

4. Bowling workload and the risk of injury in elite cricket fast bowlers

5. Is bowling workload a risk factor for injury to Australian junior cricket fast bowlers? * Commentary * Commentary

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Can an inertial measurement unit, combined with machine learning, accurately measure ground reaction forces in cricket fast bowling?;Sports Biomechanics;2023-11-09

2. Understanding the effect of contextual factors and decision making on team performance in Twenty20 cricket: an interpretable machine learning approach;Annals of Operations Research;2022-11-04

3. The relationship between bowling intensity and ground reaction force in cricket pace bowlers;Journal of Sports Sciences;2022-07-03

4. Human Health Activity Recognition Algorithm in Wireless Sensor Networks Based on Metric Learning;Computational Intelligence and Neuroscience;2022-04-18

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