Risk evaluation in professional football

Risk management is composed of three major elements viz., hazard identification, risk estimation and risk evaluation. The aim of hazard identification and risk estimation is to identify the outcomes from risk, the magnitude of the associated con&quences from risk, and the estimation of the probabilities of these outcomes. Previous work focused on hazard identification and risk estimation and identified the relatively high risks associated with playing professional football. By adhering to the risk management process, the aim of this thesis was to determine the significance of these high risks to football clubs and their players. A theoretical framework was designed to evaluate the influence of player injury on the financial and playing performance of professional football clubs. This framework was also used to assess, through use of cost benefit analysis, the practicalities of investing in suitable injury prevention strategies, to reduce the risks to football clubs and their players. Former professional footballers were surveyed to investigate the long-term medical and socioeconomic consequences associated with the high risks of playing professional football. The results identified the high financial costs associated with player injury on professional football clubs. Although the high risks of player injury have a relatively minor effect on teamperformance of the Premier League clubs, this effect still has a relatively major influence on the financial performance of the club. In contrast, the influence of player injury to teamperformance was relatively major for Division I and Division 2 clubs, but this had a relatively minor effect on financial performance. The application of cost benefit analysis to the investment of specialist personnel to reduce the risks of injury demonstrated that the proposals were practicable for Premier League and Division I clubs only. In addition, it was also demonstrated that the high risks associated with playing professional football have a significant influence on the long-term well-being of foriner players. One-third of former players had been medically diagnosed osteoarthritic in a lower limb joint. The majority of players also perceived that injury had a negative influence on their present and future welfare. The results demonstrate that the consequences associated with the relatively high acute injury risk also have a significant effect on the financial and playing performance of football clubs and the future welfare of their players

WIMU instrumentation of skeleton "ASSASSIN" trainer & sled

Skeleton is a high‐speed Winter Olympic sport performed on the same twisting, downhill ice tracks used for Bobsleigh & Luge. The single rider sprints and pushes their sled for 20‐30m on a level start section before loading and going through a twisting course of over 1km, at speeds up to 140km/h, experiencing up to 5g. In competition, the top athletes can be within a fraction of a second of each other. The initial short pushing period is believed to be critical to overall performance but it is not well understood. A collaborative project between University of Bath, UK Sport and Tyndall National Institute is instrumenting skeleton athletes, training equipment and test tracks with Tyndall’s Wireless Inertial Measurement Unit technology in order to investigate and improve understanding of this phase of a skeleton run. It is hoped this will lead to improved training regimes and better performance of such elite, Olympic level athletes. This work presents an initial look at the system as implemented and data recorded

Movement Demands of Elite U20 International Rugby Union Players

The purpose of this study was to quantify movement demands of elite international age grade (U20) rugby union players during competitive tournament match play. Forty elite professional players from an U20 international performance squad were monitored using 10 Hz global positioning systems (GPS) during 15 international tournament matches during the 2014/15 and 2015/16 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 161) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR--Front Row (prop & hooker), SR--Second Row, BR--Back Row (Flankers & No.8), HB--Half Backs (scrum half & outside half), MF--Midfield (centres), B3--Back Three (wings & full back) for match analysis. Analysis revealed significant differences between forwards and backs positions. Backs scored higher on all variables measured with the exception of number of moderate accelerations, decelerations (no difference). The centres covered the greatest total distance with the front row covering the least (6.51 ± 0.71 vs 4.97 ± 0.75 km, p < 0.001). The front row also covered the least high speed running (HSR) distance compared to the back three (211.6 ± 112.7 vs 728.4 ± 150.2 m, p < 0.001) who covered the most HSR distance, affirming that backs cover greater distances but forwards have greater contact loads. These findings highlight for the first time differences in the movement characteristics of elite age grade rugby union players specific to positional roles

