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Establishing Duration-Specific Running Intensities From Match-Play Analysis in Rugby League

Jace A. Delaney, Tannath J. Scott, Heidi R. Thornton, Kyle J.M. Bennett, David Gay, Grant M. Duthie, and Ben J. Dascombe

Rugby league coaches often prescribe training to replicate the demands of competition. The intensities of running drills are often monitored in comparison with absolute match-play measures. Such measures may not be sensitive enough to detect fluctuations in intensity across a match or to differentiate between positions.

Purpose:

To determine the position- and duration-specific running intensities of rugby league competition, using a moving-average method, for the prescription and monitoring of training.

Methods:

Data from a 15-Hz global positioning system (GPS) were collected from 32 professional rugby league players across a season. The velocity–time curve was analyzed using a rolling-average method, where maximum values were calculated for 10 different durations, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 min, for each player across each match.

Results:

There were large differences between the 1- and 2-min rolling averages and all other rolling-average durations. Smaller differences were observed for rolling averages of greater duration. Fullbacks maintained a greater velocity than outside backs and middle and edge forwards over the 1- and 2-min rolling averages (ES 0.8−1.2, P < .05). For rolling averages 3 min and greater, the running demands of the fullbacks were greater than those of the middle forwards and outside backs (ES 1.1−1.4, P < .05).

Conclusions:

These findings suggest that the running demands of rugby league fluctuate vastly across a match. Fullbacks were the only position to exhibit a greater running intensity than any other position, and therefore training prescription should reflect this.

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Optimizing Preseason Training Loads in Australian Football

David L. Carey, Justin Crow, Kok-Leong Ong, Peter Blanch, Meg E. Morris, Ben J. Dascombe, and Kay M. Crossley

Purpose: To investigate whether preseason training plans for Australian football can be computer generated using current training-load guidelines to optimize injury-risk reduction and performance improvement. Methods: A constrained optimization problem was defined for daily total and sprint distance, using the preseason schedule of an elite Australian football team as a template. Maximizing total training volume and maximizing Banister-model-projected performance were both considered optimization objectives. Cumulative workload and acute:chronic workload-ratio constraints were placed on training programs to reflect current guidelines on relative and absolute training loads for injury-risk reduction. Optimization software was then used to generate preseason training plans. Results: The optimization framework was able to generate training plans that satisfied relative and absolute workload constraints. Increasing the off-season chronic training loads enabled the optimization algorithm to prescribe higher amounts of “safe” training and attain higher projected performance levels. Simulations showed that using a Banister-model objective led to plans that included a taper in training load prior to competition to minimize fatigue and maximize projected performance. In contrast, when the objective was to maximize total training volume, more frequent training was prescribed to accumulate as much load as possible. Conclusions: Feasible training plans that maximize projected performance and satisfy injury-risk constraints can be automatically generated by an optimization problem for Australian football. The optimization methods allow for individualized training-plan design and the ability to adapt to changing training objectives and different training-load metrics.

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Predicting Self-Reported Illness for Professional Team-Sport Athletes

Heidi R. Thornton, Jace A. Delaney, Grant M. Duthie, Brendan R. Scott, William J. Chivers, Colin E. Sanctuary, and Ben J. Dascombe

Purpose:

To identify contributing factors to the incidence of illness for professional team-sport athletes, using training load (TL), self-reported illness, and well-being data.

Methods:

Thirty-two professional rugby league players (26.0 ± 4.8 y, 99.1 ± 9.6 kg, 1.84 ± 0.06 m) were recruited from the same club. Players participated in prescribed training and responded to a series of questionnaires to determine the presence of self-reported illness and markers of well-being. Internal TL was determined using the session rating of perceived exertion. These data were collected over 29 wk, across the preparatory and competition macrocycles.

Results:

The predictive models developed recognized increases in internal TL (strain values of >2282 AU, weekly TL >2786 AU, and monotony >0.78 AU) to best predict when athletes are at increased risk of self-reported illness. In addition, a reduction in overall well-being (<7.25 AU) in the presence of increased internal TL, as previously stated, was highlighted as a contributor to self-reported-illness occurrence.

Conclusions:

These results indicate that self-report data can be successfully used to provide a novel understanding of the interactions between competition-associated stressors experienced by professional team-sport athletes and their susceptibility to illness. This may help coaching staff more effectively monitor players during the season and potentially implement preventive measures to reduce the likelihood of illnesses occurring.

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Acceleration-Based Running Intensities of Professional Rugby League Match Play

Jace A. Delaney, Grant M. Duthie, Heidi R. Thornton, Tannath J. Scott, David Gay, and Ben J. Dascombe

Rugby league involves frequent periods of high-intensity running including acceleration and deceleration efforts, often occurring at low speeds.

Purpose:

To quantify the energetic cost of running and acceleration efforts during rugby league competition to aid in prescription and monitoring of training.

Methods:

Global positioning system (GPS) data were collected from 37 professional rugby league players across 2 seasons. Peak values for relative distance, average acceleration/deceleration, and metabolic power (Pmet) were calculated for 10 different moving-average durations (1–10 min) for each position. A mixed-effects model was used to assess the effect of position for each duration, and individual comparisons were made using a magnitude-based-inference network.

