Discovery and Characterisation of Forward Line Formations at Centre Bounces in the Australian Football League

The extent of player formation usage and the characteristics of player arrangements are not well understood in Australian football, unlike other team-based invasion sports. Using player location data from all centre bounces in the 2021 Australian Football League season; this study described the spatial characteristics and roles of players in the forward line. Summary metrics indicated that teams differed in how spread out their forward players were (deviation away from the goal-to-goal axis and convex hull area) but were similar with regard to the centroid of player locations. Cluster analysis, along with visual inspection of player densities, clearly showed the presence of different repeated structures or formations used by teams. Teams also differed in their choice of player role combinations in forward lines at centre bounces. New terminology was proposed to describe the characteristics of forward line formations used in professional Australian Football.

Peak movement and impact characteristics of different training methods in professional rugby union

The purpose of this study was to compare the peak periods (1- to 6-minute epochs) for three different training methods (game-based training - GBT; small-sided games - SSG; and conditioning training - CT) in elite male rugby union (RU) players. The peak movement (m·min^-1) and impact (impact·min^-1) characteristics of 42 players during in-season training were assessed. When comparing between training methods, SSG drills produced the greatest peak movement characteristics for all time epochs (1-minute average peak periods - SSG 195 m·min^-1, GBT 160 m·min^-1, and CT 144 m·min^-1). The peak impact characteristics performed during training were 1-2 impact·min^-1 for a 1-minute period and then decreased as the time period increased for all training methods. The greatest distribution of training time occurred at 30-39% (SSG and CT) and 40-49% (GBT) of peak movement intensity, with less than 5% of training performed at or above 80% peak intensity across all drill types. Findings from the current study show that the peak movement periods (m·min^-1) in RU training from all three training methods match or exceed those which are previously reported in peak gameplay, yet their ability to replicate peak impact characteristics is questionable.

Association Between Position-Specific Impact and Movement Characteristics of Professional Rugby Union Players During Game Play

ABSTRACT

Peek, RJ, Carey, DL, Middleton, KJ, Gastin, PB, and Clarke, AC. Association between position-specific impact and movement characteristics of professional rugby union players during game play. J Strength Cond Res 37(1): 161-166, 2023-The aim of this study was to understand the association between impact and movement characteristics during whole game and peak 1- to 10-minute rolling windows in professional rugby union. Maximal impact (impacts·min-1) and corresponding running (m·min-1) characteristics as well as maximal running (m·min-1) and corresponding impact (impacts·min-1) characteristics were obtained for 160 athletes from 4 teams across the 2018 and 2019 Super Rugby seasons. A linear mixed-effects model reported a positive association between whole-game running and impacts, where greater impact characteristics corresponded with greater running characteristics. The average 1-minute peak running characteristics (150-160 m·min-1) typically occurred when no impacts occurred. The average 1-minute peak impact characteristics (4-6 impacts·min-1) corresponded with an average relative distance of 90-100 m·min-1. Worst case scenario observed impact characteristics as large as 15 impacts·min-1 with a corresponding relative distance of 140 m·min-1. When training for peak period characteristics, running may be completed in isolation; however, peak impacts often occur in conjunction with moderate to high running movements. Given running and impact characteristics can appear concurrently within game play, this highlights the need to train them accordingly. As such, when prescribing training drills to replicate the peak characteristics in rugby union, consideration should be taken for both running and impact characteristics.

Characterising Psycho-Physiological Responses and Relationships during a Military Field Training Exercise

Over a 15-day period, that included an eight-day field trial, the aims of this study were to (1) quantify the physical workload, sleep and subjective well-being of soldiers in training; (2a) Explore relationships between workload and well-being, and (2b) sleep and well-being; (3) Explore relationships between workload, sleep, and well-being.

METHODS

Sixty-two Combat Engineer trainees (59 male, 3 female; age: 25.2 ± 7.2 years) wore an ActiGraph GT9X to monitor daily energy expenditure, physical activity, and sleep. Rating of perceived exertion (RPE), sleep quality, and fatigue were measured daily, subjective well-being was reported days 1, 5, 9, 13 and 15. Multi-level models were used for the analysis.

