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A novel method to establish inter-athlete measurement uncertainty
54
Abstracts / Journal of Science and Medicine in Sport 20S (2017) 52–54
modalities (i.e. strength) may be required to quantify training load and injury risk. https://doi.org/10.1016/j.jsams.2017.09.300 105
future models developed to examine technical and tactical constructs of performance. The impact of these findings is discussed in terms of the development of agent based models and patternrecognition. https://doi.org/10.1016/j.jsams.2017.09.301
A novel method to establish inter-athlete measurement uncertainty
106
M. Price ∗ , C. Cummins, A. Gray, A. Murphy
Coaches and athletes agree that RPE can be used to measure the intensity of judo bouts
University of New England, Australia
S. Bromley 2,∗ , M. Drew 1 , S. Talpey 1 , A. McIntosh 1 , C. Finch 1
Background: Microtechnology devices (Global Positioning Systems (GPS) and integrated triaxial accelerometers) have enabled descriptive analysis of basic athlete movement patterns as well as comparisons of positional activity profiles, levels of competition and match-outcome. Such analysis however, provides minimal insight into the technical (individual athlete skills) and tactical (inter-athlete interactions) constructs of performance. Before microtechnology devices can be utilized to quantify inter-player cohesion and responsiveness, complex movement patterns and team tactics their ability to examine inter-athlete separation distances must be examined. This study examined the accuracy of microtechnology devices in quantifying inter-athlete separation distances. Methods: Inter-athlete separation distances were collected utilizing microtechnology devices producing a 15-Hz sampling signal through linear interpolation of a 5-Hz sampling rate. Two athletes repeatedly completed a 30 m distance in a straight line. One athlete completed this distance at a baseline position whilst the other athlete completed these distances offset from the baseline athlete by 1 m, 2 m, 5 m and 10 m. Each separation distance provided a minimum of 842 sample points. For each instantaneous sample point, the corresponding latitude and longitude for each device was taken with the inter-athlete separation distance calculated using Vincenty’s formulae. Differences between the baseline and offset athletes were described using magnitude-based inferences, with an exponential curve of effect size and delta distance established. Results: As separation distance from the baseline athlete increased the effect size increased. Specifically, at a distance of 1 m (1.69 ± 0.46 m) and 2 m (1.85 ± 0.28 m) from the baseline athlete separation could not be resolved (ES = 0.414; 90% confidence limits ± 0.046). At a distance of 5 m (4.64 ± 0.43 m) and 10 m (10.32 ± 0.47 m) from the baseline athlete separation was detected (ES = 8.07; ±0.012 and ES = 18.8; ±0.002, respectively). The exponential curve established that at a distance of 1.61 m, there is 90% confidence (ES = 1.20) that separation between athletes can be determined. Discussion: The study has developed a novel method to detect the limits of inter-athlete separation distances. It has been established that the minimum separation distance that a microtechnology device can detect between athletes is 1.61 m. This minimum separation distance is characterised by both device measurement error and the variance in sagittal human movement. The knowledge of this minimum distance underpins the integrity of
1 2
Australian Institute of Sport, Australia Federation University Australia, Australia
Introduction: Currently, the workload measure most utilised by combat sport in Australia is Rate of Perceived Exertion (RPE). Coaches prescribe training using bout RPE (b-RPE), for example, coaches instruct tan athlete to work at an 8/10 intensity for a certain bout in training. Despite the use of b-RPE, it is currently unknown whether coaches’ ratings reflect those of an athlete, and whether multiple coaches appraising the same athlete will be in agreement about how hard that athlete is working. Therefore the aims of this study were to determine whether coaches ratings of an athlete’s b-RPE are valid in comparison to the athlete’s own rating, and to ascertain the level of agreement between national level coaches rating of effort for an athlete. Methods: Four national judo coaches watched two, four minute judo bouts at an AIS judo international camp. During the bout, coaches individually recorded the number of attacks each athlete made, alongside predicting each athlete’s b-RPE, physical and mental effort for the bout. After each bout, athletes recorded their own b-RPE, mental and physical effort using NASA Task Load Scales (NASATLX). Coach ratings were analysed using Spearman’s Rho to determine whether their level of independence. A mixed models linear regression was applied to determine the agreement between the coach and athlete on the athlete’s effort and number of attacks. Results: Coaches were in high agreement when rating the same athlete’s b-RPE (ICC was 0.781 (CI 0.009–0.955, F = 4.57, p < 0.05). Coach and athlete b-RPE ratings were not significantly different (p = 0.332). However, coach’s ratings were significantly different to athletes for NASA-physical (p = 0.02) and NASA-mental (p = 0.004) ratings of a bout. Discussion: National level coaches can provide reliable information on judo athletes in relation to the number of attacks and physical and mental demands. Coaches can utilize b-RPE as a method to prescribe and monitor the intensity of judo bouts. Caution should be exercised when using NASA-physical and NASAmental effort scales. While coaches agree with each other on the ratings for these scales, these ratings are likely higher than the athlete’s. https://doi.org/10.1016/j.jsams.2017.09.302
