min 34.57 s for the 1500-m event. However, 26 out of the 32 (81%) Olympic swimming events are competed over a race distance of 200 m or less, for a typical duration of less than 2 min 20 s. Despite the short duration of the majority of swimming events, the traditional training practices of competitive
Frank Nugent, Thomas Comyns, Alan Nevill and Giles D. Warrington
Tai T. Tran, Lina Lundgren, Josh Secomb, Oliver R.L. Farley, G. Gregory Haff, Laurent B. Seitz, Robert U. Newton, Sophia Nimphius and Jeremy M. Sheppard
To determine whether a previously validated performance-testing protocol for competitive surfers is able to differentiate between Australian elite junior surfers selected (S) to the national team and those not selected (NS).
Thirty-two elite male competitive junior surfers were divided into 2 groups (S = 16, NS = 16). Their age, height, body mass, sum of 7 skinfolds, and lean-body-mass ratio (mean ± SD) were 16.17 ± 1.26 y, 173.40 ± 5.30 cm, 62.35 ± 7.40 kg, 41.74 ± 10.82 mm, 1.54 ± 0.35 for the S athletes and 16.13 ± 1.02 y, 170.56 ± 6.6 cm, 61.46 ± 10.10 kg, 49.25 ± 13.04 mm, 1.31 ± 0.30 for the NS athletes. Power (countermovement jump [CMJ]), strength (isometric midthigh pull), 15-m sprint paddling, and 400-m endurance paddling were measured.
There were significant (P ≤ .05) differences between the S and NS athletes for relative vertical-jump peak force (P = .01, d = 0.9); CMJ height (P = .01, d = 0.9); time to 5-, 10-, and 15-m sprint paddle; sprint paddle peak velocity (P = .03, d = 0.8; PV); time to 400 m (P = .04, d = 0.7); and endurance paddling velocity (P = .05, d = 0.7).
All performance variables, particularly CMJ height; time to 5-, 10-, and 15-m sprint paddle; sprint paddle PV; time to 400 m; and endurance paddling velocity, can effectively discriminate between S and NS competitive surfers, and this may be important for athlete profiling and training-program design.
Emmanuel Ducrocq, Mark Wilson, Tim J. Smith and Nazanin Derakshan
al., 2016 for a recent meta-analysis). In line with the predictions of ACT ( Eysenck et al., 2007 ), the QE is also sensitive to the impact of competitive pressure in both self-paced (e.g., golf putting: Vine et al., 2013 ; basketball free-throw shooting: Wilson, Vine, & Wood, 2009 ) and interceptive (e
Alexandra F. DeJong and Jay Hertel
Sensors have been used to detect sport-specific movements 14 , 15 and spatiotemporal changes during a competitive marathon. 16 Thus, significantly more data can be collected in natural environments to determine biomechanical changes during athletic demands. 7 , 14 One such commercially-available sensor
Karine Corrion, Thierry Long, Alan L. Smith and Fabienne d’Arripe-Longueville
This study was designed to assess athletes’ use of moral disengagement in competitive sport. We conducted semistructured interviews with 24 elite male and female athletes in basketball and taekwondo. Participants described transgressive behaviors in competitive situations and reasons for adopting such behaviors. Content analyses revealed that the eight moral disengagement mechanisms identified in everyday Life (i.e., moral justification, advantageous comparison, euphemistic labeling, minimizing or ignoring consequences, attribution of blame, dehumanization, displacement of responsibility, and diffusion of responsibility; Bandura, Barbaranelli, Caprara, & Pastorelli, 1996) were germane in sport. However, the most frequently adopted mechanisms in sport (i.e., displacement and diffusion of responsibility, attribution of blame, minimizing or ignoring consequences, and euphemistic labeling) differed somewhat from those considered most salient in everyday life (i.e., moral justification, advantageous comparison, and euphemistic labeling). Moral disengagement mechanisms linked to projecting fault onto others (“It’s not my fault”) and minimization of transgressions and their consequences (“It’s not serious”) appear to be especially prominent in sport. The findings extend the sport moral disengagement literature by showcasing athlete accounts of moral disengagement.
Dajo Sanders, Grant Abt, Matthijs K.C. Hesselink, Tony Myers and Ibrahim Akubat
To assess the dose-response relationships between different training-load methods and aerobic fitness and performance in competitive road cyclists.
Training data from 15 well-trained competitive cyclists were collected during a 10-wk (December–March) preseason training period. Before and after the training period, participants underwent a laboratory incremental exercise test with gas-exchange and lactate measures and a performance assessment using an 8-min time trial (8MT). Internal training load was calculated using Banister TRIMP, Edwards TRIMP, individualized TRIMP (iTRIMP), Lucia TRIMP (luTRIMP), and session rating of perceived exertion (sRPE). External load was measured using Training Stress Score (TSS).
Large to very large relationships (r = .54–.81) between training load and changes in submaximal fitness variables (power at 2 and 4 mmol/L) were observed for all training-load calculation methods. The strongest relationships with changes in aerobic fitness variables were observed for iTRIMP (r = .81 [95% CI .51–.93, r = .77 [95% CI .43–.92]) and TSS (r = .75 [95% CI .31–.93], r = .79 [95% CI .40–.94]). The strongest dose-response relationships with changes in the 8MT test were observed for iTRIMP (r = .63 [95% CI .17–.86]) and luTRIMP (r = .70 [95% CI .29–.89).
Training-load quantification methods that integrate individual physiological characteristics have the strongest dose-response relationships, suggesting this to be an essential factor in the quantification of training load in cycling.
David Simbaña Escobar, Philippe Hellard, David B. Pyne and Ludovic Seifert
, turns, and finish. The effect of turns and starts on stroking parameters has also been observed during competitive swimming events. 11 – 13 In particular, Veiga and Roig 12 compared the free swimming and underwater speed after the start and turns for the 200 m at the FINA 2013 World Swimming
Philippe Hellard, Robin Pla, Ferran A. Rodríguez, David Simbana and David B. Pyne
The evaluation of metabolic capacities and their relative contributions to performance in different events informs the training programs for competitive pool swimming, from short (50 m) to long (1500 m) distances. 1 , 2 This evaluation is needed for coaches and sports scientists to more
Jules Woolf, Jess C. Dixon, B. Christine Green and Patrick J. Hill
whether it was just a clash of personalities. While Scott was known for his Type-A personality, Toften could also be stubborn and the competitive environment of college athletics can sometimes lead to this type of blow up. At the same time, Jacobs could not ignore the other resignations and wondered
Ian W. Maynard, Martin J. Smith and Lawrence Warwick-Evans
The aims of this field-based study were to evaluate the effects of a cognitive intervention technique and to further examine the anxiety–performance relationship in semiprofessional soccer players. Participants completed a composite version of the Competitive State Anxiety Inventory-2 (CSAI-2) 20 minutes before three soccer league matches. Two experimental groups, one suffering from debilitative cognitive anxiety (n = 8), one suffering from debilitative somatic anxiety (n = 8), undertook a 12-week cognitive intervention. Player performances were evaluated using intraindividual criteria. A series of two-way analyses of variance (group and event), with repeated measures on the second factor, indicated significant Group × Event interactions for cognitive anxiety intensity and direction, and somatic anxiety intensity and direction, yet failed to reveal significant interactions or main effects for the performance measures. This study provided partial support for the “matching hypothesis” in that a compatible treatment proved more effective in reducing the targeted anxiety in both experimental groups.