The body of research that reports the relevance of sleep in high-performance sports is growing steadily. While the identification of sleep cycles and diagnosis of sleep disorders are limited to lab-based assessment via polysomnography, the development of activity-based devices estimating sleep patterns provides greater insight into the sleep behavior of athletes in ecological settings. Generally, small sleep quantity and/or poor quality appears to exist in many athletic populations, although this may be related to training and competition context. Typical sleep-affecting factors are the scheduling of training sessions and competitions, as well as impaired sleep onset as a result of increased arousal prior to competition or due to the use of electronic devices before bedtime. Further challenges are travel demands, which may be accompanied by jet-lag symptoms and disruption of sleep habits. Promotion of sleep may be approached via behavioral strategies such as sleep hygiene, extending nighttime sleep, or daytime napping. Pharmacological interventions should be limited to clinically induced treatments, as evidence among healthy and athletic populations is lacking. To optimize and manage sleep in athletes, it is recommended to implement routine sleep monitoring on an individual basis.
Sarah Kölling, Rob Duffield, Daniel Erlacher, Ranel Venter and Shona L. Halson
Dionne A. Noordhof, Carl Foster, Marco J.M. Hoozemans and Jos J. de Koning
Speed skating posture, or technique, is characterized by the push-off angle or effectiveness (e), determined as the angle between the push-off leg and the ice; the preextension knee angle (θ 0); and the trunk angle (θ 1). Together with muscle-power output and environmental conditions, skating posture, or technique, determines velocity (v).
To gain insight into technical variables that are important to skate efficiently and perform well, e, θ 0, θ 1, and skating v were determined every lap during a 5000-m World Cup. Second, the authors evaluated if changes (Δ) in e, θ 0, and θ 1 are associated with Δv.
One camera filmed the skaters from a frontal view, from which e was determined. Another camera filmed the skaters from a sagittal view, from which θ 0 and θ 1 were determined. Radio-frequency identification tags around the ankles of the skaters measured v.
During the race, e progressively increased and v progressively decreased, while θ 0 and θ 1 showed a less consistent pattern of change. Generalized estimating equations showed that Δe is significantly associated with Δv over the midsection of the race (β = −0.10, P < .001) and that Δθ 0 and Δθ 1 are not significantly associated with Δv.
The decrease in skating v over the race is not due to increases in power losses to air friction, as knee and trunk angle were not significantly associated with changes in velocity. The decrease in velocity can be partly ascribed to the decrease in effectiveness, which reflects a decrease in power production associated with fatigue.
Scott R. Brown, Matt Brughelli and Lee A. Bridgeman
Muscle imbalances aid in the identification of athletes at risk for lower-extremity injury. Little is known regarding the influence that leg preference or playing position may have on lower-extremity muscle strength and asymmetry.
To investigate lower-extremity strength profiles in rugby union athletes and compare isokinetic knee- and hip-strength variables between legs and positions.
Thirty male academy rugby union athletes, separated into forwards (n = 15) and backs (n = 15), participated in this cross-sectional analysis. Isokinetic dynamometry was used to evaluate peak torque, angle of peak torque, and strength ratios of the preferred and nonpreferred legs during seated knee extension/flexion and supine hip extension/flexion at 60°/s.
Backs were older (ES = 1.6) but smaller in stature (ES = –0.47) and body mass (ES = –1.3) than the forwards. The nonpreferred leg was weaker than the preferred leg for forwards during extension (ES = –0.37) and flexion (ES = –0.21) actions and for backs during extension (ES = –0.28) actions. Backs were weaker at the knee than forwards in the preferred leg during extension (ES = –0.50) and flexion (ES = –0.66) actions. No differences were observed in strength ratios between legs or positions. Backs produced peak torque at longer muscle lengths in both legs at the knee (ES = –0.93 to –0.94) and hip (ES = –0.84 to –1.17) than the forwards.
In this sample of male academy rugby union athletes, the preferred leg and forwards displayed superior strength compared with the nonpreferred leg and backs. These findings highlight the importance of individualized athletic assessments to detect crucial strength differences in male rugby union athletes.
Nicola Furlan, Mark Waldron, Kathleen Shorter, Tim J. Gabbett, John Mitchell, Edward Fitzgerald, Mark A. Osborne and Adrian J. Gray
To investigate temporal variation in running intensity across and within halves and evaluate the agreement between match-analysis indices used to identify fluctuations in running intensity in rugby sevens.
Data from a 15-Hz global positioning system (GPS) were collected from 12 elite rugby sevens players during the IRB World Sevens Series (N = 21 full games). Kinematic (eg, relative distance [RD]) and energetic (eg, metabolic power [MP]) match-analysis indices were determined from velocity–time curves and used to investigate between-halves variations. Mean MP and RD were used to identify peak 2-minute periods of play. Adjacent 2-minute periods (prepeak and postpeak) were compared with peak periods to identify changes in intensity. MP and RD were expressed relative to maximal oxygen uptake (V̇O2max) and speed at V̇O2max, respectively, and compared in their ability to describe the intensity of peak periods and their temporal occurrence.