Abstracts / Journal of Science and Medicine in Sport 20S (2017) 52–54
modalities (i.e. strength) may be required to quantify training load and injury risk. https://doi.org/10.1016/j.jsams.2017.09.300 105
future models developed to examine technical and tactical constructs of performance. The impact of these findings is discussed in terms of the development of agent based models and patternrecognition. https://doi.org/10.1016/j.jsams.2017.09.301
A novel method to establish inter-athlete measurement uncertainty
106
M. Price ∗ , C. Cummins, A. Gray, A. Murphy
Coaches and athletes agree that RPE can be used to measure the intensity of judo bouts
University of New England, Australia
S. Bromley 2,∗ , M. Drew 1 , S. Talpey 1 , A. McIntosh 1 , C. Finch 1
Background: Microtechnology devices (Global Positioning Systems (GPS) and integrated triaxial accelerometers) have enabled descriptive analysis of basic athlete movement patterns as well as comparisons of positional activity profiles, levels of competition and match-outcome. Such analysis however, provides minimal insight into the technical (individual athlete skills) and tactical (inter-athlete interactions) constructs of performance. Before microtechnology devices can be utilized to quantify inter-player cohesion and responsiveness, complex movement patterns and team tactics their ability to examine inter-athlete separation distances must be examined. This study examined the accuracy of microtechnology devices in quantifying inter-athlete separation distances. Methods: Inter-athlete separation distances were collected utilizing microtechnology devices producing a 15-Hz sampling signal through linear interpolation of a 5-Hz sampling rate. Two athletes repeatedly completed a 30 m distance in a straight line. One athlete completed this distance at a baseline position whilst the other athlete completed these distances offset from the baseline athlete by 1 m, 2 m, 5 m and 10 m. Each separation distance provided a minimum of 842 sample points. For each instantaneous sample point, the corresponding latitude and longitude for each device was taken with the inter-athlete separation distance calculated using Vincenty’s formulae. Differences between the baseline and offset athletes were described using magnitude-based inferences, with an exponential curve of effect size and delta distance established. Results: As separation distance from the baseline athlete increased the effect size increased. Specifically, at a distance of 1 m (1.69 ± 0.46 m) and 2 m (1.85 ± 0.28 m) from the baseline athlete separation could not be resolved (ES = 0.414; 90% confidence limits ± 0.046). At a distance of 5 m (4.64 ± 0.43 m) and 10 m (10.32 ± 0.47 m) from the baseline athlete separation was detected (ES = 8.07; ±0.012 and ES = 18.8; ±0.002, respectively). The exponential curve established that at a distance of 1.61 m, there is 90% confidence (ES = 1.20) that separation between athletes can be determined. Discussion: The study has developed a novel method to detect the limits of inter-athlete separation distances. It has been established that the minimum separation distance that a microtechnology device can detect between athletes is 1.61 m. This minimum separation distance is characterised by both device measurement error and the variance in sagittal human movement. The knowledge of this minimum distance underpins the integrity of
1 2
Australian Institute of Sport, Australia Federation University Australia, Australia
Introduction: Currently, the workload measure most utilised by combat sport in Australia is Rate of Perceived Exertion (RPE). Coaches prescribe training using bout RPE (b-RPE), for example, coaches instruct tan athlete to work at an 8/10 intensity for a certain bout in training. Despite the use of b-RPE, it is currently unknown whether coaches’ ratings reflect those of an athlete, and whether multiple coaches appraising the same athlete will be in agreement about how hard that athlete is working. Therefore the aims of this study were to determine whether coaches ratings of an athlete’s b-RPE are valid in comparison to the athlete’s own rating, and to ascertain the level of agreement between national level coaches rating of effort for an athlete. Methods: Four national judo coaches watched two, four minute judo bouts at an AIS judo international camp. During the bout, coaches individually recorded the number of attacks each athlete made, alongside predicting each athlete’s b-RPE, physical and mental effort for the bout. After each bout, athletes recorded their own b-RPE, mental and physical effort using NASA Task Load Scales (NASATLX). Coach ratings were analysed using Spearman’s Rho to determine whether their level of independence. A mixed models linear regression was applied to determine the agreement between the coach and athlete on the athlete’s effort and number of attacks. Results: Coaches were in high agreement when rating the same athlete’s b-RPE (ICC was 0.781 (CI 0.009–0.955, F = 4.57, p < 0.05). Coach and athlete b-RPE ratings were not significantly different (p = 0.332). However, coach’s ratings were significantly different to athletes for NASA-physical (p = 0.02) and NASA-mental (p = 0.004) ratings of a bout. Discussion: National level coaches can provide reliable information on judo athletes in relation to the number of attacks and physical and mental demands. Coaches can utilize b-RPE as a method to prescribe and monitor the intensity of judo bouts. Caution should be exercised when using NASA-physical and NASAmental effort scales. While coaches agree with each other on the ratings for these scales, these ratings are likely higher than the athlete’s. https://doi.org/10.1016/j.jsams.2017.09.302