The epidemiology of injuries in Australian professional Rugby Union 2014 Super Rugby competition

BACKGROUND: Rugby union is a collision-based ball sport played at the professional level internationally. Rugby union has one of the highest reported incidences of injury of all team sports. PURPOSE: To identify the characteristics, incidence, and severity of injuries occurring in Australian professional Super Rugby Union. DESIGN: Descriptive epidemiology study. METHODS: The present study was a prospective epidemiology study on a cohort of 180 professional players from 5 Australian Super Rugby teams during the 2014 Super Rugby Union Tournament. Team medical staff collected and submitted daily training and match-play injury data through a secure, web-based electronic platform. The injury data included the main anatomic location of the injury, specific anatomic structure of the injury, injury diagnosis, training or match injury occurrence, main player position, mechanism of injury, and the severity of the injury quantified based on the number of days lost from training and/or competition due to injury. RESULTS: The total combined incidence rate for injury during training and match-play across all Australian Super Rugby Union teams was 6.96 per 1000 hours, with a mean injury severity of 37.45 days lost from training and competition. The match-play injury incidence rate was 66.07 per 1000 hours, with a mean severity of 39.80 days lost from training and competition. No significant differences were observed between forward- and back-playing positions for match or training injury incidence rate or severity. CONCLUSION: The incidence of injury for the present study was lower during match-play than has previously been reported in professional rugby union; however, the overall time loss was higher compared with previous studies in professional rugby union. The high overall time loss was due fundamentally to a high incidence of injuries with greater than 28 days’ severity

Movement demands and perceived wellness associated with preseason training camp in NCAA Division I college football players

The aims of this study were to examine the movement demands of preseason practice in National Collegiate Athletic Association Division I college football players using portable global positioning system (GPS) technology and to assess perceived wellness associated with preseason practice to determine whether GPS-derived variables from the preceding day influence perceived wellness the following day. Twenty-nine players were monitored using GPS receivers (Catapult Innovations, Melbourne, Australia) during 20 preseason practices. Individual observations (n = 550) were divided into offensive and defensive position groups. Movement variables including low-, medium-, high-intensity, and sprint distance, player load, and acceleration and deceleration distance were assessed. Perceived wellness ratings (n = 469) were examined using a questionnaire which assessed fatigue, soreness, sleep quality, sleep quantity, stress, and mood. A 1-way analysis of variance for positional movement demands and multilevel regressions for wellness measures were used, followed by post hoc testing to evaluate the relational significance between categorical outcomes of perceived wellness scores and movement variables. Results demonstrated significantly (p ≤ 0.05) greater total, high-intensity, and sprint distance, along with greater acceleration and deceleration distances for the defensive back and wide receiver position groups compared with their respective offensive and defensive counterparts. Significant (p ≤ 0.05) differences in movement variables were demonstrated for individuals who responded more or less favorably on each of the 6 factors of perceived wellness. Data from this study provide novel quantification of the position-specific physical demands and perceived wellness associated with college football preseason practice. Results support the use of position-specific training and individual monitoring of college football players

Automated Image Analysis of Offshore Infrastructure Marine Biofouling

Supplementary Materials: The following are available online at www.mdpi.com/2077-1312/6/1/2/s1 Acknowledgments: This project was funded by the Natural Environmental Research Council (NERC) project No.: NE/N019865/1. The authors would like to thank Melanie Netherway and Don Orr, from our project partner (company requested to remain anonymous) for the provision of survey footage and for supporting the project. In addition, many thanks to Oscar Beijbom, University California Berkley for providing guidance and support to the project. Additional thanks to Calum Reay, Bibby Offshore; George Gair, Subsea 7; and Alan Buchan, Wood Group Kenny for help with footage collection and for allowing us to host workshops with them and their teams, their feedback and insights were very much appreciated.Peer reviewedPublisher PD

Statistical modelling of home range and larvae movement data

In this thesis, we investigate two di erent approaches to animal movement modelling; nite mixture models, and di usion processes. These models are considered in two di erent contexts, rstly for analysis of data obtained in home range studies, and then, on a much smaller scale, modelling the movements of larvae. We consider the application of mixture models to home range movement data, and compare their performance with kernel density estimators commonly used for this purpose. Mixtures of bivariate normal distributions and bivariate t distributions are considered, and the latter are found to be good models for simulated and real movement data. The mixtures of bivariate t distributions are shown to provide a robust parametric approach. Subsequently, we investigate several measures of overlap for assessing site delity in home range data. Di usion processes for home range data are considered to model the tracks of animals. In particular, we apply models based on a bivariate Ornstein-Uhlenbeck process to recorded coyote movements. We then study modelling in a di erent application area involving tracks. Di usion models for the movements of larvae are used to investigate their behaviour when exposed to chemical compounds in a scienti c study. We nd that the tted models represent the movements of the larvae well, and correctly distinguish between the behaviour of larvae exposed to attractant and repellent compounds. Mixtures of di usion processes and Hidden Markov models provide more exible alternatives to single di usion processes, and are found to improve upon them considerably. A Hidden Markov model with 4 states is determined to be optimal, with states accounting for directed movement, localized movement and stationary observations. Models incorporating higherorder dependence are investigated, but are found to be less e ective than the use of multiple states for modelling the larvae movements

Talent identification in soccer: The influence of technical, physical and maturity-related characteristics on a national selection process

The present study examines the influence of technical, physical, and relative age characteristics on players selection success within the Scottish Performance School trials. Ninety adolescent players (81 males, 9 females; mean ± standard deviation: age = 11.3 ± 0.4 years, height = 149.6 ± 6.9 cm, mass 38.1 ± 4.7 kg) performed a battery of physical fitness (20m Sprint, CMJ, 5-0-5 agility test), anthropometric, and 8 small-sided games (SSG; 9v9) as part of a talent identification (TID) programme. Players technical (ball touches, time on the ball, high-speed releases) and locomotor activities (high-speed running distance, sprint distance, accelerations, and decelerations) were monitored using foot-mounted inertial measurements units during SSG’s. The data was analysed using independent sample T-tests. Mann-Whitney U analyses were conducted to examine the differences between groups whose data was determined as being (non)parametric, with Cohen effect sizes applied. Successful players performed significantly better during physical tests (Effect size ± confidence limits: Left 5-0-5 = -0.89±0.13, Right 5-0-5 = -0.51±0.11), had significantly higher locomotor activities during SSG (high-intensity distance = 0.4±26.6, horizontal accelerations = 0.59±1.19) and significantly higher technical outputs during SSG (touches = 0.71±6.1, releases = 0.49±2.5, high-speed releases = 0.59±2.7, time on the ball = 0.52±3.4) compared to unsuccessful players. Successful players had significantly higher locomotor activities and technical outputs during SSG than their unsuccessful counterparts. Monitoring technical and locomotor activities during SSG may compliment or replace physical testing batteries for assessing TID processes in soccer