Search Results

You are looking at 1 - 10 of 17 items for

  • Author: Craig Twist x
Clear All Modify Search
Restricted access

Craig Twist and Jamie Highton

Rugby league is a contact team sport performed at an average intensity similar to that of other team sports (~70–80% VO2max), made up of unsystematic movements of varying type, duration, and frequency. The high number of collisions, repeated eccentric muscle contractions associated with accelerating and decelerating, and prolonged aerobic nature of rugby league matches result in the development of fatigue in the days after exercise. Monitoring the presence and magnitude of this fatigue to maximize performance and training adaptation is an important consideration for applied sports scientists. Several methods have been proposed to measure the magnitude of fatigue in athletes. Perceptual measures (eg, questionnaires) are easy to employ and are sensitive to changes in performance. However, the subjective nature of such measures should be considered. Blood biochemical markers of fatigue may provide a more objective measure of homeostatic disturbances associated with fatigue; however, the cost, level of expertise required, and high degree of variability of many of these measures often preclude them from being used in the applied setting. Accordingly, simple measure of muscle function (eg, jump height) and simulated performance offer the most practical and appropriate method of determining the extent of fatigue experienced by rugby league players. A meaningful change in each measure of fatigue for the monitoring of players can be easily determined, provided that the reliability of the measure is known. Multiplying the coefficient of variation by 0.3, 0.9, and 1.6 can be used to determine a small, moderate, and large change, respectively.

Restricted access

Jonathan P. Norris, Jamie Highton and Craig Twist

Purpose: To assess the reliability and external validity of a rugby league movement-simulation protocol for interchange players (RLMSP-i) that was adapted to include physical contact between participants. Methods: A total of 18 rugby players performed 2 trials of a modified RLMSP-i, 7 d apart. The simulation was conducted outdoors on artificial turf with movement speeds controlled using an audio signal. Microtechnology was used to measure locomotive and accelerometer (ie, PlayerLoad™) metrics for both bouts (∼23 min each) alongside heart rate (HR) and rating of perceived exertion (RPE). Results: Reported for each bout, total distance (102 [3] m·min−1 and 101 [3] m·min−1), low-speed distance (77 [3] m·min−1 and 79 [4] m·min−1), high-speed distance (25 [3] m·min−1 and 22 [4] m·min−1), PlayerLoad (10 [1] AU·min−1 and 10 [1] AU·min−1), PlayerLoad slow (3.2 [0.6] AU·min−1 and 3.2 [0.6] AU·min−1), 2-dimensional PlayerLoad (6.0 [0.9] AU·min−1 and 5.7 [0.8] AU·min−1), and HR (86 [5]%HRmax and 84 [6]%HRmax) 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 1 or both bouts of the simulation except high-speed distance, percentage of the participant’s peak HR, and RPE. 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.

Restricted access

Mark Waldron, Jamie Highton and Craig Twist

Purpose:

This study assessed the reliability of a rugby league movement-simulation protocol, relative to interchanged players (RLMSP-i).

Methods:

Fifteen male participants completed 2 trials of the RLMSP-i, separated by 1 wk. The RLMSP-i comprised low- to moderate-intensity running, interspersed by high-intensity sprinting and tackling activity, based on global positioning system (GPS) data recorded during Super League performances.

Results:

The lowest coefficient of variation (CV ± 95% CI) was observed for total m/min during both interchange bout 1 (1.1% ± 0.2%) and bout 2 (1.0% ± 0.2%). The percentage of heart rate peak and ratings of perceived exertion demonstrated CVs of 1.2–2.0% and 2.9–3.5%, respectively. The poorest agreement between trials was found for blood lactate concentration (16.2% ± 2.8%). In no case was the CV smaller than the smallest worthwhile change, yet in every case the moderate changes were larger than the CV.

Conclusions:

The RLMSP-i’s reliability is sufficient to enable the detection of moderate changes in various performance and physiological measurements that accurately simulate some, but not all, aspects of rugby league matches.

Restricted access

Jamie Highton, Thomas Mullen and Craig Twist

Purpose:

To examine the influence of knowledge of exercise duration on pacing and performance during simulated rugby league match play.

Methods:

Thirteen male university rugby players completed 3 simulated rugby league matches (RLMSP-i) on separate days in a random order. In a control trial, participants were informed that they would be performing 2 × 23-min bouts (separated by 20 min) of the RLMSP-i (CON). In a second trial, participants were informed that they would be performing 1 × 23-min bout of the protocol but were then asked to perform another 23-min bout (DEC). In a third trial, participants were not informed of the exercise duration and performed 2 × 23-min bouts (UN).

