experience of team sport participation. Although individuals are living longer than ever due to improvements in health care, negative stereotypes of older adults still persist. In Western nations, negative stereotypes of older adults include the assumption that they have health issues and cognitive
Jen D. Wong, Julie S. Son, Stephanie T. West, Jill J. Naar and Toni Liechty
Benjamin M. Jackson, Ted Polglaze, Brian Dawson, Trish King and Peter Peeling
. 6 While GPS devices have demonstrated a reasonable level of accuracy for measuring total distance covered during team sport competition, 7 , 8 some limitations remain. 9 Typically, distance measures become less reliable as running speed increases, and accuracy is reduced when movement occurs over
Hugh H.K. Fullagar, Rob Duffield, Sabrina Skorski, Aaron J. Coutts, Ross Julian and Tim Meyer
While the effects of sleep loss on performance have previously been reviewed, the effects of disturbed sleep on recovery after exercise are less reported. Specifically, the interaction between sleep and physiological and psychological recovery in team-sport athletes is not well understood. Accordingly, the aim of the current review was to examine the current evidence on the potential role sleep may play in postexercise recovery, with a tailored focus on professional team-sport athletes. Recent studies show that team-sport athletes are at high risk of poor sleep during and after competition. Although limited published data are available, these athletes also appear particularly susceptible to reductions in both sleep quality and sleep duration after night competition and periods of heavy training. However, studies examining the relationship between sleep and recovery in such situations are lacking. Indeed, further observational sleep studies in team-sport athletes are required to confirm these concerns. Naps, sleep extension, and sleep-hygiene practices appear advantageous to performance; however, future proof-of-concept studies are now required to determine the efficacy of these interventions on postexercise recovery. Moreover, more research is required to understand how sleep interacts with numerous recovery responses in team-sport environments. This is pertinent given the regularity with which these teams encounter challenging scenarios during the course of a season. Therefore, this review examines the factors that compromise sleep during a season and after competition and discusses strategies that may help improve sleep in team-sport athletes.
Mark Evans, Peter Tierney, Nicola Gray, Greg Hawe, Maria Macken and Brendan Egan
indicated by a decline in maximal sprint speed with subsequent sprints, that is, an increase in sprint duration over a set distance. Clearly, any ergogenic aid that can attenuate fatigue and maintain RSP in team sport athletes may prove beneficial and warrant use during competition. A wide body of
Lucas A. Pereira, Rodrigo Ramirez-Campillo, Saul Martín-Rodríguez, Ronaldo Kobal, César C.C. Abad, Ademir F.S. Arruda, Aristide Guerriero and Irineu Loturco
, superset, and triset resistance training sessions in university rugby union players. Thus, a more complete understanding of the actual acute responses to different exercise types is clearly warranted in team-sport disciplines. One of the most common and practical ways to quantify the symptoms of fatigue
Heidi R. Thornton, Jace A. Delaney, Grant M. Duthie, Brendan R. Scott, William J. Chivers, Colin E. Sanctuary and Ben J. Dascombe
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.
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.
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.
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.
John T. Cacioppo and Charlotte A. Lowell
Eight situations dealing with team sports were described to 63 male and 63 female undergraduates. Each situation depicted a team competition involving same-sex members, and subjects were told specifically about the affiliation, acquaintance, and skill of one of the participants. Subjects indicated how enjoyable they viewed each of the eight sports situations, how many years they had participated in team sports, and how much experience they had in team sport competition. The results suggested that men and women similarly enjoyed aspects of team sport participation that improved their chances of winning and interacting cooperatively with friends, but men seemed to enjoy the ego-challenging aspects of team sports more than women.
Samuel Robertson, Jonathan D. Bartlett and Paul B. Gastin
Decision-support systems are used in team sport for a variety of purposes including evaluating individual performance and informing athlete selection. A particularly common form of decision support is the traffic-light system, where color coding is used to indicate a given status of an athlete with respect to performance or training availability. However, despite relatively widespread use, there remains a lack of standardization with respect to how traffic-light systems are operationalized. This paper addresses a range of pertinent issues for practitioners relating to the practice of traffic-light monitoring in team sports. Specifically, the types and formats of data incorporated in such systems are discussed, along with the various analysis approaches available. Considerations relating to the visualization and communication of results to key stakeholders in the team-sport environment are also presented. In order for the efficacy of traffic-light systems to be improved, future iterations should look to incorporate the recommendations made here.
Bruno Marrier, Julien Robineau, Julien Piscione, Mathieu Lacome, Alexis Peeters, Christophe Hausswirth, Jean-Benoît Morin and Yann Le Meur
Peaking for major competition is considered critical for maximizing team-sport performance. However, there is little scientific information available to guide coaches in prescribing efficient tapering strategies for team-sport players.
To monitor the changes in physical performance in elite team-sport players during a 3-wk taper after a preseason training camp.
Ten male international rugby sevens players were tested before (Pre) and after (Post) a 4-wk preseason training camp focusing on high-intensity training and strength training with moderate loads and once each week during a subsequent 3-wk taper. During each testing session, midthigh-pull maximal strength, sprint-acceleration mechanical outputs, and performance, as well as repeated-sprint ability (RSA), were assessed.
At Post, no single peak performance was observed for maximal lower-limb force output and sprint performance, while RSA peaked for only 1 athlete. During the taper, 30-m-sprint time decreased almost certainly (–3.1% ± 0.9%, large), while maximal lower-limb strength and RSA, respectively, improved very likely (+7.7% ± 5.3%, small) and almost certainly (+9.0% ± 2.6%, moderate). Of the peak performances, 70%, 80%, and 80% occurred within the first 2 wk of taper for RSA, maximal force output, and sprint performance, respectively.
These results show the sensitivity of physical qualities to tapering in rugby sevens players and suggest that an ~1- to 2-wk tapering time frame appears optimal to maximize the overall physical-performance response.
Niels J. Nedergaard, Mark A. Robinson, Elena Eusterwiemann, Barry Drust, Paulo J. Lisboa and Jos Vanrenterghem
To investigate the relationship between whole-body accelerations and body-worn accelerometry during team-sport movements.
Twenty male team-sport players performed forward running and anticipated 45° and 90° side-cuts at approach speeds of 2, 3, 4, and 5 m/s. Whole-body center-of-mass (CoM) accelerations were determined from ground-reaction forces collected from 1 foot–ground contact, and segmental accelerations were measured from a commercial GPS accelerometer unit on the upper trunk. Three higher-specification accelerometers were also positioned on the GPS unit, the dorsal aspect of the pelvis, and the shaft of the tibia. Associations between mechanical load variables (peak acceleration, loading rate, and impulse) calculated from both CoM accelerations and segmental accelerations were explored using regression analysis. In addition, 1-dimensional statistical parametric mapping (SPM) was used to explore the relationships between peak segmental accelerations and CoM-acceleration profiles during the whole foot–ground contact.
A weak relationship was observed for the investigated mechanical load variables regardless of accelerometer location and task (R 2 values across accelerometer locations and tasks: peak acceleration .08–.55, loading rate .27–.59, and impulse .02–.59). Segmental accelerations generally overestimated whole-body mechanical load. SPM analysis showed that peak segmental accelerations were mostly related to CoM accelerations during the first 40–50% of contact phase.
While body-worn accelerometry correlates to whole-body loading in team-sport movements and can reveal useful estimates concerning loading, these correlations are not strong. Body-worn accelerometry should therefore be used with caution to monitor whole-body mechanical loading in the field.