Mike Hopkinson

The pole vault is a highly technical event where the athletes must successfully convert horizontal velocity during the run-up to vertical velocity at take-off. The aim of this study was to compare the kinematics of men's and women's world-class pole vaulting. Video data were collected of the best clearances by 14 men and 11 women at the 2018 IAAF World Indoor Championships using three high-speed cameras (200 Hz). Running velocity, step lengths, step times, and pole angles were measured during the run-up; during take-off, distance from the plant box, angle and velocity of take-off, and relative positions of the foot and hands were measured. Men achieved greater clearance heights with faster run-ups, faster take-off velocities and higher hand grip positions (all p < 0.001), with each of the last three steps longer for men when expressed as absolute values (all p < 0.001), but not when expressed relative to stature. There were no differences in run-up pole angles, step times, take-off angle, take-off contact time or time from pole plant to take-off. Women differed in their approach and take-off for characteristics affected by stature and strength, such as fewer run-up steps, shorter take-off distances, and lower grip heights. These lower grips result from a shorter, lighter pole, and this disadvantage was greater than slower run-up velocities. Coaches should therefore note that sex-based differences occur in the pole vault that result from anthropometric differences, but which do not negate the adoption of similar technical models of vaulting.

Rugby league (RL) carries a high injury incidence with 61% of injuries occurring at tackles. The ball carrier has a higher injury incidence than the defender, therefore understanding mechanisms occurring during injurious tackles are important. Given the dynamic, open nature of tackling, characteristics influencing tackle outcome likely encompass complex networks of dependencies. This study aims to identify important classifying characteristics of the tackle related to ball carrier injurious and non-injurious events in RL and identify the characteristics capability to correctly classify those events. Forty-one ball carrier injuries were identified and 205 matched non-injurious tackles were identified as controls. Each case and control were analysed retrospectively through video analysis. Random forest models were built to 1.) filter tackle characteristics possessing relative importance for classifying tackles resulting in injurious/non-injurious outcomes and 2.) determine sensitivity and specificity of tackle characteristics to classify injurious and non-injurious events. Six characteristics were identified to possess relative importance to classify injurious tackles. This included ‘tackler twisted ball carrier’s legs when legs were planted on ground’, ‘the tackler and ball carrier collide heads’, ‘the tackler used body weight to tackle ball carrier, ‘the tackler has obvious control of the ball carrier’ ‘the tackler was approaching tackle sub-maximally’ and ‘tackler's arms were below shoulder level, elbows were flexed’. The study identified tackle characteristics that can be modified in attempt to reduce injury. Additional injury data are needed to establish relationship networks of characteristics and analyse specific injuries. Sensitivity and specificity results of the random forest were 0.995 and 0.525.

The aims of this study were: (1) to quantify interlimb asymmetries in EPL soccer players in the context of kicking limb preference and (2) to establish the relationship between interlimb asymmetries and measures of physical performance. Twenty-two players (age: 21.8 ± 4.4 years) from an EPL club performed a running gait assessment (20 km/h) and unilateral countermovement jumps, a CoD assessment (modified 505 test), and an isokinetic knee extension/flexion protocol using each leg. Asymmetries were quantified using the percentage difference method and Pearson’s correlations were used to quantify the association between variables. Players displayed the greatest level of asymmetry in isokinetic strength measures (5.9-12.7%) and lower levels of asymmetry in gait (1.6-7.7%), jump (0.9-7.0%) and CoD (1.9-3.5%) assessments. The influence of the preferred kicking limb was most evident in the isokinetic assessment with the players showing dominance in the preferred limb for knee flexor strength and in the non-preferred limb for knee extensor strength. These manifested in the asymmetry values calculated for the hamstring:quadricep (H:Q) ratios at 60°/s (8.80 ± 7.82%) and 240°/s (11.22 ± 7.04%) and in the functional H:Q ratio (12.67 ± 8.25%). The asymmetry values for peak extensor moment at 240°/s showed a significant correlation (ρ = ─0.55, p = 0.034) with 10 m time in the CoD assessment. These findings provide benchmark asymmetry data for soccer practitioners and reveal that kicking limb preferences may bring about interlimb differences in the H:Q ratio which raises important considerations in the design of testing batteries and injury reduction interventions.

Objective To (1) systematically review the literature to identify which match-related risk factors and mechanisms of rugby tackle events result in musculoskeletal injury; concussion; head injury assessments; and head impacts or head accelerations; and (2) identify the perceived importance and feasibility of potential intervention strategies for tackle-related injury reduction in the rugby codes. Design A systematic search was performed using PRISMA guidelines. Risk factors/mechanisms associated with tackle injuries across the rugby codes were extracted. After extraction, 50 international rugby experts participated in a Delphi poll. Via content analysis, expert-recommended risk factors/mechanisms were developed. In round two, experts rated all risk factors and mechanisms for importance to injury risk. In round three, the feasibility of law changes, coach and player education and training as interventions to reduce injury risk for each injury risk factor/mechanism deemed important during round two were rated. Data sources PubMed [MEDLINE], Scopus, SPORTDiscus [EBSCOhost] and CINAHL. Eligibility criteria Eligible studies included cohort, observational and cross-sectional designs, that included male or female rugby union, league, or sevens players. Results Thirty-seven eligible studies were identified, with 138 injury risk factors/mechanisms extracted. 70% of the studies were rated ‘high quality’, with 30% moderate quality. Thirty-eight new risk factors/mechanisms were recommended by the expert group, eight being identified as important and highly feasible for modification by an intervention strategy. ‘The tackler placing their head on the incorrect side of the ball carrier’ was described as the most important mechanism, with ‘training’ and ‘coach/player education’ thought to be highly feasible interventions. Conclusion Numerous risk factors or mechanisms associated with tackle-related injury appear important and modifiable, helping to guide interventions to reduce injury risk in the rugby tackle.

