, rugby union is considered to be responsible for one of the highest injury rates in sports. 2 In professional players, the overall injury incidence for matches is reported as 81 per 1000 player hours, 2 whereas for elite junior academy and schoolboy players, match injury incidences are 47 and 35 per
Shane Ball, Mark Halaki, Tristan Sharp, and Rhonda Orr
Heidi R. Thornton, Jace A. Delaney, Grant M. Duthie, and Ben J. Dascombe
To investigate the ability of various internal and external training-load (TL) monitoring measures to predict injury incidence among positional groups in professional rugby league athletes.
TL and injury data were collected across 3 seasons (2013–2015) from 25 players competing in National Rugby League competition. Daily TL data were included in the analysis, including session rating of perceived exertion (sRPE-TL), total distance (TD), high-speed-running distance (>5 m/s), and high-metabolic-power distance (HPD; >20 W/kg). Rolling sums were calculated, nontraining days were removed, and athletes’ corresponding injury status was marked as “available” or “unavailable.” Linear (generalized estimating equations) and nonlinear (random forest; RF) statistical methods were adopted.
Injury risk factors varied according to positional group. For adjustables, the TL variables associated most highly with injury were 7-d TD and 7-d HPD, whereas for hit-up forwards they were sRPE-TL ratio and 14-d TD. For outside backs, 21- and 28-d sRPE-TL were identified, and for wide-running forwards, sRPE-TL ratio. The individual RF models showed that the importance of the TL variables in injury incidence varied between athletes.
Differences in risk factors were recognized between positional groups and individual athletes, likely due to varied physiological capacities and physical demands. Furthermore, these results suggest that robust machine-learning techniques can appropriately monitor injury risk in professional team-sport athletes.
Chelsey Klimek, Christopher Ashbeck, Alexander J. Brook, and Chris Durall
databases Inclusion and Exclusion Criteria Inclusion • Studies that compared injury rates in CrossFit training to other types of exercise • Limited to the English language • Limited to humans • Limited to the last 10 years (2006–2015) Exclusion • Studies that did not provide data on injury incidence Results
Nicole J. Chimera, Monica R. Lininger, and Meghan Warren
researchers to collect data on injury incidence, without the use of EMR. If text messaging is a valid injury reporting mechanism, this technology can be used to get a better estimate of injury occurrence in recreational activities. Focused Clinical Question Can text message be used for epidemiologic data
Nicola Relph and Katie Small
Multi-day running events are increasingly popular, however, research on these events is lacking and fails to consider the dynamic nature of musculoskeletal physiology. Twenty-three athletes completing a 10-day marathon event participated in the study. Proprioception, dynamic balance, knee valgus, and flexibility were assessed the day before the event and after one, five, and nine consecutive marathons. There were significant reductions in these measurements across the event and reductions were more apparent in the nondominant side. Each runner suffered, on average, 4.2 injuries. Runners performed significantly worse in musculoskeletal measurements, particularly on the nondominant side, as the competition progressed. Therefore, athletic trainers should design appropriate between-day recovery strategies during events based on within-event data collection.
Alan A. Zakaria, Robert B. Kiningham, and Ananda Sen
To determine if there is any benefit to static stretching after performing a dynamic warm-up in the prevention of injury in high school soccer athletes.
Prospective cluster randomized nonblinded study.
12 high schools with varsity and junior varsity boys’ soccer teams (24 soccer teams) across the state of Michigan.
Four hundred ninety-nine student-athletes were enrolled, and 465 completed the study. One high school dropped out of the study in the first week, leaving a total of 22 teams.
Dynamic stretching protocol vs dynamic + static (D+S) stretching protocol.
Main Outcome Measures:
Lower-extremity, core, or lower-back injuries per team.
Twelve teams performed the dynamic stretching protocol and 10 teams performed the D+S stretching protocol. There were 17 injuries (1.42 ± 1.49 injuries/team) among the teams that performed the dynamic stretching protocol and 20 injuries (2.0 ± 1.24 injuries/team) among the teams that performed the D+S protocol. There was no statistically significant difference in injuries between the 2 groups (P = .33).
There is no difference between dynamic stretching and D+S stretching in the prevention of lower-extremity, core, and back injuries in high school male soccer athletes. Static stretching does not provide any added benefit to dynamic stretching in the prevention of injury in this population before exercise.
Javier Raya-González, Luis Suárez-Arrones, Archit Navandar, Carlos Balsalobre-Fernández, and Eduardo Sáez de Villarreal
heterogenic, making comparisons difficult. Therefore, studies about the specific injury profiles in young players are necessary to understand the etiology of injuries and to develop useful preventive strategies. 16 A recent systematic review has shown that the injury incidence during training is higher in
Guillermo Mendez-Rebolledo, Romina Figueroa-Ureta, Fernanda Moya-Mura, Eduardo Guzmán-Muñoz, Rodrigo Ramirez-Campillo, and Rhodri S. Lloyd
this context, the main objective of this study was (1) to determine the effects of NM training on reducing lower limb injury incidence and (2) to establish its effects on CMJ performance, balance, 30-m sprint, and joint position sense in youth female track-and-field athletes. We hypothesized that NM
Pedro Gómez-Carmona, Ismael Fernández-Cuevas, Manuel Sillero-Quintana, Javier Arnaiz-Lastras, and Archit Navandar
Injuries are an inherent part of high-level sports performance, with soccer having one of the highest injury incidences. 1 Specifically, epidemiological studies in soccer have observed a prevalence of injuries about 15% per season, affecting 65% to 95% of all players. 1 , 2 Injury rate in soccer
Pablo A. Domene, Michelle Stanley, and Glykeria Skamagki
sustaining an injury, and (3) calculate the injury incidence rate in nonprofessional salsa dance using an anonymous web-based 1-year retrospective injury history survey. It was hypothesized that being female 16 and having a higher age, 16 higher volume of salsa dance engagement per week, 16 higher volume