RESULTS

Well-being was affected by a combination of variables including workload, subjective sleep quality, sleep duration, and sleep efficiency. RPE and subjective sleep quality were consistently significant parameters within the models of best fit.

CONCLUSIONS

Perceptions of well-being were lower during the field training when physical workload increased, and sleep decreased. Energy expenditure was comparatively low, while daily sleep duration was consistent with field training literature. Subjective assessments of workload and sleep quality were consistently effective in explaining variations in well-being and represent an efficient approach to monitor training status of personnel.

Quantification of Recruit Training Demands and Subjective Wellbeing during Basic Military Training

Purpose: Assess and describe the physical demands and changes in subjective wellbeing of recruits completing the 12 week Australian Army Basic Military Training (BMT) course. Methods: Thirty-five recruits (24.8 ± 6.8 y; 177.4 ± 10.1 cm, 75.6 ± 14.7 kg) consented to daily activity monitoring and weekly measures of subjective wellbeing (Multi-component Training Distress Scale, MTDS). The physical demands of training were assessed via wrist worn activity monitors (Actigraph GT9X accelerometer). Physical fitness changes were assessed by push-ups, sit-ups and multi-stage shuttle run in weeks 2 and 8. Results: All objective and subjective measures significantly changed (p < 0.05) across the 12 week BMT course. In parallel, there was a significant improvement in measures of physical fitness from weeks 2 to 8 (p < 0.001). The greatest disturbance to subjective wellbeing occurred during week 10, which was a period of field training. Weeks 6 and 12 provided opportunities for recovery as reflected by improved wellbeing. Conclusions: The physical demands of training varied across the Australian Army 12 week BMT course and reflected the intended periodization of workload and recovery. Physical fitness improved from week 2 to 8, indicating a positive training response to BMT. Consistent with findings in sport, wellbeing measures were sensitive to fluctuations in training stress and appear to have utility for individual management of personnel in the military training environment.

Elite Junior Australian Football Players With Impaired Wellness Are at Increased Injury Risk at High Loads

BACKGROUND

Elite junior Australian football players experience high training loads across levels of competition and training. This, in conjunction with impaired wellness, can predispose athletes to injury.

HYPOTHESIS

Elite junior Australian football players exposed to high loads with poor wellness are more likely to be at risk of injury than those with improved wellness.

STUDY DESIGN

Longitudinal prospective cohort study.

LEVEL OF EVIDENCE

Level 3.

METHODS

Data were collected and analyzed from 280 players across the 2014 season. Internal load was measured via session rating of perceived exertion. Player wellness was reported according to ratings of sleep quality, fatigue, soreness, stress, and mood. Week- and month-based training load measures were calculated, representing a combination of absolute and relative load variables. Principal component analysis factor loadings, based on 17 load and wellness variables, were used to calculate summed variable covariates. Injury was defined as "any injury leading to a missed training session or competitive match." Associations between covariates and injury risk (yes/no) were determined via logistic generalized estimating equations.

RESULTS

A significant interaction term between load and wellness on injury was found [odds ratio (OR) 0.76; 95% CI 0.62-0.92; P < 0.01), indicating that wellness acts as a "dimmer switch" of load on injury. Further, there was evidence of moderated mediation (OR 0.71; 95% CI 0.57-0.87; P < 0.01). When wellness was low, injury risk started to increase substantially at a 1-week load of 3250 au.

CONCLUSIONS

Subjective measures of training load are associated with injury risk through a nonlinear relationship. This relationship is further influenced by player wellness, which can amplify the risk of injury. There is evidence that higher stress is linked with injury and that soreness and sleep mediate any stress-injury relationship.

CLINICAL RELEVANCE

Coaching efforts to manage training load and player adaptive responses, including wellness, may reduce the risk of injury, with stress, soreness, and sleep particularly relevant at this level.

Techniques to derive and clean acceleration and deceleration data of athlete tracking technologies in team sports: A scoping review

The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.

Sleep of recruits throughout basic military training and its relationships with stress, recovery, and fatigue

Objective

Studies in basic military training (BMT) examining sleep are largely cross-sectional, and do not investigate relationships between sleep, stress, recovery and fatigue. The aims of this study were to (1a) quantify changes in recruits’ sleep quantity and quality over 12 weeks of BMT; (1b) quantify changes in recruits’ perceptions of stress, fatigue and recovery over BMT; and (2) explore relationships between sleep, and perceptions of stress, fatigue and recovery.

