Submission received: 17 February 2025 / Revised: 18 March 2025 / Accepted: 25 March 2025
Abstract
Technological advancements have led to widespread use of wearable devices that capture external performance metrics in team sports. Tracking systems including global positioning system (GPS) technology with inbuilt microelectromechanical systems (MEMS), instrumented mouthguards (iMGs), and video analysis provide valuable insights into the contact demands of collision sports. In collision sports, successfully “winning the contact” is positively associated with better individual and team performance, but it also comes with a high risk of injury, posing a concern for player welfare. Understanding the frequency and intensity of these contact events is important in order for coaches and practitioners to adequately prepare players for competition and can simultaneously reduce the burden on athletes. Different methods have been developed for detecting contact events, although limitations of the current methods include validity and reliability issues, varying thresholds, algorithm inconsistencies, and a lack of code- and sex-specific algorithms. In this review, we evaluate common methods for capturing contact events in team collision sports and detail a new method for assessing contact intensity through notational analysis, offering a potential alternative for capturing contact events that are currently challenging to detect through microtechnology alone.
Keywords:
1. Introduction
Technological advancements have enabled the detection and application of metrics related to physical performance, physiological status, biochemical composition, and mental alertness in athletes. These innovations can help reduce injury risks and enhance physical performance, enabling coaching, medical, and performance staff to create, evaluate, and refine athlete-centered protocols and treatment plans [1,2]. A key application of technology in sport is the capture and analysis of the demands of the competition, which can play a pivotal role in refining training sessions to replicate or exceed actual match-play conditions, thus promoting athletes’ adaptation and improving their overall performance during competition. Sporting demands are generally classified into external and internal categories. The term “external” refers to the mechanical or locomotive stress placed on an athlete during exercise (e.g., distance travelled, number of jumps performed, or the number of tackles performed in rugby) [3]. “Internal” demands refer to the physiological and psychological stress (e.g., heart rate [HR], rating of perceived exertion [RPE]) experienced by the athlete in response to the external demands [3].
In team sports, external demands are most commonly measured using wearable tracking systems like global positioning (GPS) or local positioning (LPS), which generate large volumes of data that provide valuable insights into the physical demands of match-play. These data help coaches and performance staff to better understand the specific demands players face during match-play [4,5,6,7,8]. When combined with other technologies, such as a heart rate monitor and embedded inertial sensors, these tracking systems play a crucial role in developing a comprehensive understanding of match-play [9]. The information that they provide assists in planning, evaluating, and refining training plans that align with both physical and tactical demands, aiming to improve athletic performance and reduce injury risk.
Table 1. Overview of micro sensors and their application in contact event detection.
Author Contributions
C.B. conceived the idea for this review. C.B. wrote the first draft. A.J.M., D.B.P., J.M. and B.F. contributed to the writing of subsequent drafts and provided content and editorial suggestions. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Acknowledgments
The preparation of this perspective review was supported by the University of Canberra’s Institutional Open Access Program.
Conflicts of Interest
The authors declare no conflicts of interest.
References
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