Results:

Distance covered and high-intensity running were higher in CON (4813 ± 167 m, 26 ± 4.1 m/min) than DEC (4764 ± 112 m, 25.2 ± 2.8 m/min) and UN (4744 ± 131 m, 24.4 m/min). Compared with CON, high-intensity running and peak speed were typically higher for DEC in bout 1 and lower in bout 2 of the RLMSP-i, while UN was generally lower throughout. Similarly, DEC resulted in an increased heart rate, blood lactate, and rating of perceived exertion than CON in bout 1, whereas these variables were lower throughout the protocol in UN.

Conclusions:

Pacing and performance during simulated rugby league match play depend on an accurate understanding of the exercise endpoint. Applied practitioners should consider informing players of their likely exercise duration to maximize running.

Restricted access

Thomas Mullen, Jamie Highton and Craig Twist

It is important to understand the extent to which physical contact changes the internal and external load during rugby simulations that aim to replicate the demands of match play. Accordingly, this study examined the role of physical contact on the physiological and perceptual demands during and immediately after a simulated rugby league match. Nineteen male rugby players completed a contact (CON) and a noncontact (NCON) version of the rugby league match-simulation protocol in a randomized crossover design with 1 wk between trials. Relative distance covered (ES = 1.27; ±0.29), low-intensity activity (ES = 1.13; ±0.31), high-intensity running (ES = 0.49; ±0.34), heart rate (ES = 0.52; ±0.35), blood lactate concentration (ES = 0.78; ±0.34), rating of perceived exertion (RPE) (ES = 0.72; ±0.38), and session RPE (ES = 1.45; ±0.51) were all higher in the CON than in the NCON trial. However, peak speeds were lower in the CON trial (ES = −0.99; ±0.40) despite unclear reductions in knee-extensor (ES = 0.19; ±0.40) and -flexor (ES = 0.07; ±0.43) torque. Muscle soreness was also greater after CON than in the NCON trial (ES = 0.97; ±0.55). The addition of physical contact to the movement demands of a simulated rugby league match increases many of the external and internal demands but also results in players’ slowing their peak running speed during sprints. These findings highlight the importance of including contacts in simulation protocols and training practices designed to replicate the demands of real match play.

Restricted access

Nick Dobbin, Jamie Highton, Samantha Louise Moss and Craig Twist

Purpose: To investigate the factors affecting the anthropometric and physical characteristics of elite academy rugby league players. Methods: One hundred ninety-seven elite academy rugby league players (age = 17.3 [1.0] y) from 5 Super League clubs completed measures of anthropometric and physical characteristics during a competitive season. The interaction between and influence of contextual factors on characteristics was assessed using linear mixed modeling. Results: All physical characteristics improved during preseason and continued to improve until midseason, whereafter 10-m sprint (η 2 = .20 cf .25), countermovement jump (CMJ) (η 2 = .28 cf .30), and prone Yo-Yo Intermittent Recovery (Yo-Yo IR) test (η 2 = .22 cf .54) performance declined. Second (η 2 = .17) and third (η 2 = .16) -year players were heavier than first-years, whereas third-years had slower 10-m sprint times (η 2 = .22). Large positional variability was observed for body mass, 20-m sprint time, medicine-ball throw, CMJ, and prone Yo-Yo IR1. Compared with bottom-ranked teams, top-ranked teams demonstrated superior 20-m (η 2 = −.22) and prone Yo-Yo IR1 (η 2 = .26) performance, whereas middle-ranked teams reported higher CMJ height (η 2 = .26) and prone Yo-Yo IR1 distance (η 2 = .20) but slower 20-m sprint times (η 2 = .20). Conclusion: These findings offer practitioners who design training programs for academy rugby league players insight into the relationships between anthropometric and physical characteristics and how they are influenced by playing year, league ranking, position, and season phase.

Restricted access

Jamie Highton, Thomas Mullen, Jonathan Norris, Chelsea Oxendale and Craig Twist

This aim of this study was to examine the validity of energy expenditure derived from microtechnology 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 microtechnology. In addition, energy expenditure was estimated from open-circuit spirometry (EEVO2). While related (r = .63, 90%CI .08–.89), there was a systematic underestimation of energy expenditure during the protocol (–5.94 ± 0.67 kcal/min) for EEGPS (7.2 ± 1.0 kcal/min) compared with EEVO2 (13.2 ± 2.3 kcal/min). High-speed-running distance (r = .50, 95%CI –.66 to .84) was related to EEVO2, while PlayerLoad was not (r = .37, 95%CI –.81 to .68). While metabolic power might provide a different measure of external load than other typically used microtechnology metrics (eg, high-speed running, PlayerLoad), it underestimates energy expenditure during intermittent team sports that involve collisions.

Restricted access

Chelsea L. Oxendale, Craig Twist, Matthew Daniels and Jamie Highton

Purpose:

While exercise-induced muscle damage (EIMD) after rugby league match play has been well documented, the specific match actions that contribute to EIMD are unclear. Accordingly, the purpose of this study was to investigate the positional demands of elite rugby league matches and examine their relationship with subsequent EIMD.