Methods

45 recruits (37 male; 8 female, age: 25.2 ± 7.2 years, height: 176.2 ± 10.0 cm, mass: 76.8 ± 15.0 kg) wore ActiGraph GT9X’s for 12 weeks of BMT, collecting sleep duration, efficiency and awakenings. Subjective sleep quality, fatigue were measured daily, with stress and recovery measured weekly. Multi-level models assessed relationships between sleep, and stress, recovery, and fatigue.

Results

Objective daily means for sleep duration were 6.3 h (± 1.2 h) and 85.6% (± 5.5%) for sleep efficiency. Main effects were detected for all mean weekly values (p < 0.05). Sleep quality showed the strongest relationships with stress, recovery and fatigue. The best model to explain relationships between, stress, recovery and fatigue, included sleep quality, sleep duration, sleep efficiency and awakenings.

Conclusions

The reported mean sleep duration of 6.3 h per night may negatively impact training outcomes across BMT. Combining both subjective and objective measures of sleep best explained relationships between sleep metrics stress, fatigue and recovery. Perceived sleep quality was most strongly related to change in stress, recovery, or post-sleep fatigue.

Questionnaire-Derived Sleep Habits and Academic Achievement in First Year University Students

This study aimed to determine the effect of sleep quantity and quality via the Pittsburgh Sleep Quality Index (PSQI) on students’ academic achievement in their first year of university study. In this cross-sectional study, 193 students (102 female, 91 male, mean ± SD; age = 19.3 ± 2.9 y) from an undergraduate Health degree in New Zealand completed the PSQI four weeks prior to the end of the semester in their first year of university study. Results from three core subjects in the first semester were averaged and correlations between the PSQI and academic success were evaluated using Spearman’s rho (ρ). The group were also trichotomized using a PSQI global score of ≤5 as the threshold for “good” sleepers (n = 62, 32%), a score of 5–8 for “moderate” sleepers (n = 63, 33%) and a score ≥8 to characterize “poor” sleepers (n = 68, 35%). Overall, students averaged 7 h 37 min of self-reported sleep duration with an average bedtime of 22:55 p.m. and wake time of 8:01 a.m. There was a significant, small inverse relationship between academic performance and bedtime (p = 0.03, ρ = −0.14), with those going to bed earlier having superior academic success. The trichotomized data demonstrated no significant differences in academic performance between students with poor, moderate and good sleep quality (p = 0.92). Later bedtimes were associated with lower academic performance in a group of first year university students. However, there were no other relationships observed between academic success and self-reported sleep quality or quantity as determined by the PSQI. Enhancing awareness of the impact of sleep timing on academic success should be prioritized and strategies to improve sleep hygiene should be promoted to university students.

Predicting Youth Athlete Sleep Quality and the Development of a Translational Tool to Inform Practitioner Decision Making

BACKGROUND

Identifying key variables that predict sleep quality in youth athletes allows practitioners to monitor the most parsimonious set of variables that can improve athlete buy-in and compliance for athlete self-report measurement. Translating these findings into a decision-making tool could facilitate practitioner willingness to monitor sleep in athletes.

HYPOTHESIS

Key predictor variables, identified by feature reduction techniques, will lead to higher predictive accuracy in determining youth athletes with poor sleep quality.

STUDY DESIGN

Cross-sectional study.

LEVEL OF EVIDENCE

Level 3.

METHODS

A group (N = 115) of elite youth athletes completed questionnaires consisting of the Pittsburgh Sleep Quality Index and questions on sport participation, training, sleep environment, and sleep hygiene habits. A least absolute shrinkage and selection operator regression model was used for feature reduction and to select factors to train a feature-reduced sleep quality classification model. These were compared with a classification model utilizing the full feature set.

RESULTS

Sport type, training before 8 am, training hours per week, presleep computer usage, presleep texting or calling, prebedtime reading, and during-sleep time checks on digital devices were identified as variables of greatest influence on sleep quality and used for the reduced feature set modeling. The reduced feature set model performed better (area under the curve, 0.80; sensitivity, 0.57; specificity, 0.80) than the full feature set models in classifying youth athlete sleep quality.

