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Activity Profiles and Demands of Seasonal and Tournament Basketball Competition

Markus J. Klusemann, David B. Pyne, Will G. Hopkins, and Eric J. Drinkwater

Competition-specific conditioning for tournament basketball games is challenging, as the demands of tournament formats are not well characterized.

Purpose:

To compare the physical, physiological, and tactical demands of seasonal and tournament basketball competition and determine the pattern of changes within an international tournament.

Methods:

Eight elite junior male basketball players (age 17.8 ± 0.2 y, height 1.93 ± 0.07 m, mass 85 ± 3 kg; mean ± SD) were monitored in 6 seasonal games played over 4 mo in an Australian second-division national league and in 7 games of an international under-18 tournament played over 8 days. Movement patterns and tactical elements were coded from video and heart rates recorded by telemetry.

Results:

The frequency of running, sprinting, and shuffling movements in seasonal games was higher than in tournament games by 8–15% (99% confidence limits ± ~8%). Within the tournament, jogging and low- to medium-intensity shuffling decreased by 15–20% (± ~14%) over the 7 games, while running, sprinting, and high-intensity shuffling increased 11–81% (± ~25%). There were unclear differences in mean and peak heart rates. The total number of possessions was higher in seasonal than in tournament games by 8% (± 10%).

Conclusions:

Coaches should consider a stronger emphasis on strength and power training in their conditioning programs to account for the higher activity of seasonal games. For tournament competition, strategies that build a sufficient aerobic capacity and neuromuscular resilience to maintain high-intensity movements need to be employed. A focus on half-court tactics accounts for the lower number of possessions in tournaments.

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Performance Science Domains: Contemporary Strategies for Teams Preparing for the Rugby World Cup

Liam P. Kilduff, David B. Pyne, and Christian J. Cook

Purpose: As the start of the 10th Rugby Union World Cup approaches, performance staff will be working on the final elements of their teams’ preparation. Much of this planning and preparation will be underpinned by the latest performance science research. In this invited commentary, we discuss contemporary performance science research in rugby union centered around 4 key performance domains. First, we outline a systematic approach to developing an overall understanding of the game demands and how performance staff can enhance the players’ preparedness for competition. We then move on to outline our understanding of the training science domain, followed by a brief overview of effective recovery strategies at major tournaments. Finally, we outline research in the area of competition-day strategies and how they can positively impact players’ readiness to compete. Conclusions: Evaluating a team’s preparation for the Rugby Union World Cup can be achieved by mapping their performance plan based on the 4 domains outlined above.

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Variability in Power Output During Cycling in International Olympic-Distance Triathlon

Naroa Etxebarria, Shaun D’Auria, Judith M. Anson, David B. Pyne, and Richard A. Ferguson

Purpose:

The patterns of power output in the ~1-h cycle section of Olympic-distance triathlon races are not well documented. Here the authors establish a typical cycling-race profile derived from several International Triathlon Union elite-level draftinglegal triathlon races.

Methods:

The authors collated 12 different race power profiles from elite male triathletes (N = 5, age 25 ± 5 y, body mass 65.5 ± 5.6 kg; mean ± SD) during 7 international races. Power output was recorded using SRM cranks and analyzed with proprietary software.

Results:

The mean power output was 252 ± 33 W, or 3.9 ± 0.5 W/kg in relative terms, with a coefficient of variation of 71% ± 13%. Normalized power (power output an athlete could sustain if intensity were maintained constant without any variability) for the entire cycle section was 291 ± 29 W, or 40 ± 13 W higher than the actual mean power output. There were 34 ± 14 peaks of power output above 600 W and ~18% time spent at >100% of maximal aerobic power.

Conclusion:

Cycling during Olympic-distance triathlon, characterized by frequent and large power variations including repeat supramaximal efforts, equates to a higher workload than cycling at constant power.

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Physiological Measures Tracking Seasonal Changes in Peak Running Speed

Philo U. Saunders, Amanda J. Cox, Will G. Hopkins, and David B. Pyne

It is unclear whether physiological measures monitored in an incremental treadmill test during a training season provide useful diagnostic information about changes in distance running performance.

Purpose:

To quantify the relationship between changes in physiological measures and performance (peak running speed) over a training season.

Methods:

Well-trained distance runners (34 males; VO2max 64 ± 6 mL⋅kg-1⋅min-1, mean ± SD) completed four incremental treadmill tests over 17 wk. The tests provided values of peak running speed, VO2max, running economy, and lactate threshold (as speed and %VO2max). The physiological measures were included in simple and multiple linear regression models to quantify the relationship between changes in these measures and changes in peak speed.

Results:

The typical within-subject variation in peak speed from test to test was 2.5%, whereas those for physiological measures were VO2max (mL⋅min-1⋅kg-1) 3.0%, economy (m⋅kg⋅mL–1) 3.6%, lactate threshold (%VO2max) 8.7%, and body mass 1.8%. In simple models these typical changes predicted the following changes in performance: VO2max 1.4%, economy 0.8%, lactate threshold –0.3%, and body mass –0.2% (90% confidence limits ~±0.7%); the corresponding correlations with performance were 0.57, 0.33, –0.05, and –0.13 respectively (~±0.20). In a multiple linear regression model, the contribution of each physiological variable to performance changed little after adjustment for the other variables.