Introduction Research within Rugby league (RL) tackle investigations using video analysis has often used two sources of variables. The exception being King et al (2010) who described the characteristics of the RL tackle event such as number of tacklers and tackle height of the first tackler. However, the majority of investigations have either adopted technical variables from rugby union (RU) tackle variables (Sperenza et al., 2017) or technical criteria from coaching cues (Gabbett, 2008). In doing so, content validity and relevance to RL could be questioned (O’Donoghue, 2014). The aim of this study was to adopt a 5 stage process to determine tackle variables which are valid and reliable for RL research. Method A 5 stage process was undertaken based upon recommendations by O’Donoghue (2014). STAGE 1 involved a synthesis of literature and examined phases of the tackle, variables describing the tackle descriptions of these variables research. A draft variable list was then developed before the start of STAGE 2. To achieve content validity and relevancy, STAGE 2 formed an expert group of practitioners to critique the previously formed draft variable list and develop new phases, variables and descriptors. STAGE 3 refined the variable list based upon the practitioner consultation. STAGE 4 established an expert group agreement in the refined variable list. Finally, STAGE 5 tested intra and inter-reliability of the list using Kappa statistics (McHugh, 2012). Results The agreed variable list comprised of 6 phases including defensive start point, pre-contact, initial contact, post-contact and play the ball phases. Within the phases 66 variables were determined. The intra- and inter-reliability testing resulted in at least moderate agreement (>0.7) (McHugh, 2012) of all phases. Discussion Due to possessing both strong relevance to an RL tackle and demonstrating good levels of reliability, researchers can be confident that the variables within the list are valid for research purposes (O’Donoghue, 2014). In addition, the rigorous 5 stage process of validating the content of the variable list should be used when determining different variables within different sports and actions for research purposes. In doing so, researchers can be confident that they are valid in use and thus can be used consistently for research purposes. Furthermore, the findings show that although there are similarities between a RU and RL tackle, clear differences exist and therefore justifies the need for specific RL variables during tackle research.

Video analysis research into the rugby league tackle typically uses technical criteria from coaching cues or tackle variables from rugby union. As such, the content validity and relevance could be questioned. A video analysis framework which establishes appropriate variables for rugby league is therefore required. The aim of this study was to adopt a 5-stage process to establish a video analysis framework for the rugby league tackle, which was content valid, relevant and reliable. The 5-stage process included 1) creation of draft variable list (video analysis framework), using available rugby tackle research, 2) expert group recruitment and critique, 3) refinement of video analysis framework to establish content validity, 4) response process validity task and agreement within expert group, 5) intra- and inter-reliability testing using Kappa statistics. The agreed video analysis framework comprised 6 phases including; tackle event, defensive start point, pre-contact, initial contact, post-contact and play the ball. Within the identified phases, 63 variables were established. The intra- and inter-reliability testing resulted in strong agreement (>0.81-1.0) within all phases. The 5-stage process allowed for the creation of a valid, relevant and reliable video analysis framework. The video analysis framework can be used in rugby league tackle research, categorising complex tackle events such as injurious or optimal tackles, improving both player welfare and performance. Furthermore, the application of the video analysis framework to future rugby league research will increase the coherence and usefulness of research findings.

Rugby league has a relatively high injury risk, with the tackle having the greatest injury propensity. The number of tackles players engage in, prior to injurious tackles may influence injury risk, which has yet to be investigated. Therefore, this study investigated if rugby league players are involved in more tackles (as either tackler or ball carrier) (i) in the 10 minutes, or (ii) 1-min periods prior to an injurious tackle-event, (iii) differences for ball carriers vs. tacklers, and (iv) forwards vs. backs. Video analysis was utilised to quantify the number and rate of tackles in the 10-min periods prior to 61 tackle-related injuries. One thousand two hundred and eighty 10-min periods where players were not injured, were used as matched-controls. Generalized mixed linear models were used to analyse mean total and rate for tackles. Injured players were involved in significantly fewer tackles during the 10-min period, yet significantly more tackles during the final minute prior to the injurious tackle-event, compared to non-injured players. There were no differences between ball carriers vs. tacklers during the 10-min period. Both injured position groups were involved in significantly more tackles in the final minute. Additional match data sources are needed to further inform injury preventive strategies of tackle events.