Small to moderate reductions were present for kinematic (RD; 8.9%) and energetic (MP; 6%) indices between halves. Peak periods (RD = 130 m/min, MP =13 W/kg) were higher (P < .001) than the match average (RD = 94 m/min, MP = 9.5 W/kg) and the prepeak and postpeak periods (P < .001). RD underestimated the intensity of peak periods compared with MP (bias 16%, limits of agreement [LoA] ± 6%). Peak periods identified by RD and MP were temporally dissociated (bias 21 s, LoA ± 212 s).
The findings suggest that running intensity varies between and within halves; however, the index used will influence both the magnitude and the temporal identification of peak periods.
Dionne A. Noordhof, Carl Foster, Marco J.M. Hoozemans and Jos J. de Koning
A meaningful association between changes (Δ) in push-off angle or effectiveness (e) and changes in skating velocity (v) has been found during 5000-m races, although no significant association was found between changes in knee (θ0) and trunk angle (θ1) and Δv. It might be that speed skating event, sex, and performance level influence these associations.
To study the effect of skating event, sex, and performance level on the association between Δe and Δv and between Δθ0 and Δθ1 and Δv.
Video recordings were made from frontal (e) and sagittal views (θ0 and θ1) during 1500- and 5000-m men’s and women’s World Cup races. Radio-frequency identification tags provided data of v.
Skating event influenced the association between Δe and Δv, which resulted in a significant association between Δe and Δv for the 5000-m (β = –0.069, 95% confidence interval [–0.11, –0.030]) but not for the 1500-m (β = –0.011 [–0.032, 0.010]). The association between Δθ0 and Δθ1 and Δv was not significantly influenced by skating event. Sex and performance level did not substantially affect the association between Δe and Δv and between Δθ0 and Δθ1 and Δv.
Skating event significantly influenced the association between Δe and Δv; a 1° change in e results in a 0.011-m/s decrease in v during the 1500-m and a 0.069-m/s decrease in v during the 5000-m. Thus, it seems especially important to maintain a small e during the 5000-m.
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.
To compare 4 methods for early-career selection of Australia’s 2012 Olympic-qualifying swimmers.
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.
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.
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.
Thiago Oliveira Borges, Ben Dascombe, Nicola Bullock and Aaron J. Coutts
This study aimed to profile the physiological characteristics of junior sprint kayak athletes (n = 21, VO2max 4.1 ± 0.7 L/min, training experience 2.7 ± 1.2 y) and to establish the relationship between physiological variables (VO2max, VO2 kinetics, muscle-oxygen kinetics, paddling efficiency) and sprint kayak performance. VO2max, power at VO2max, power:weight ratio, paddling efficiency, VO2 at lactate threshold, and whole-body and muscle oxygen kinetics were determined on a kayak ergometer in the laboratory. Separately, on-water time trials (TT) were completed over 200 m and 1000 m. Large to nearly perfect (−.5 to −.9) inverse relationships were found between the physiological variables and on-water TT performance across both distances. Paddling efficiency and lactate threshold shared moderate to very large correlations (−.4 to −.7) with 200- and 1000-m performance. In addition, trivial to large correlations (−.11 to −.5) were observed between muscle-oxygenation parameters, muscle and whole-body oxygen kinetics, and performance. Multiple regression showed that 88% of the unadjusted variance for the 200-m TT performance was explained by VO2max, peripheral muscle deoxygenation, and maximal aerobic power (P < .001), whereas 85% of the unadjusted variance in 1000-m TT performance was explained by VO2max and deoxyhemoglobin (P < .001). The current findings show that well-trained junior sprint kayak athletes possess a high level of relative aerobic fitness and highlight the importance of the peripheral muscle metabolism for sprint kayak performance, particularly in 200-m races, where finalists and nonfinalists are separated by very small margins. Such data highlight the relative aerobic-fitness variables that can be used as benchmarks for talent-identification programs or monitoring longitudinal athlete development. However, such approaches need further investigation.
Countering Psychological Characteristics in Talent Identification and Development Áine MacNamara * Dave Collins * 3 2015 29 29 1 1 73 73 81 81 10.1123/tsp.2014-0021 Cliques in Sport: Perceptions of Intercollegiate Athletes Luc J. Martin * Jessi Wilson * M. Blair Evans * Kevin S. Spink * 3 2015 29
’ Eating Disorder Recovery Experiences Jessyca N. Arthur-Cameselle * Paula A. Quatromoni * 12 2014 28 28 4 4 334 334 346 346 10.1123/tsp.2013-0079 The Impact of Athlete Leaders on Team Members’ Team Outcome Confidence: A Test of Mediation by Team Identification and Collective Efficacy Katrien Fransen
Knud Ryom, Mads Ravn, Rune Düring and Kristoffer Henriksen
Both talent identification (TI) and talent development (TD) play a vital role in the pursuit of excellence in football ( Reilly, Williams, Nevill, & Franks, 2000 ). Football represents one of the most competitive and complex sports when it comes to attaining expertise ( Aguiar, Botelho, Lago, Maças