Conclusion:

Change in VO2max in an incremental test during a running season is a good predictor of change in peak running speed, change in running economy is a moderate predictor, and lactate threshold and body mass provide little additional information.

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Effect of Carbohydrate Intake on Half-Marathon Performance of Well-Trained Runners

Louise M. Burke, Clare Wood, David B. Pyne, Richard D. Telford, and Philo U. Saunders

Eighteen highly-trained runners ran two half marathons in mild environmental conditions, 3 wk apart, consuming either 426 ± 227 mL of a flavored placebo drink (PLACEBO) or an equivalent volume of water (386 ± 185 mL) and a commercial gel (GEL) supplying 1.1 ± 0.2 g/kg body mass (BM) carbohydrate (CHO). Voluntary consumption of this fluid was associated with a mean BM change of ~ 2.4%. Runners performed better in their second race by 0.9% or 40 s (P = 0.03). Three runners complained of gastrointestinal discomfort in GEL trial, which produced a clear impairment of half-marathon performance by 2.4% or 105 s (P = 0.03 ) . The effect of GEL on performance was trivial: time was improved b y 0.3% or 14 s compared with PLACEBO (P = 0.52). Consuming the gel was associated with a 2.4% slower time through the 2 × 200 m feed zone; adding a trivial ~ 2 s to race time. Although benefits to half marathon performance were not detected, the theoretical improvement during 1-h exercise with CHO intake merits further investigation.

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Morning Exercise: Enhancement of Afternoon Sprint-Swimming Performance

Courtney J. McGowan, David B. Pyne, Kevin G. Thompson, John S. Raglin, and Ben Rattray

Context:

An exercise bout completed several hours prior to an event may improve competitive performance later that same day.

Purpose:

To examine the influence of morning exercise on afternoon sprint-swimming performance.

Methods:

Thirteen competitive swimmers (7 male, mean age 19 ± 3 y; 6 female, mean age 17 ± 3 y) completed a morning session of 1200 m of variedintensity swimming (SwimOnly), a combination of varied-intensity swimming and a resistance-exercise routine (SwimDry), or no morning exercise (NoEx). After a 6-h break, swimmers completed a 100-m time trial.

Results:

Time-trial performance was faster in SwimOnly (1.6% ± 0.6, mean ± 90% confidence limit, P < .01) and SwimDry (1.7% ± 0.7%, P < .01) than in NoEx. Split times for the 25- to 50-m distance were faster in both SwimOnly (1.7% ± 1.2%, P = .02) and SwimDry (1.5% ± 0.8%, P = .01) than in NoEx. The first 50-m stroke rate was higher in SwimOnly (0.70 ± 0.21 Hz, mean ± SD, P = .03) and SwimDry (0.69 ± 0.18 Hz, P = .05) than in NoEx (0.64 ± 0.16 Hz). Before the afternoon session, core (0.2°C ± 0.1°C [mean ± 90% confidence limit], P = .04), body (0.2°C ± 0.1°C, P = .02), and skin temperatures (0.3°C ± 0.3°C, P = .02) were higher in SwimDry than in NoEx.

Conclusions:

Completion of a morning swimming session alone or together with resistance exercise can substantially enhance sprint-swimming performance completed later the same day.

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Predicting a Nation’s Olympic-Qualifying Swimmers

Sian V. Allen, Tom J. Vandenbogaerde, David B. Pyne, and Will G. Hopkins

Talent identification and development typically involve allocation of resources toward athletes selected on the basis of early-career performance.

Purpose:

To compare 4 methods for early-career selection of Australia’s 2012 Olympic-qualifying swimmers.

Methods:

Performance times from 5738 Australian swimmers in individual Olympic events at 101 competitions from 2000 to 2012 were analyzed as percentages of world-record times using 4 methods that retrospectively simulated early selection of swimmers into a talent-development squad. For all methods, squad-selection thresholds were set to include 90% of Olympic qualifiers. One method used each swimmer’s given-year performance for selection, while the others predicted each swimmer’s 2012 performance. The predictive methods were regression and neural-network modeling using given-year performance and age and quadratic trajectories derived using mixed modeling of each swimmer’s annual best career performances up to the given year. All methods were applied to swimmers in 2007 and repeated for each subsequent year through 2011.

Results:

The regression model produced squad sizes of 562, 552, 188, 140, and 93 for the years 2007 through 2011. Corresponding proportions of the squads consisting of Olympic qualifiers were 11%, 11%, 32%, 43%, and 66%. Neural-network modeling produced similar outcomes, but the other methods were less effective. Swimming Australia’s actual squads ranged from 91 to 67 swimmers but included only 50−74% of Olympic qualifiers.

Conclusions:

Large talent-development squads are required to include most eventual Olympic qualifiers. Criteria additional to age and performance are needed to improve early selection of swimmers to talent-development squads.

