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Journal of Sports Sciences Volume 39, 2021 - Issue 12
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Sports Performance

Can an inertial measurement unit (IMU) in combination with machine learning measure fast bowling speed and perceived intensity in cricket?

Joseph McGratha Sports Performance Research Institute New Zealand, AUT University, Auckland, New Zealand;b School of Sport, Manukau Institute of Technology, Auckland, New Zealand;c Paramedicine and Emergency Management, School of Health Care Practice, AUT University, Auckland, New ZealandCorrespondence[email protected]
,
Jonathon Nevillea Sports Performance Research Institute New Zealand, AUT University, Auckland, New Zealand
,
Tom Stewarta Sports Performance Research Institute New Zealand, AUT University, Auckland, New Zealand;d Human Potential Centre, AUT University, Auckland, New Zealand
,
Hayley Clinninge Auckland, New Zealand
&
John Cronina Sports Performance Research Institute New Zealand, AUT University, Auckland, New ZealandORCID Iconhttps://orcid.org/0000-0002-8889-0911
ORCID Icon
Pages 1402-1409 | Accepted 11 Jan 2021, Published online: 22 Jan 2021

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Read on this site (4)

Joseph W. McGrath, Jonathon Neville, Tom Stewart, Matt Lamb, Peter Alway, Mark King & John Cronin. (2022) The relationship between bowling intensity and ground reaction force in cricket pace bowlers. Journal of Sports Sciences 40:14, pages 1602-1608.
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Daniel J. Epifano, Samuel Ryan, Anthea C. Clarke & Kane J. Middleton. (2022) Objective assessment of fast bowling delivery intensity in amateur male cricketers. Journal of Sports Sciences 40:4, pages 442-449.
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Joseph W. McGrath, Jonathon Neville, Tom Stewart, Hayley Clinning, Bernd Thomas & John Cronin. (2022) Quantifying cricket fast bowling volume, speed and perceived intensity zone using an Apple Watch and machine learning. Journal of Sports Sciences 40:3, pages 323-330.
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Joseph W. McGrath, Jonathon Neville, Tom Stewart, Matt Lamb, Peter Alway, Mark King & John Cronin. Can an inertial measurement unit, combined with machine learning, accurately measure ground reaction forces in cricket fast bowling?. Sports Biomechanics 0:0, pages 1-13.
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Bernhard Hollaus, Yannic Heyer, Johannes Steiner & Gerda Strutzenberger. (2023) Location Matters—Can a Smart Golf Club Detect Where the Club Face Hits the Ball?. Sensors 23:24, pages 9783.
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Nahida Reyaz, Gulfam Ahamad, Mohd Naseem, Javed Ali & Khalid Imam Rahmani. (2023) Information communication and technology in sports: a meticulous review. Frontiers in Sports and Active Living 5.
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Indika Wickramasinghe. (2022) Applications of Machine Learning in cricket: A systematic review. Machine Learning with Applications 10, pages 100435.
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Shuai Leng & Mingjiao Shao. (2022) A Study on the Effect of the Club Model on the Effectiveness of College Volleyball Teaching Based on a Random Matrix Model. Mathematical Problems in Engineering 2022, pages 1-12.
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Taylor Léger, Philippe J. Renaud, Shawn M. Robbins & David J. Pearsall. (2022) Pilot Study of Embedded IMU Sensors and Machine Learning Algorithms for Automated Ice Hockey Stick Fitting. Sensors 22:9, pages 3419.
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Yufeng Liu, Jared Evans, Jacek Wąsik, Xiang Zhang & Gongbing Shan. (2022) Performance Alteration Induced by Weight Cutting in Mixed Martial Arts—A Biomechanical Pilot Investigation. International Journal of Environmental Research and Public Health 19:4, pages 2015.
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Xiangdong Wang, Ruijiao Liu, Tian Zhang & Gongbing Shan. (2022) The Proper Motor Control Model Revealed by Wheelchair Curling Quantification of Elite Athletes. Biology 11:2, pages 176.
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Larisa Gomaz, DirkJan Veeger, Erik van der Graaff, Bart van Trigt & Frank van der Meulen. (2021) Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data. Sensors 21:22, pages 7442.
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Roland van den Tillaar, Shruti Bhandurge & Tom Stewart. (2021) Can Machine Learning with IMUs Be Used to Detect Different Throws and Estimate Ball Velocity in Team Handball?. Sensors 21:7, pages 2288.
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