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The aims of this investigation were to describe the physical output of hockey relative to possession status, and to identify differences in physical output during each possession category with respect of match result. Ten international matches were analysed utilizing Sportscode to identify in and not in possession instances. 24 players (age 26 ± 4) wore a 10 Hz GPS device to track physical output. Linear Mixed Models and post hoc pairwise comparisons were utilised to compare the physical output in each possession category within each position and relative to match result. Significant main effects were found for possession status on several physical output metrics (p ≤ 0.05). For all positions except forwards, not in possession instances were more physically demanding than in possession instances for metrics such as relative total distance, explosive distance, and high-speed running (>5.5 m.s−1). No significant difference was identified between possession category physical output aligned with match result (p > 0.05). This study shows for the first time that not in possession instances were more physically demanding than in possession instances for defenders, outside backs and midfielders. For not in possession instances, relative total distance and high-speed running was, on average, 13% and 41% higher compared to in possession instances. Furthermore, there was no statistical difference in physical output for any position during each possession category relative to the match result. [ABSTRACT FROM AUTHOR]

Background: The ankle joint requires very precise neuromuscular control during the transition from terminal swing to the early stance phase of the gait cycle. Altered ankle joint arthrokinematics and muscular [...]

Poor reporting of medical and healthcare systematic reviews is a problem from which the sports and exercise medicine, musculoskeletal rehabilitation, and sports science fields are not immune. Transparent, accurate and comprehensive systematic review reporting helps researchers replicate methods, readers understand what was done and why, and clinicians and policy-makers implement results in practice. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement and its accompanying Explanation and Elaboration document provide general reporting examples for systematic reviews of healthcare interventions. However, implementation guidance for sport and exercise medicine, musculoskeletal rehabilitation, and sports science does not exist. The Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science (PERSiST) guidance attempts to address this problem. Nineteen content experts collaborated with three methods experts to identify examples of exemplary reporting in systematic reviews in sport and exercise medicine (including physical activity), musculoskeletal rehabilitation (including physiotherapy), and sports science, for each of the PRISMA 2020 Statement items. PERSiST aims to help: (1) systematic reviewers improve the transparency and reporting of systematic reviews and (2) journal editors and peer reviewers make informed decisions about systematic review reporting quality. [ABSTRACT FROM AUTHOR]

Hamstring strains are the most prevalent injury sustained by field-sport athletes. Insufficiencies in the architectural characteristics of the hamstring muscles can heighten an athlete's risk of incurring a hamstring strain. To evaluate the influence of hamstring muscle architectural characteristics (i. e., fascicle length, pennation angle, muscle thickness) on injury risk, it is necessary to precisely evaluate these characteristics. Considering this, our aim was to develop and evaluate the precision of a novel semi-automated tracing software to measure the architectural characteristics of the biceps femoris long head (the most commonly injured hamstring muscle) in B-mode ultrasound images. We acquired static sonograms of the biceps femoris long head from ten healthy male field-sport athletes. The architectural characteristics (fascicle length, pennation angle, and muscle thickness) of participants' biceps femoris long head were evaluated 10 times using the tracing software, with the specific purpose of determining its measurement precision. The tracing software precisely measured the architectural characteristics of the participants' biceps femoris long head: fascicle length (% CV: 0.64–1.12), pennation angle (% CV: 2.58–10.70), muscle thickness (% CV: 0.48–2.04) Our semi-automated skeletal muscle tracing algorithm precisely measures fascicle length, pennation angles, and muscle thickness of the biceps femoris long head in static B-mode ultrasound images. [ABSTRACT FROM AUTHOR]