CONCLUSION

The findings of our study highlight that sleep quality of elite youth athletes is best predicted by specific sport participation, training, and sleep hygiene habits.

CLINICAL RELEVANCE

Education and interventions around the training and sleep hygiene factors that were identified to most influence the sleep quality of youth athletes could be prioritized to optimize their sleep characteristics. The developed sleep quality nomogram may be useful as a decision-making tool to improve sleep monitoring practice among practitioners.

Motives for Dropout Among Former Junior Elite Caribbean Track and Field Athletes: A Qualitative Investigation

Anecdotal reports within the Caribbean track and field fraternity have revealed that there is a high level of athlete dropout from competitive sport at the junior-elite level, and a poor transition to senior-elite status. Consequently, this qualitative investigation explored the key motives that may have contributed toward the unsuccessful transitions and ensuing dropout of Caribbean track and field athletes during the junior to senior transition period. Eleven former junior-elite track and field athletes (four males, seven females; M_age = 29, SD ± 4.2 years) from four English-speaking Caribbean islands participated in semi-structured interviews. Following an inductive and deductive thematic analysis, four higher order themes were identified: (1) “there's not enough support”; (2) “felt pressure to make sure I committed”; (3) “it's always competitive here”; and (4) “battle with the injuries.” For these former junior-elite Caribbean athletes, the decision on whether to continue within the sport was influenced by a combination of factors, although inadequate financial and organizational support had the most bearing on athletes' decision to drop out during the crucial transition years. Implications for consideration by key stakeholders and policymakers within the region are discussed.

Technical determinants of success in professional women's soccer: A wider range of variables reveals new insights

Knowledge of optimal technical performance is used to determine match strategy and the design of training programs. Previous studies in men’s soccer have identified certain technical characteristics that are related to success. These studies however, have relative limited sample sizes or limited ranges of performance indicators, which may have limited the analytical approaches that were used. Research in women’s soccer and our understanding of optimal technical performance, is even more limited (n = 3). Therefore, the aim of this study was to identify technical determinants of match outcome in the women’s game and to compare analytical approaches using a large sample size (n = 1390 team performances) and range of variables (n = 450). Three different analytical approaches (i.e. combinations of technical performance variables) were used, a data-driven approach, a rational approach and an approach based on the literature in men’s soccer. Match outcome was modelled using variables from each analytical approach, using generalised linear modelling and decision trees. It was found that the rational and data-driven approaches outperformed the literature-driven approach in predicting match outcome. The strongest determinants of match outcome were; scoring first, intentional assists relative to the opponent, the percentage of shots on goal saved by the goalkeeper relative to the opponent, shots on goal relative to the opponent and the percentage of duels that are successful. Moreover the rational and data-driven approach achieved higher prediction accuracies than comparable studies about men’s soccer.

Impact of the talent development environment on the wellbeing and burnout of Caribbean youth track and field athletes

This study examined the perceived talent development environment (TDE) of youth track and field athletes within the Caribbean region and explores the relationship with their subjective wellbeing and burnout levels. A sample of 400 Caribbean youth track and field athletes (male = 198, and female = 202; age 13-20 years) participated in this cross-sectional study. Athletes responded to a survey which included the Talent Development Environment Questionnaire (TDEQ-5), the World Health Organization Wellbeing Index (WHO-5) and the Athlete Burnout Questionnaire (ABQ). Structural equation modelling showed that a positive and supportive TDE was associated with better athlete wellbeing and lower athlete burnout. Moreover, gender and hours of training moderated relationships of athletes' perceptions of their development environment with wellbeing and burnout levels respectively. Furthermore, there was a positive association between the support network and athlete wellbeing, while holistic quality preparation was negatively associated with athlete burnout. Development environments perceived as supportive and geared towards a holistic athlete-centred approach were associated with better athlete wellbeing and lower burnout.