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Evaluating Warm-Up Strategies for Elite Sprint Breaststroke Swimming Performance

Courtney J. McGowan, David B. Pyne, Kevin G. Thompson, and Ben Rattray

Purpose:

Targeted passive heating and completion of dryland-based activation exercises within the warm-up can enhance sprint freestyle performance. The authors investigated if these interventions would also elicit improvements in sprint breaststroke swimming performance.

Methods:

Ten national and internationally competitive swimmers (~805 FINA (Fédération internationale de natation) 2014 scoring points; 6 men, mean ± SD 20 ± 1 y; 4 women, 21 ± 3 y) completed a standardized pool warm-up (1550 m) followed by a 30-min transition phase and a 100-m breaststroke time trial. In the transition phase, swimmers wore a conventional tracksuit and remained seated (control) or wore tracksuit pants with integrated heating elements and performed a 5-min dryland-based exercise routine (combo) in a crossover design.

Results:

Performance in the 100-m time trial (control: 68.6 ± 4.0 s, combo: 68.4 ± 3.9 s, P = .55) and start times to 15 m (control: 7.3 ± 0.6 s; combo: 7.3 ± 0.6 s; P = .81) were not different between conditions. It was unclear (P = .36) whether combo (–0.12°C ± 0.19°C [mean ± 90% confidence limits]) elicited an improvement in core temperature maintenance in the transition phase compared with control (–0.31°C ± 0.19°C). Skin temperature immediately before commencement of the time trial was higher (by ~1°C, P = .01) within combo (30.13°C ± 0.88°C [mean ± SD]) compared with control (29.11°C ± 1.20°C). Lower-body power output was not different between conditions before the time trial.

Conclusions:

Targeted passive heating and completion of dryland-based activation exercises in the transition phase does not enhance sprint breaststroke performance despite eliciting elevated skin temperature immediately before time trial commencement.

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Partial-Body Cryotherapy Exposure 2 Hours Prior to a Shuttle Run Does Not Enhance Running Performance

Emily M. Partridge, Julie Cooke, Andrew J. McKune, and David B. Pyne

Purpose: To determine whether a single acute preexercise bout of partial-body cryotherapy (PBC) enhanced maximal-effort shuttle run performance, salivary enzyme concentration, and self-reported performance readiness. Methods: A total of 18 male rugby league players (age = 20.1 [0.5] y; mass = 91.4 [12.4] kg) were exposed to either PBC for 3 minutes at −136°C (1°C) or a control condition prior to a continuous, high-intensity 6 × 40-m shuttle run test. Passive saliva samples were collected to determine salivary alpha amylase (sAA) concentration. Perceived performance readiness and well-being questionnaires were completed using a 1-to-7 Likert scale. Results: The PBC exposure did not elicit a greater improvement in 6 × 40-m shuttle run performance in comparison with the control condition (standardized difference; +0.4 [5.9%]; P = .881; mean ± 90% confidence limits). The increase in sAA concentration was moderately greater 15 minutes after PBC compared with the control group (+67 [32%], P = .012) and remained moderately higher up to 2 hours post-PBC exposure compared with the control condition (+41 [40%], P = .045). There were greater improvements in self-reported perceptions of muscle soreness (+0.6 [0.4%], P = .043; units ±90% confidence limits) and mood (+0.6 [0.7%], P = .038) after PBC compared with control. Conclusions: It appears that a single 3-minute bout of PBC does not augment maximal effort shuttle run performance in elite rugby league players. Beneficial increases in sAA concentration, coupled with improved perceptions of muscle soreness and mood, should be explored further for alternative training or precompetition practices.

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Relationships Between Physical Testing and Match Activity Profiles Across the Australian Football League Participation Pathway

Jade A.Z. Haycraft, Stephanie Kovalchik, David B. Pyne, and Sam Robertson

Purpose: To establish levels of association between physical fitness and match activity profiles of players in the Australian Football League (AFL) participation pathway. Methods: Players (N = 287, range 10.9–19.1 y) were assessed on 20-m sprint, AFL agility, vertical jump and running vertical jump, 20-m multistage fitness test (MSFT), and Athletic Abilities Assessment. Match activity profiles were obtained from global positioning system measures: relative speed, maximal velocity, and relative high-speed running. Results: Correlational analyses revealed moderate relationships between sprint (r = .32–.57, P ≤ .05) and jump test scores (r = .34–.78, P ≤ .05) and match activity profiles in Local U12, Local U14, National U16, and National U18s, except jump tests in National U18s. AFL agility was also moderate to strongly associated in Local U12, Local U14, Local U18, and National U16s (r = .37–.87, P ≤ .05) and strongly associated with relative speed in Local U18s (r = .84, P ≤ .05). Match relative speed and high-speed running were moderate to strongly associated with 20-m MSFT in Local U14, Local U18, and National U18s (r = .41–.95, P ≤ .05) and Athletic Abilities Assessment in Local U12 and Local U18s (r = .35–.67, P ≤ .05). Match activity profile demands increased between Local U12 and National U16s, then plateaued. Conclusions: Physical fitness relates more strongly to match activity profiles in younger adolescent and national-level players. Recruiters should consider adolescent physical fitness and match activity profiles as dynamic across the AFL participation pathway.