Quantification of physical contact and its influence on simulated performance and recovery in rugby players.
|dc.identifier.citation||Norris, J. (2018). Quantification of physical contact and its influence on simulated performance and recovery in rugby players. (Doctoral dissertation). University of Chester, United KIngdom.|
|dc.description.abstract||The aim of this thesis was to investigate the influence of physical collisions on internal (physiological and perceptual) and external (locomotive and accelerometer) load during simulated rugby league performance and fatigue responses in the days after. Chapter 4 examined the influence of physical contact type on internal and external load using a traditional soft tackle bag and custom-built tackle sled. Using a traditional tackle bag to simulate physical collisions resulted in likely faster sprint to contact speed (16.1 ± 1.5 c.f. 14.8 ± 1.1 km.h -1 ) but possibly lower overall high-speed running distance (27.7 ± 2.4 c.f. 28.4 ± 2.6 m.min-1 ). Also, the heavier tackle sled likely increased time at 91-100% HRpeak (12:58 ± 13:21 c.f. 6:44 ± 8:06 min:s) and resulted in greater lower limb fatigue reflected by the likely larger decrease in countermovement jump (CMJ) performance (5.9 ± 4.9 c.f. 2.6 ± 5.4%). Also of note was the variation in number of tackles detected using the automatic tackle detection feature compared to the actual number in the match simulation. During the Bag and Sled simulations ~53 and ~59 tackles were detected compared to 48 performed. The purpose of Chapter 5 was to investigate the influence of sprint to contact speed and contact type on automatic tackle detection using microtechnology. Repetitions were divided into three speed categories; walking, jogging and striding (1, 2.5 and 4 m.s -1 ) and four conditions: i) no contact standing upright (NCST), ii) no contact dropping to the ground in a prone position (NCGR), iii) contact with the tackle bag and remaining upright (CST), iv) contact with the tackle bag and going to ground (CGR). Similar tackle detection accuracy was observed between NCGR and CST conditions with one tackle observed in 41 and 43% of trials, respectively. While CGR resulted in the greatest frequency of correct tackle detection (62%), during 16% of trials two tackles were detected. During NCST, there were no tackles detected and 100% accuracy. The PlayerLoadTM results demonstrated that the metric can detect differences in movement speed, the inclusion of physical contact and changes in orientation during short periods of activity (8-10 s). In Chapter 6 the rugby league movement simulation protocol for interchange players (RLMSP-i) was modified to include a tackle shield collision to investigate the reliability of PlayerLoadTM metrics to quantify collision load. The coefficient of variation (%CV) for locomotive metrics ranged from 1.3 to 14.4%, with greatest variability observed for high-speed running distance (8.0 and 14.4% for Bouts 1 and 2, respectively). Accelerometer metrics CV% were 4.4 to 10.0%, while internal load markers were 4.8 to 13.7%. All variables presented a CV% less than the calculated moderate change during one or both bouts of the match simulation except from high-speed distance (m.min-1 ), %HRpeak and RPE (AU). The aim of Chapter 7 was to investigate the influence of contact type on external load metrics including PlayerLoadTM derivatives whilst controlling for total running distance. Participants were randomly assigned to one group to complete the match simulation with either a tackle shield (n = 10), tackle bag (n = 7) or no-contact (n = 10). Total PlayerLoadTM, PlayerLoadTM 2D (AU), PlayerLoadTM slow (AU) and PlayerLoadTM slow-ratio (%) were analysed from the accelerometer in addition to high- and low-speed running and sprint speed. Total PlayerLoadTM was likely lower for the Bag group compared to the Run group (498 c.f. 460 AU), with no clear differences between the other groups. 3 PlayerLoadTM slow for the Shield group (167 ± 26 AU) was very likely greater than both the Bag (133 ± 11 AU) and Run groups (128 ± 20 AU) but no clear difference was observed between the Bag and Run groups. No differences were observed in PlayerLoadTM 2D between any groups. High-speed running distance was likely lower in the Shield group (1056 ± 225 m) compared to the Bag group (1326 ± 245 m) and very likely lower compared to the Run group (1318 ± 175 m). Total PlayerLoadTM is not sensitive to contact type during simulated rugby league activity but does reflect greater high-speed running distance during a rugby league match simulation. However, PlayerLoadTM slow can detect the types of contact and might be preferred for quantifying match and training loads associated with physical contact. The purpose of the final empirical chapter (Chapter 8) was to determine the influence of contact type on in neuromuscular, perceptual and biochemical parameters associated with exercise-induced muscle damage. The participants were again assigned to one of three groups to complete the match simulation with a tackle shield (n = 6), tackle bag (n = 7) or no contact (n = 7). In addition to internal and external load measured during the match simulation, venous blood, muscle function and soreness measures were collected immediately (+0), +24 and +72 hours after the match simulation. Upper body neuromuscular performance and knee flexion torque likely decreased in the Shield group +0 and +72 hours after the simulation compared to the other groups while CMJ power likely decreased more in the Run group. All three groups demonstrated a very likely increase in IL-6 and IL-10 concentration immediately after the match simulation, but differences between the groups were unclear and values returned to baseline +24 hours after the simulation. In conclusion, current automatic tackle detection metric should be used with caution, particularly in training sessions where physical contact is replicated. Instead PlayerLoadTM and associated derivatives from the embedded accelerometer can provide a useful measure of contact-specific load during training and competitive matches. Physical contact type affected external load by modifying a participant’s running strategy during simulated match performance, thereby influencing site-specific fatigue during and after a simulated rugby league match. However, regardless of contact type, large increases in cytokine and leukocyte concentration are apparent with a return to basal values 24 hours after. Therefore it is not recommended to use such biomarkers in applied settings to quantify the magnitude of muscle damage specifically associated with physical contact.|
|dc.publisher||University of Chester||en_US|
|dc.rights||Attribution-NonCommercial-NoDerivs 3.0 United States||*|
|dc.title||Quantification of physical contact and its influence on simulated performance and recovery in rugby players.||en_US|
|dc.type||Thesis or dissertation||en_US|
|dc.rights.embargoreason||Recommended 6 month embargo period||en_US|