Methods:

Twenty-eight performances (from 17 participants) were captured using 10-Hz global positioning systems over 4 competitive matches. Upper- and lower-body neuromuscular fatigue, creatine kinase (CK), and perceived muscle soreness were assessed 24 h before and at 12, 36, and 60 h after matches.

Results:

High-intensity running was moderately higher in backs (6.6 ± 2.6 m/min) than in forwards (5.1 ± 1.6 m/min), whereas total collisions were moderately lower (31.1 ± 13.1 vs 54.1 ± 37.0). Duration (r = .90, CI: .77–.96) and total (r = .86, CI: .70–.95) and high-intensity distance covered (r = .76, CI: .51–.91) were associated (P < .05) with increased CK concentration postmatch. Total collisions and repeated high-intensity efforts were associated (P < .05) with large decrements in upper-body neuromuscular performance (r = –.48, CI: –.74 to .02; r = –.49, CI: –.77 to .05, respectively), muscle soreness (r = –.68, CI: –.87 to –.10, r = –.66, CI: –.89 to .21, respectively), and CK concentration (r = .67, CI: .42–.85; r = .73, CI: .51–.87, respectively). All EIMD markers returned to baseline within 60 h.

Conclusion:

Match duration, high-intensity running, and collisions were associated with variations in EIMD markers, suggesting that recovery is dependent on individual match demands.

Restricted access

Nicola Marsh, Nick Dobbin, Craig Twist and Chris Curtis

This study assessed energy intake and expenditure of international female touch players during an international tournament. Energy intake (food diary) and expenditure (accelerometer, global positioning system) were recorded for 16 female touch players during a four-day tournament, competing in 8.0 ± 1.0 matches; two on Days 1, 2, and 4, and three on Day 3. Total daily energy expenditure (43.6 ± 3.1 Kcal·kg-1 body mass (BM)) was not different (p > .05) from energy intake (39.9 ± 9.4 Kcal·kg-1 BM). Carbohydrate intakes were below current recommendations (6–10 g·kg-1 BM) on Days 1 (4.4 ± 0.6 g·kg-1 BM) and 3 (4.7 ± 1.0 g·kg-1 BM) and significantly below (p < .05) on Day 2 (4.1 ± 1.0 g·kg-1 BM). Protein and fat intakes were consistent with recommendations (protein, 1.2–2.0 g·kg-1 BM: fat, 20–35% total Kcal) across Days 1–3 (protein, 1.9 ± 0.8, 2.2 ± 0.8, and 2.0 ± 0.7 g·kg-1 BM; fat, 35.6 ± 6.8, 38.5 ± 6.4, and 35.9 ± 5.4% total Kcal). Saturated fat intakes were greater (p < .05) than recommendations (10% total Kcal) on Days 1–3 (12.4 ± 2.9, 14.2 ± 5.1, and 12.7 ± 3.5% total Kcal). On average, female touch players maintained energy balance. Carbohydrate intakes appeared insufficient and might have contributed to the reduction (p < .05) in high-intensity running on Day 3. Further research might investigate the applicability of current nutrition recommendations and the role of carbohydrate in multimatch, multiday tournaments.

Restricted access

Craig Twist, Jamie Highton, Matthew Daniels, Nathan Mill and Graeme Close

Player loads and fatigue responses are reported in 15 professional rugby league players (24.3 ± 3.8 y) during a period of intensified fixtures. Repeated measures of internal and external loads, perceived well-being, and jump flight time were recorded across 22 d, comprising 9 training sessions and matches on days 5, 12, 15, and 21 (player exposure: 3.6 ± 0.6 matches). Mean training loads (session rating of perceived exertion × duration) between matches were 1177, 1083, 103, and 650 AU. Relative distance in match 1 (82 m/min) and match 4 (79 m/min) was very likely lower in match 2 (76 m/min) and likely higher in match 3 (86 m/min). High-intensity running (≥5.5 m/s) was likely to very likely lower than match 1 (5 m/min) in matches 2–4 (2, 4, and 3 m/min, respectively). Low-intensity activity was likely to very likely lower than match 1 (78 m/min) in match 2 (74 m/min) and match 4 (73 m/min) but likely higher in match 3 (81 m/min). Accumulated accelerometer loads for matches 1–4 were 384, 473, 373, and 391 AU, respectively. Perceived well-being returned to baseline values (~21 AU) before all matches but was very likely to most likely lower the day after each match (~17 AU). Prematch jump flight times were likely to most likely lower across the period, with mean values of 0.66, 0.65, 0.62, and 0.64 s before matches 1–4, respectively. Across a 22-d cycle with fixture congestion, professional rugby league players experience cumulative neuromuscular fatigue and impaired match running performance.