10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Validity and reliability of an accelerometer-based player tracking device

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          This study aimed to determine the intra- and inter-device accuracy and reliability of wearable athletic tracking devices, under controlled laboratory conditions. A total of nineteen portable accelerometers (Catapult OptimEye S5) were mounted to an aluminum bracket, bolted directly to an Unholtz Dickie 20K electrodynamic shaker table, and subjected to a series of oscillations in each of three orthogonal directions (front-back, side to side, and up-down), at four levels of peak acceleration (0.1g, 0.5g, 1.0g, and 3.0g), each repeated five times resulting in a total of 60 tests per unit, for a total of 1140 records. Data from each accelerometer was recorded at a sampling frequency of 100Hz. Peak accelerations recorded by the devices, Catapult PlayerLoad™, and calculated player load (using Catapult’s Cartesian formula) were used for the analysis. The devices demonstrated excellent intradevice reliability and mixed interdevice reliability. Differences were found between devices for mean peak accelerations and PlayerLoad™ for each direction and level of acceleration. Interdevice effect sizes ranged from a mean of 0.54 (95% CI: 0.34–0.74) (small) to 1.20 (95% CI: 1.08–1.30) (large) and ICCs ranged from 0.77 (95% CI: 0.62–0.89) (very large) to 1.0 (95% CI: 0.99–1.0) (nearly perfect) depending upon the magnitude and direction of the applied motion. When compared to the player load determined using the Cartesian formula, the Catapult reported PlayerLoad™ was consistently lower by approximately 15%. These results emphasize the need for industry wide standards in reporting validity, reliability and the magnitude of measurement errors. It is recommended that device reliability and accuracy are periodically quantified.

          Related collections

          Most cited references14

          • Record: found
          • Abstract: found
          • Article: not found

          Monitoring Training Load to Understand Fatigue in Athletes

          Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The reliability of MinimaxX accelerometers for measuring physical activity in Australian football.

            To assess the reliability of triaxial accelerometers as a measure of physical activity in team sports. Eight accelerometers (MinimaxX 2.0, Catapult, Australia) were attached to a hydraulic universal testing machine (Instron 8501) and oscillated over two protocols (0.5 g and 3.0 g) to assess within- and between device reliability. A static assessment was also conducted. Secondly, 10 players were instrumented with two accelerometers during Australian football matches. The vector magnitude was calculated, expressed as Player load and assessed for reliability using typical error (TE) ± 90% confidence intervals (CI), and expressed as a coefficient of variation (CV%). The smallest worthwhile difference (SWD) in Player load was calculated to determine if the device was capable of detecting differences in physical activity. Laboratory: Within- (Dynamic: CV 0.91 to 1.05%; Static: CV 1.01%) and between-device (Dynamic: CV 1.02 to 1.04%; Static: CV 1.10%) reliability was acceptable across each test. Field: The between-device reliability of accelerometers during Australian football matches was also acceptable (CV 1.9%). The SWD was 5.88%. The reliability of the MinimaxX accelerometer is acceptable both within and between devices under controlled laboratory conditions, and between devices during field testing. MinimaxX accelerometers can be confidently utilized as a reliable tool to measure physical activity in team sports across multiple players and repeated bouts of activity. The noise (CV%) of Player load was lower than the signal (SWD), suggesting that accelerometers can detect changes or differences in physical activity during Australian football.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Player Load, Acceleration, and Deceleration During Forty-Five Competitive Matches of Elite Soccer.

              The use of time-motion analysis has advanced our understanding of position-specific work rate profiles and the physical requirements of soccer players. Still, many of the typical soccer activities can be neglected, as these systems only examine activities measured by distance and speed variables. This study used triaxial accelerometer and time-motion analysis to obtain new knowledge about elite soccer players' match load. Furthermore, we determined acceleration/deceleration profiles of elite soccer players and their contribution to the players' match load. The data set includes every domestic home game (n = 45) covering 3 full seasons (2009, 2010, and 2011) for the participating team (Rosenborg FC), and includes 8 central defenders (n = 68), 9 fullbacks (n = 83), 9 central midfielders (n = 70), 7 wide midfielders (n = 39), and 5 attackers (A, n = 50). A novel finding was that accelerations contributed to 7-10% of the total player load for all player positions, whereas decelerations contributed to 5-7%. Furthermore, the results indicate that other activities besides the high-intensity movements contribute significantly to the players' total match workload. Therefore, motion analysis alone may underestimate player load because many high-intensity actions are without a change in location at the pitch or they are classified as low-speed activity according to current standards. This new knowledge may help coaches to better understand the different ways players achieve match load and could be used in developing individualized programs that better meet the "positional physical demands" in elite soccer.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 February 2018
                2018
                : 13
                : 2
                : e0191823
                Affiliations
                [1 ] Southwest Research Institute, San Antonio, Texas, United States of America
                [2 ] Institute of Sport, Exercise and Active Living, College of Sport and Exercise Science, Victoria University, Melbourne, VIC, Australia
                Universita degli Studi di Verona, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-9411-6474
                Article
                PONE-D-17-13300
                10.1371/journal.pone.0191823
                5805236
                29420555
                778b0aad-f37a-4de5-9eab-d43cb0b8dbbc
                © 2018 Nicolella et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 April 2017
                : 11 January 2018
                Page count
                Figures: 5, Tables: 6, Pages: 13
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Engineering and Technology
                Electronics
                Accelerometers
                Physical Sciences
                Physics
                Classical Mechanics
                Acceleration
                Engineering and Technology
                Equipment
                Measurement Equipment
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Research and Analysis Methods
                Research Assessment
                Research Validity
                Biology and Life Sciences
                Behavior
                Recreation
                Sports
                Biology and Life Sciences
                Sports Science
                Sports
                Research and Analysis Methods
                Equipment Preparation
                Instrument Calibration
                Engineering and Technology
                Instrumentation
                Instrument Calibration
                Biology and Life Sciences
                Behavior
                Human Performance
                Custom metadata
                The data underlying this study have been uploaded to the Harvard Dataverse and are accessible using the following DOI: 10.7910/DVN/4WHUZH ( http://dx.doi.org/10.7910/DVN/4WHUZH).

                Uncategorized
                Uncategorized

                Comments

                Comment on this article