Objective: The purpose of this study was to establish the inter-day reliability of several performance variables measured during a 2 × 6 s sprint on a Wattbike cycle ergometer in male rugby players. Reliablilty was assessed against an ‘analytical goal’ of detecting meaningful changes that might be expected with fatigue in rugby. Design & Methods: Sixteen male rugby players performed three trials of the protocol on different days seperated by a mimimum of 48 h. The protocol comprised 2 × 6 s ‘all out’ cycle sprints with 90 s recovery between efforts. Typical error (TE), coefficient of variation (CV), smallest worthwhile change (SWC) and moderate change (MC) were calculated between each trial for seven variables. Results: Peak Power output significantly increased from the first to the third trial (3.3-4.4 %), whilst all variables had better reliability from trials 2-3 than 1-2. Mean power (3.7%), peak power (4.2%) and total distance (2.7%) had a CV% lower than dec rements observed with team sport fatigue (~5%), however only total work had a TE (2.1 kJ) lower than the smallest worthwhile change (4.6 kJ) while the remainder were lower than the moderate worthwhile change. Conclusion: Assuming one complete habituation trial is completed, total work appears to be the most reliable variable capable of detecting a worthwhile change in performance. We recommend using this variable to monitor fatigue in rugby players.

Objectives: The aim of this study was to determine if there were differences in physical fitness performance across different cohorts of successful candidates attending law enforcement agency (LEA) training. Design and Methods: Retrospective, non-identifiable, data from three training cohorts, comprising 226 LEA candidates (♂ = 196: ♀ = 30) were analyzed. Data from a standard testing battery used to screen new candidates on entry were used to inform physi cal fitness performance. This battery included: maximal number of push-up and sit-up repetitions in 60 seconds (s); a 75-yard pursuit run (75PR) around a pre-determined course designed to mimic a foot pursuit; an arm ergometer test where candidates completed as many revolutions in 60 s; and the 2.4 kilometer (km) run. A one-way analysis of variance with Bonferroni post hoc adjustments compared age and test results across the classes. Alpha levels were set at p < 0.05 a priori. Results: There were no significant (p = 0.091-0.458) differences between the three cohorts for age, maximal number of push-ups and sit-ups completed in 60 s, time to complete the 75PR, number of revolutions completed in the 60 s arm ergometer test, or time to complete the 2.4 km run. Conclusions: The level of physical fitness for new candidates attending LEA training, as measured by the testing battery, was similar across cohorts attending training and as such physical training programs to prepare new candidates for LEA duties may not need to be different. However, trainers should be aware of individual variations in physical characteristics within classes to optimize individual gains.

Objectives: The purpose of this study was to examine the validity of a wireless device measuring velocity via inertial sensor medi cine ball. Design and Methods: Sixteen healthy adults volunteered in the study. Each participant performed a series of three static and countermovement (CM) medicine ball chest throws. All throws were performed using 8-lb and 12-lb medicine balls inlayed with a wirelessly transmitted accelerometer and gyroscope. Reflective markers were placed on both sides of medicine ball and data were collected using a three-dimensional (3D) motion analysis system as the criterion measure. Pearson correlations and paired samples t-tests were calculated to assess the accuracy of the medicine ball peak velocity to that of the 3D motion analysis. Additionally, intraclass correlation coefficients (ICC) were calculated within each device to determine reliability. The alpha level was set as p ≤ 0.05.  Results: Pearson correlations indicated the medicine ball device to be relatively accurate with 3D motion analysis for static throws (r = 0.85-0.94) and CM throws (r = 0.62-0.89). There were no statistically significant differences between the two devices. ICC  indicated trial-to-trial reliability of the medicine ball device to be acceptable (ICC = 0.74-0.98) compared to the 3D motion analysis (ICC = 0.67-0.98).  Conclusion: Overall, the study demonstrated that relatively accurate data may be obtained from an inertial sensor medicine ball, indicated from the strong and very strong correlations with 3D motion analysis. Additionally, similar ICC values between the medicine ball and 3D motion analysis suggest the device yields acceptable reliability.

Objectives: A growing area of discourse within sports medicine and resistance training is that of periodization. This has been represented as variation in load and subsequently repetitions as well as volume, with a view to maximize strength and hypertrophy adaptations. A number of recent review articles have attempted to draw overarching conclusions from the present body of literature in an effort to provide definitive guidelines. However, there are numerous variables within resistance training that are often overlooked, and in the context of periodization, might significantly impact adaptation. Design & Methods: Narrative Review Results: The present piece confers need for clarity in terminology of effort rather than intensity, as well as discussing how variety of load might impact volume-load, discomfort, muscle damage and recovery. Furthermore, this article discusses often over looked variables such as variety in exercise selection, detraining periods, and supervision, which are all evidenced to impact strength and hypertrophy adaptations. Conclusions: Our opinion is that without inclusion of these variables any guidelines surrounding periodization for strength or hypertrophy are limited in application. We conclude by highlighting areas for future research, as well as practical recommendations within this field.