Movement Demands of Elite Under-20s and Senior International Rugby Union Players

This study compared the movement demands of elite international Under-20 age grade (U20s) and senior international rugby union players during competitive tournament match play. Forty elite professional players from an U20 and 27 elite professional senior players from international performance squads were monitored using 10Hz global positioning systems (GPS) during 15 (U20s) and 8 (senior) international tournament matches during the 2014 and 2015 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 258) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR–Front Row (prop & hooker), SR–Second Row, BR–Back Row (Flankers & No.8), HB–Half Backs (scrum half & outside half), MF–Midfield (centres), B3 –Back Three (wings & full back) for match analysis. Linear mixed models revealed significant differences between U20 and senior teams in both the forwards and backs. In the forwards the seniors covered greater HML distance (736.4 ± 280.3 vs 701.3 ± 198.7m, p = 0.01) and severe decelerations (2.38 ± 2.2 vs 2.28 ± 1.65, p = 0.05) compared to the U20s, but performed less relative HSR (3.1 ± 1.6 vs 3.2 ± 1.5, p < 0.01), moderate (19.4 ± 10.5 vs 23.6 ± 10.5, p = 0.01) and high accelerations (2.2 ± 1.9 vs 4.3 ± 2.7, p < 0.01) and sprint•min-1 (0.11 ± 0.06 vs 0.11 ± 0.05, p < 0.01). Senior backs covered a greater relative distance (73.3 ± 8.1 vs 69.1 ± 7.6 m•min-1, p < 0.01), greater High Metabolic Load (HML) distance (1138.0 ± 233.5 vs 1060.4 ± 218.1m, p < 0.01), HML efforts (112.7 ± 22.2 vs 98.8 ± 21.7, p < 0.01) and heavy decelerations (9.9 ± 4.3 vs 9.5 ± 4.4, p = 0.04) than the U20s backs. However, the U20s backs performed more relative HSR (7.3 ± 2.1 vs 7.2 ± 2.1, p <0.01) and sprint•min-1 (0.26 ± 0.07 vs 0.25 ± 0.07, p < 0.01). Further investigation highlighted differences between the 6 positional groups of the teams. The positional groups that differed the most on the variables measured were the FR and MF groups, with the U20s FR having higher outputs on HSR, moderate & high accelerations, moderate, high & severe decelerations, HML distance, HML efforts, and sprints•min-1. For the MF group the senior players produced greater values for relative distance covered, HSR, moderate decelerations, HML distance and sprint•min-1. The BR position group was most similar with the only differences seen on heavy accelerations (U20s higher) and moderate decelerations (seniors higher). Findings demonstrate that U20s internationals appear to be an adequate ‘stepping stone’ for preparing players for movement characteristics found senior International rugby, however, the current study highlight for the first time that certain positional groups may require more time to be able to match the movement demands required at a higher playing level than others. Conditioning staff must also bear in mind that the U20s players whilst maintaining or improving match movement capabilities may require to gain substantial mass in some positions to match their senior counterparts

Can salivary testosterone and cortisol reactivity to a mid-week stress test discriminate a match outcome during international rugby union competition?

ObjectivesEvidence suggests that stress-induced changes in testosterone and cortisol are related to future competitive behaviours and team-sport outcomes. Therefore, we examined whether salivary testosterone and cortisol reactivity to a mid-week stress test can discriminate a match outcome in international rugby union competition.DesignSingle group, quasi-experimental design with repeated measures.MethodThirty-three male rugby players completed a standardised stress test three or four days before seven international matches. Stress testing involved seven minutes of shuttle runs (2 × 20 m), dispersed across one-minute stages with increasing speeds. Salivary testosterone and cortisol were measured in the morning, along with delta changes from morning to pre-test (Morn-PreΔ) and pre-test to post-test (Pre-PostΔ). Data were compared across wins (n = 3) and losses (n = 4).ResultsThe Morn-PreΔ in cortisol increased before winning and decreased prior to losing (p < 0.001), with a large effect size difference (d = 1.6, 90% CI 1.3-1.9). Testosterone decreased significantly across the same period, irrespective of the match outcome. The Morn-PreΔ in testosterone and cortisol, plus the Pre-PostΔ in testosterone, all predicted a match outcome (p ≤ 0.01). The final model showed good diagnostic accuracy (72%) with cortisol as the main contributor.ConclusionsThe salivary testosterone and cortisol responses to mid-week testing showed an ability to discriminate a rugby match outcome over a limited number of games. The Morn-PreΔ in cortisol was the strongest diagnostic biomarker. This model may provide a unique format to assess team readiness or recovery between competitions, especially with the emergence of rapid hormonal testing

