& Stambulova, 2007 ). Given the high level of athletic investment and the threat to valued goals and opportunities, team-selection processes are a central source of stress for many athletes ( Hanton, Fletcher, & Coughlan, 2005 ; Woodman & Hardy, 2001 ). Although the processes involved in team selection can
Carolyn E. McEwen, Laura Hurd Clarke, Erica V. Bennett, Kimberley A. Dawson and Peter R.E. Crocker
Jorge Arede, António Paulo Ferreira, Oliver Gonzalo-Skok and Nuno Leite
parameters among national team level players and whether biological maturation can predict national team selection. In this regard, coaches should be aware of interindividual, between-players differences related to their maturity and consider the impact that maturational status has on physical and technical
Georgia M. Black, Tim J. Gabbett, Rich D. Johnston, Michael H. Cole, Geraldine Naughton and Brian Dawson
from low-standard players within multiple team sports. 1 , 2 Despite the importance of one’s physical qualities to their playing standard, physical fitness tests also have the ability to predict team selection. 2 , 3 Compared with nonselected players, selected junior rugby league players were faster
Peter Le Rossignol, Tim J. Gabbett, Dan Comerford and Warren R. Stanton
To investigate the relationship between selected physical capacities and repeated-sprint performance of Australian Football League (AFL) players and to determine which physical capacities contributed to being selected for the first competition game.
Sum of skinfolds, 40-m sprint (with 10-, 20-, 30-, and 40-m splits), repeated-sprint ability (6 × 30-m sprints), and 3-km-run time were measured during the preseason in 20 AFL players. The physical qualities of players selected to play the first match of the season and those not selected were compared. Pearson correlation coefficients were used to determine the relationship among variables, and a regression analysis identified variables significantly related to repeated-sprint performance.
In the regression analysis, maximum velocity was the best predictor of repeated-sprint time, with 3-km-run time also contributing significantly to the predictive model. Sum of skinfolds was significantly correlated with 10-m (r = .61, P < .01) and 30-m (r = .53, P < .05) sprint times. A 2.6% ± 2.1% difference in repeated-sprint time (P < .05, ES = 0.88 ± 0.72) was observed between those selected (25.26 ± 0.55 s) and not selected (25.82 ± 0.80 s) for the first game of the season.
The findings indicate that maximum-velocity training using intervals of 30–40 m may contribute more to improving repeated-sprint performance in AFL players than short 10- to 20-m intervals from standing starts. Further research is warranted to establish the relative importance of endurance training for improving repeated-sprint performance in AFL football.
Kacey C. Neely, John G.H. Dunn, Tara-Leigh F. McHugh and Nicholas L. Holt
The overall purpose of this study was to examine coaches’ views on deselecting athletes from competitive female adolescent sport teams. Individual semistructured interviews were conducted with 22 head coaches of Canadian provincial level soccer, basketball, volleyball, and ice hockey teams. Interpretive description methodology (Thorne, 2008) was used. Results revealed deselection was a process that involved four phases: pre-tryout meeting, evaluation and decision-making, communication of deselection, and post deselection reflections. Within the evaluation and decision-making phase coaches made programmed and nonprogrammed decisions under conditions of certainty and uncertainty. When faced with uncertainty coaches relied on intuition.
Brendan H. Lazarus, William G. Hopkins, Andrew M. Stewart and Robert J. Aughey
only advance with age. 6 While the effect of age on performance has implications for player-list management and team selection, the effect of age on match outcome in elite Australian football is unknown. Research on the effects of anthropometry in Australian football has mainly focused on describing
Craig A. Williams
Youth sport participation offers many benefits including the development of self-esteem, peer socialization, and general fitness. However, an emphasis on competitive success—often driven by goals of elite-level travel team selection, collegiate scholarships, Olympic and National team membership, and even professional contracts—has seemingly become widespread. This has resulted in increased pressure to begin high intensity training at young ages. Such an excessive focus on early intensive training and competition at young ages rather than skill development can lead to overuse injury and burnout.