Results:

There were almost certainly large differences in relative distance and Pmet between the 10-min window and all moving averages <5 min in duration (ES = 1.21–1.88). Fullbacks, halves, and hookers covered greater relative distances than outside backs, edge forwards, and middle forwards for moving averages lasting 2–10 min. Acceleration/deceleration demands were greatest in hookers and halves compared with fullbacks, middle forwards, and outside backs. Pmet was greatest in hookers, halves, and fullbacks compared with middle forwards and outside backs.

Conclusions:

Competition running intensities varied by both position and moving-average duration. Hookers exhibited the greatest Pmet of all positions, due to high involvement in both attack and defense. Fullbacks also reached high Pmet, possibly due to a greater absolute volume of running. This study provides coaches with match data that can be used for the prescription and monitoring of specific training drills.

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Validity of Skinfold-Based Measures for Tracking Changes in Body Composition in Professional Rugby League Players

Jace A. Delaney, Heidi R. Thornton, Tannath J. Scott, David A. Ballard, Grant M. Duthie, Lisa G. Wood, and Ben J. Dascombe

High levels of lean mass are important in collision-based sports for the development of strength and power, which may also assist during contact situations. While skinfold-based measures have been shown to be appropriate for cross-sectional assessments of body composition, their utility in tracking changes in lean mass is less clear.

Purpose:

To determine the most effective method of quantifying changes in lean mass in rugby league athletes.

Methods:

Body composition of 21 professional rugby league players was assessed on 2 or 3 occasions separated by ≥6 wk, including bioelectrical impedance analysis (BIA), leanmass index (LMI), and a skinfold-based prediction equation (SkF). Dual-X-ray absorptiometry provided a criterion measure of fat-free mass (FFM). Correlation coefficients (r) and standard errors of the estimate (SEE) were used as measures of validity for the estimates.

Results:

All 3 practical estimates exhibited strong validity for cross-sectional assessments of FFM (r > .9, P < .001). The correlation between change scores was stronger for the LMI (r = .69, SEE 1.3 kg) and the SkF method (r = .66, SEE = 1.4 kg) than for BIA (r = .50, SEE = 1.6 kg).

Conclusions:

The LMI is probably as accurate in predicting changes in FFM as SkF and very likely to be more appropriate than BIA. The LMI offers an adequate, practical alternative for assessing in FFM among rugby league athletes.

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Effects of a 2-Week High-Intensity Training Camp on Sleep Activity of Professional Rugby League Athletes

Heidi R. Thornton, Grant M. Duthie, Nathan W. Pitchford, Jace A. Delaney, Dean T. Benton, and Ben J. Dascombe

Purpose:

To investigate the effects of a training camp on the sleep characteristics of professional rugby league players compared with a home period.

Methods:

During a 7-d home and 13-d camp period, time in bed (TIB), total sleep time (TST), sleep efficiency (SE), and wake after sleep onset were measured using wristwatch actigraphy. Subjective wellness and training loads (TL) were also collected. Differences in sleep and TL between the 2 periods and the effect of daytime naps on nighttime sleep were examined using linear mixed models. Pearson correlations assessed the relationship of changes in TL on individuals’ TST.

Results:

During the training camp, TST (–85 min), TIB (–53 min), and SE (–8%) were reduced compared with home. Those who undertook daytime naps showed increased TIB (+33 min), TST (+30 min), and SE (+0.9%). Increases in daily total distance and training duration above individual baseline means during the training camp shared moderate (r = –.31) and trivial (r = –.04) negative relationships with TST.

Conclusions:

Sleep quality and quantity may be compromised during training camps; however, daytime naps may be beneficial for athletes due to their known benefits, without being detrimental to nighttime sleep.

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Peak Running Intensity of International Rugby: Implications for Training Prescription

Jace A. Delaney, Heidi R. Thornton, John F. Pryor, Andrew M. Stewart, Ben J. Dascombe, and Grant M. Duthie

Purpose:

To quantify the duration and position-specific peak running intensities of international rugby union for the prescription and monitoring of specific training methodologies.

Methods:

Global positioning systems (GPS) were used to assess the activity profile of 67 elite-level rugby union players from 2 nations across 33 international matches. A moving-average approach was used to identify the peak relative distance (m/min), average acceleration/deceleration (AveAcc; m/s2), and average metabolic power (Pmet) for a range of durations (1–10 min). Differences between positions and durations were described using a magnitude-based network.

Results:

Peak running intensity increased as the length of the moving average decreased. There were likely small to moderate increases in relative distance and AveAcc for outside backs, halfbacks, and loose forwards compared with the tight 5 group across all moving-average durations (effect size [ES] = 0.27–1.00). Pmet demands were at least likely greater for outside backs and halfbacks than for the tight 5 (ES = 0.86–0.99). Halfbacks demonstrated the greatest relative distance and Pmet outputs but were similar to outside backs and loose forwards in AveAcc demands.

Conclusions:

The current study has presented a framework to describe the peak running intensities achieved during international rugby competition by position, which are considerably higher than previously reported whole-period averages. These data provide further knowledge of the peak activity profiles of international rugby competition, and this information can be used to assist coaches and practitioners in adequately preparing athletes for the most demanding periods of play.