Browsing Sport and Exercise Sciences by Authors
The effects of physical contact type on the internal and external demands during a rugby league match simulation protocol.Norris, Jonathan; Highton, Jamie M.; Hughes, Stephen F.; Twist, Craig; University of Chester (Taylor and Francis, 2016-02-09)This study investigated how the type of contact influences physiological, perceptual and locomotive demands during a simulated rugby league match. Eleven male university rugby league players performed two trials of the rugby league movement simulation protocol for forwards (RLMSP-i) with a traditional soft tackle bag (BAG) and a weighted tackle sled (SLED) to replicate contact demands. Locomotive rate, sprint speed, tackle intensity, heart rate, rating of perceived exertion and blood lactate concentration were analysed in four periods during the first and second bout of both trials. Countermovement jump (CMJ) was measured before and immediately after each trial. More time was spent in heart rate zone between 90 – 100% HRpeak during the first (effect size ± 95% confidence interval: 0.44 ± 0.49) and second bout (0.44 ± 0.43), and larger (0.6 ± 0.69) decrements in CMJ performance were observed during SLED (5.9, s = 4.9%) compared to BAG (2.6, s = 5.4%). Sprint into contact speed was faster during BAG compared to SLED in the first (1.10 ± 0.92) and second bout (0.90 ± 0.90), which impaired high intensity running ability but did not increase physiological strain. Changing the type of contact during the match simulation subtly altered both the internal and external load on participants. These findings indicate that tackle training apparatus should be considered regarding the outcome of a training session.
The reproducibility and external validity of a modified rugby league movement simulation protocol for interchange playersNorris, Jonathan; Highton, Jamie M.; Twist, Craig; University of Chester (2019-04-01)Purpose: The study assessed the reliability and external validity of a rugby league movement simulation protocol for interchange players that was adapted to include physical contact between participants Methods: Eighteen rugby players performed two trials of a modified rugby league movement simulation protocol for interchange players (RLMSP-i), seven days apart. The simulation was conduced outdoors on artificial turf with movement speeds controlled using an audio signal. Micro-technology was used to measure locomotive and accelerometer (i.e. PlayerLoadTM) metrics for both bouts (~23 min each) alongside heart rate and RPE. Results: Reported for each bout, total distance (102 ± 3 and 101 ± 3 m.min-1), low-speed distance (77 ± 3 and 79 ± 4 m.min-1), high-speed distance (25 ± 3 and 22 ± 4 m.min-1), PlayerLoadTM (10 ± 1 and 10 ± 1 AU.min-1), PlayerLoadTM slow (3.2 ± 0.6 and 3.2 ± 0.6 AU.min-1), PlayerLoadTM 2D (6.0 ± 0.9 and 5.7 ± 0.8 AU.min-1) and heart rate (86 ± 5 and 84 ± 6 %HR max) were similar to match play. The coefficient of variation (%CV) for locomotive metrics ranged from 1.3 to 14.4%, accelerometer CV% 4.4 to 10.0%, and internal load 4.8 to 13.7%. All variables presented a CV% less than the calculated moderate change during one or both bouts of the simulation except high-speed distance (m.min-1), %HRpeak and RPE (AU). Conclusion: The modified RLMSP-i offers a reliable simulation to investigate influences of training and nutrition interventions on the movement and collision activities of rugby league interchange players.
The Unsuitability of Energy Expenditure Derived From Microtechnology for Assessing Internal Load in Collision-Based ActivitiesHighton, Jamie M.; Mullen, Thomas; Norris, Jonathan; Oxendale, Chelsea; Twist, Craig (Human Kinetics, 2016-05-25)This aim of this study was to examine the validity of energy expenditure derived from micro-technology when measured during a repeated effort rugby protocol. Sixteen male rugby players completed a repeated effort protocol comprising 3 sets of 6 collisions during which movement activity and energy expenditure (EEGPS) were measured using micro-technology. In addition, energy expenditure was also estimated from open circuit spirometry (EEVO2). Whilst related (r = 0.63, 90%CI 0.08-0.89), there was a systematic underestimation of energy expenditure during the protocol (-5.94 ± 0.67 kcalmin-1) for EEGPS (7.2 ± 1.0 kcalmin-1) compared to EEVO2 (13.2 ± 2.3 kcalmin-1). High-speed running distance (r = 0.50, 95%CI -0.66-0.84) was related to EEVO2, while Player Load was not (r = 0.37, 95%CI -0.81-0.68). Whilst metabolic power might provide a different measure of external load than other typically used micro-technology metrics (e.g. high-speed running, Player Load), it underestimates energy expenditure during intermittent team sports that involve collisions.