Network analysis of kick-in possession chains in elite Australian football

The study aim was to investigate ball movement patterns using network analysis techniques, to compare between successful and unsuccessful outcomes and teams in the Australian Football League (AFL). This analysis focused on possession chains starting from a kick-in (n = 1,720), drawn from all games played in the 2015 AFL Premiership season (18 teams, 206 games). Player interactions were quantified using four network metrics: cluster coefficient, degree centrality, network density, and entropy. Three-way ANOVA with Tukey post hoc and ω2 effect sizes were calculated to assess whether differences existed between kick-in outcomes, ladder brackets, and match outcomes for each network metric. No significant differences were observed between ladder brackets or match outcomes for any network metric. More successful kick-in chains were characterised by lower density (ω2 = 0.26, large effect; F(9, 1678) = 66.6, p < 0.00) and higher entropy (ω2 = 0.17, large effect; F(9, 1678) = 39.6, p < 0.00). This suggests that chains resulting in successful kick-in outcomes exhibited lower interconnectedness, with a high number of players involved, and lower predictability in ball movement patterns. These findings have practical value for coaches and performance analysts and support further applications of network analysis in Australian football.

Is injury associated with team performance in elite Australian football? 20 years of player injury and team performance data that include measures of individual player value

OBJECTIVES

To determine whether specific injury measures were associated with team performance in the Australian Football League (AFL).

METHODS

15 289 injuries caused players from 18 teams to miss 51 331 matches between 1997 and 2016. Data were aggregated to the team level. We analysed the associations among injury measures and team performance (reaching finals/playoffs and specific ladder/table position). Injury measures per team included: injury incidence, injury severity, injury burden, player match availability and percentage of the full player roster injured. We also weighted injury measures by five measures of player value.

RESULTS

AFL teams' injury burden and player match availability were associated with final table position (r2=0.03, p<0.05). Player value weighted injury burden was different between finalists and non-finalists (mean difference=-8, p<0.001) and explained 12% of the variation in the table position of teams (p<0.001). For a team, nine missed matches due to injury (burden weighted by a best and fairest player rating system) was associated with one lower table position. Player match availability weighted by player value was higher for finalists than non-finalists (mean difference=1.7, p<0.01) and explained 7% of the variation in the table position of teams (p<0.001).

DISCUSSION AND POTENTIAL IMPLICATIONS

The impact of injury (burden weighted by best and fairest) explained up to 12% of the variation in final table position-this is particularly relevant to making/not making playoffs as well as home ground/travel advantages for those teams that make the one-game format of AFL playoffs (not home-away or best of seven format).

Absolute and Relative Load and Injury in Elite Junior Australian Football Players Over 1 Season

PURPOSE

To investigate the association between training and match loads and injury in elite junior Australian football players over 1 competitive season.

METHODS

Elite junior Australian football players (n = 290, age 17.7 [0.3] y, range 16-18 y) were recruited from the under-18 state league competition in Victoria to report load and injury information. One-week load (session rating of perceived exertion multiplied by duration) and all time-loss injuries were reported using an online sport-injury surveillance system. Absolute load measures (weekly sums) enabled the calculation of relative measures such as the acute:chronic workload ratio. Load measures were modeled against injury outcome (yes/no) using a generalized estimating equation approach, with a 1-wk lag for injury.

RESULTS

Low (<300 arbitrary units [au]) and high (>4650 au) 1-wk loads were associated with significantly higher risk of injury. Furthermore, low (<100 au) and high (>850 au) session loads were associated with a higher risk of injury. High strain values (>13,000) were associated with up to a 5-fold increase in the odds of injury. There was a relatively flat-line association between the acute:chronic workload ratio and injury.

CONCLUSIONS

This study is the first investigation of elite junior athletes demonstrating linear and nonlinear relationships between absolute and relative load measures and injury. Coaches should focus player loads on, or at least close to, the point at which injury risk starts to increase again (2214 au for 1-wk load and 458 au for session load) and use evidence-based strategies across the week and month to help reduce the risk of injury.