Daniel Gould, Christy Greenleaf, Diane Guinan and Yongchul Chung
As part of a larger project to examine variables perceived to influence performance in Olympic competition, this manuscript was designed to (a) report coaches’ perceptions of variables influencing Olympic athlete performance, (b) triangulate findings from surveys and interviews with Olympic athletes, and (c) examine coaches’ perceptions of variables influencing Olympic coaching effectiveness. Surveys were completed by 46 U.S. Atlanta Olympic coaches (46% of all U.S. coaches) and 19 U.S. Nagano coaches (45% of all U.S. coaches). A large number of variables were perceived by coaches to have influenced athlete performances and included having plans for dealing with distractions, strong team chemistry and cohesion, loud and enthusiastic crowd support, high levels of athlete confidence, and fair and effective team selection. Variables perceived to have influenced coaching effectiveness included markedly changed coaching behaviors, the inability to establish trust with athletes, the inability to effectively handle crisis situations, staying cool under pressure, and making fair but decisive decisions.
Andrew M. Murray and Matthew C. Varley
To investigate the influence of score line, level of opposition, and timing of substitutes on the activity profile of rugby sevens players and describe peak periods of activity.
Velocity and distance data were measured via 10-Hz GPS from 17 international-level male rugby sevens players on 2–20 occasions over 4 tournaments (24 matches). Movement data were reported as total distance (TD), high-speed-running distance (HSR, 4.17−10.0 m/s), and the occurrence of maximal accelerations (Accel, ≥2.78 m/s2). A rolling 1-min sample period was used.
Regardless of score line or opponent ranking there was a moderate to large reduction in average and peak TD and HSR between match halves. A close halftime score line was associated with a greater HSR distance in the 1st minute of the 1st and 2nd halves compared with when winning. When playing against higher-compared with lower-ranked opposition, players covered moderately greater TD in the 1st minute of the 1st half (difference = 26%; 90% confidence limits = 6, 49). Compared with players who played a full match, substitutes who came on late in the 2nd half had a higher average HSR and Accel by a small magnitude (31%; 5, 65 vs 34%; 6, 69) and a higher average TD by a moderate magnitude (16%; 5, 28).
Match score line, opposition, and substitute timing can influence the activity profile of rugby sevens players. Players are likely to perform more running against higher opponents and when the score line is close. This information may influence team selection.
Tyler L. Goodale, Tim J. Gabbett, Trent Stellingwerff, Ming-Chang Tsai and Jeremy M. Sheppard
To investigate the physical qualities that differentiate playing minutes in international-level women’s rugby sevens players.
Twenty-four national-level female rugby sevens players underwent measurements of anthropometry, acceleration, speed, lower- and upper-body strength, lower-body power, and aerobic fitness. Playing minutes in international competition were used to differentiate players into 2 groups, a high- or low-playing-minutes group. Playing minutes were related to team selection, which was determined by the coaching staff. Playing minutes were therefore used to differentiate performance levels.
Players in the high-playing-minutes group (≥70 min) were older (mean ± SD 24.3 ± 3.1 vs 21.2 ± 4.3 y, P = .05, effect size [ES] = 0.77 ± 0.66, 90% confidence limit) and had greater experience in a national-training-center environment (2.4 ± 0.8 vs 1.7 ± 0.9 y, P = .03, ES = 0.83 ± 0.65), faster 1600-m time (374.5 ± 20.4 vs 393.5 ± 29.8 s, P = .09, ES = –0.70 ± 0.68), and greater 1-repetition-maximum upper-body strength (bench press 68.4 ± 6.3 vs 62.2 ± 8.1 kg, P = .07, ES = 0.80 ± 0.70, and neutral-grip pull-up 84.0 ± 8.2 vs 79.1 ± 5.4 kg, P = .12, ES = 0.68 ± 0.72) than athletes who played fewer minutes. Age (rs = .59 ± ~.28), training experience (rs = .57 ± ~.29), bench press (r = .44 ± ~.36), and 1600-m time (r = –.43 ± ~.34) were significantly associated with playing minutes. Neutral-grip pull-up and bench press contributed significantly to a discriminant analysis. The average squared canonical correlation was .46. The discriminant analysis predicted 7 of 9 and 6 of 10 high- and low-playing-minutes athletes, respectively.
Age, training experience, upper-body strength, and aerobic fitness differentiated athlete playing minutes in international women’s rugby sevens.