Relationships between physical qualities and key performance indicators during match-play in senior international rugby union players

The use of physical tests to profile physical capabilities, and provide training direction to athletes is common practice. Likewise, in professional team sports, notational analysis codes the key contributions of each player during competition. Limited studies have however investigated relationships between physical capabilities and key performance indicators (KPIs) of rugby union match-play. Elite professional players, categorised as forwards (n = 15) or backs (n = 14), from an international rugby union squad (n = 29) undertook assessments of isometric mid-thigh pull (IMTP), bilateral and unilateral countermovement jumps (CMJ) and drop jumps (DJ; from 40 and 20 cm, respectively), and assessment of acceleration (10 m), a 5 m weighted sled drive, and a Yo-Yo intermittent recovery test level 1 (Yo-Yo IRTL1). Game statistics of the same players from 92 matches (~23 matches per player) during the 2014-15 season were analysed for effort and performance-based metrics. For forwards, Yo-Yo IRTL1 correlated significantly with; number of tackles made (r = 0.717), first three players at a ruck in both attack (r = 0.568) and defence (r = 0.581), number of effective rucks (r = 0.630), total possessions (r = 0.522), passes made (r = 0.651), percentage of carries over the gainline (r = 0.610), effective ruck success (r = 0.600), tackle success (r = 0.540), and the number of turnovers made (r = 0.518). Drop jump performance in forwards was associated with; the number of clean breaks (r = 0.558), dominant collisions (r = 0.589), and offloads (r = 0.594). For backs, the sled-drive test correlated with; number of carries (r = -0.751), first three players at an attacking ruck (r = -0.613), effective attacking rucks (r = -0.584), number of dominant collisions (r = -0.792) and offloads (r = -0.814). Likewise, for backs, IMTP peak force was related to; the number of possessions (r = 0.793), passes made (r = 0.792), effective attacking ruck percentage (r = 0.628), and the number of offloads (r = 0.621) whilst relative peak force correlated with; the percentage of carries over the gainline (r = 0.533), percent tackle success (r = 0.603) and effective attacking ruck percentage (r = 0.584). Regression analyses highlighted that only a small number of variables (i.e., carries, tackles, attacking and defensive first three at ruck) returned practically achievable changes (&lt;20%) in physical qualities. In spite of this, and while leaving scope identification of further physical and/or performance predictors, greater strength, power and intermittent running performance were positively related to match-derived KPIs during competition. This may provide a basis for better integrating the strategies used by physical and technical performance-focused coaching staff to improve key performance indicators, and thus match performance, of rugby union players

Movement Demands of Elite Under-20s and Senior International Rugby Union Players

This study compared the movement demands of elite international Under-20 age grade (U20s) and senior international rugby union players during competitive tournament match play. Forty elite professional players from an U20 and 27 elite professional senior players from international performance squads were monitored using 10Hz global positioning systems (GPS) during 15 (U20s) and 8 (senior) international tournament matches during the 2014 and 2015 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 258) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR–Front Row (prop &amp; hooker), SR–Second Row, BR–Back Row (Flankers &amp; No.8), HB–Half Backs (scrum half &amp; outside half), MF–Midfield (centres), B3 –Back Three (wings &amp; full back) for match analysis. Linear mixed models revealed significant differences between U20 and senior teams in both the forwards and backs. In the forwards the seniors covered greater HML distance (736.4 ± 280.3 vs 701.3 ± 198.7m, p = 0.01) and severe decelerations (2.38 ± 2.2 vs 2.28 ± 1.65, p = 0.05) compared to the U20s, but performed less relative HSR (3.1 ± 1.6 vs 3.2 ± 1.5, p -1. For the MF group the senior players produced greater values for relative distance covered, HSR, moderate decelerations, HML distance and sprint•min-1. The BR position group was most similar with the only differences seen on heavy accelerations (U20s higher) and moderate decelerations (seniors higher). Findings demonstrate that U20s internationals appear to be an adequate ‘stepping stone’ for preparing players for movement characteristics found senior International rugby, however, the current study highlight for the first time that certain positional groups may require more time to be able to match the movement demands required at a higher playing level than others. Conditioning staff must also bear in mind that the U20s players whilst maintaining or improving match movement capabilities may require to gain substantial mass in some positions to match their senior counterparts