The validity of microsensors to automatically detect bowling events and counts in cricket fast bowlers

McNamara, Dean J. and Gabbett, Tim J. and Chapman, Paul and Naughton, Geraldine and Farhart, Patrick (2015) The validity of microsensors to automatically detect bowling events and counts in cricket fast bowlers. International Journal of Sports Physiology and Performance, 10 (1). pp. 71-75. ISSN 1555-0265


Purpose: Bowling workload is linked to injury risk in cricket fast bowlers. This study investigated the validity of microtechnology in the automated detection of bowling counts and events, including run-up distance and velocity, in cricket fast bowlers. Method: Twelve highly skilled fast bowlers (mean ± SD age 23.5 ± 3.7 y) performed a series of bowling, throwing, and fielding activities in an outdoor environment during training and competition while wearing a microtechnology unit (MinimaxX). Sensitivity and specificity of a bowling-detection algorithm were determined by comparing the outputs from the device with manually recorded bowling counts. Run-up distance and run-up velocity were measured and compared with microtechnology outputs. Results: No significant differences were observed between direct measures of bowling and nonbowling events and true positive and true negative events recorded by the MinimaxX unit (P = .34, r = .99). The bowling-detection algorithm was shown to be sensitive in both training (99.0%) and competition (99.5%). Specificity was 98.1% during training and 74.0% during competition. Run-up distance was accurately recorded by the unit, with a percentage bias of 0.8% (r = .90). The final 10-m (-8.9%, r = .88) and 5-m (-7.3%, r = .90) run-up velocities were less accurate. Conclusions: The bowling-detection algorithm from the MinimaxX device is sensitive to detect bowling counts in both cricket training and competition. Although specificity is high during training, the number of false positive events increased during competition. Additional bowling workload measures require further development.

Statistics for USQ ePrint 32292
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: No Faculty
Faculty/School / Institute/Centre: No Faculty
Date Deposited: 30 May 2017 01:14
Last Modified: 30 May 2017 01:14
Uncontrolled Keywords: competition; GPS; team sport; training; workload; accelerometry; adult; algorithms; competitive behavior; geographic information systems; humans; magnetometry; microtechnology; physical education and training; reproducibility of results; sports; workload; young adult
Fields of Research (2008): 11 Medical and Health Sciences > 1106 Human Movement and Sports Science > 110699 Human Movement and Sports Science not elsewhere classified
Fields of Research (2020): 42 HEALTH SCIENCES > 4207 Sports science and exercise > 420799 Sports science and exercise not elsewhere classified
Socio-Economic Objectives (2008): C Society > 92 Health > 9299 Other Health > 929999 Health not elsewhere classified
Identification Number or DOI:

Actions (login required)

View Item Archive Repository Staff Only