Understanding the relative contribution of technical and tactical performance to match outcome in Australian Football

The aim of this study was to assess if tactical and technical performance indicators (PIs) could be used in combination to model match outcomes in Australian Football (AF). A database of 101 technical PIs and 14 tactical PIs from every match in the 2009-2016 Australian Football League (AFL) seasons was merged. Two outcome measures Win-loss and Score margin were used as dependent variables. The top 45 ranked technical and tactical PIs from a feature selection process were used to model match outcome using decision tree and Generalised Linear Models (GLMs). Of the top 45 selected features, this included seven tactical PIs. The Win-loss-based Decision tree model achieved a classification accuracy of 89.0% and GLM 93.2%. A Score margin-based GLM achieved a root mean squared error (RMSE) of 6.9 points. A combined approach to the classification of match outcomes provided no improvement in model accuracy compared with previous literature. However, this study has established the relative importance of technical and tactical measures of performance in relation to successful team performance in AF.

Deceleration, Acceleration, and Impacts Are Strong Contributors to Muscle Damage in Professional Australian Football

Gastin, PB, Hunkin, SL, Fahrner, B, and Robertson, S. Deceleration, acceleration, and impacts are strong contributors to muscle damage in professional Australian football. J Strength Cond Res 33(12): 3374-3383, 2019-The purpose of this study was to investigate the relationships between serum creatine kinase [CK], an indirect marker of muscle damage, and specific indices of match load in elite Australian football. Twenty-six professional players were assessed during a competitive Australian Football League (AFL) season. [CK] was collected 24-36 hours before match and 34-40 hours after match during 8 in-season rounds. An athlete-tracking technology was used to quantify match load. Generalized estimating equations and random forest models were constructed to determine the extent to which match-load indices and pre-match [CK] explained post-match [CK]. There was a 129 ± 152% increase in [CK] in response to AFL competition. Generalized estimating equations found that number of impacts >3g (p = 0.004) and game time (p = 0.016) were most strongly associated with post-match [CK]. Random forest, with considerably lower errors (130 vs. 316 U·L), found deceleration, acceleration, impacts >3g, and sprint distance to be the strongest predictors. Pre-match [CK] accounted for 11% of post-match [CK], and considerable interindividual and intraindividual variability existed in the data. Creatine kinase, an indicator of muscle damage, was considerably elevated as a result of AFL competition. Parametric and machine-learning analysis techniques found several indices of physical load associated with muscle damage during competition, with impacts >3g and high-intensity running variables as the strongest predictors. [CK] may be used as a global measure of muscle damage in field team sports such as AF, yet with some caution given cost, invasiveness, and inherent variability. Quantifying physical load and the responses to that load can guide athlete management decision-making and is best undertaken within a suite of practical, sport-specific measures, where data are interpreted individually and with an understanding of the limitations.

Construct validity and reliability of the Talent Development Environment Questionnaire in Caribbean youth track and field athletes

Caribbean nations stand to benefit significantly from the potential insights that can be gained from the assessment of their athlete talent development environments; which in turn can lead to the formulation of evidence-based strategies and improvements to their sport development pathways. The principal aim of this study was to examine the psychometric properties of the 25-item TDEQ-5 to determine its validity to assess the development environments of talented youth track and field athletes from six English-speaking Caribbean countries. As a secondary aim, we sought to examine athletes’ perceptions of their talent development environment within this context. Confirmatory factor analysis revealed adequate model fit of a re-specified model and good overall internal reliability of the scale, therefore offering support for its use within this context. Furthermore, adequate construct validity and internal reliability was found within three subscales (i.e., communication, holistic quality preparation and support network) with subpar scores within two subscales (i.e., long-term development focus and alignment of expectations). Preliminary findings on athletes’ perceptions of their environment revealed key strengths in coaches’ long-term development focus and communication, however deficiencies were noted in the accessibility and availability of sport-related support and preparation of athletes. In conclusion, the re-specified TDEQ-5 with 25 items appears to be a reliable and valid measure within the Caribbean context. However, it is recommended that the scale be used with some caution with regard to the interpretation of results for the ‘long-term development focus’ and ‘alignment of expectations’ subscales.

Factors Influencing the Early Development of World-Class Caribbean Track and Field Athletes: A Qualitative Investigation

This qualitative investigation sought to explore through a socio-cultural lens the perceived early training and competition environment, and support network of world-class Caribbean track and field athletes and the influence on their sport engagement and progression during early childhood and adolescence. Sixteen world-class track and field athletes (8 males and 8 females; M age = 29, SD = 5 years) from 6 English-speaking Caribbean islands took part in semi-structured interviews. A thematic analysis was performed on the transcribed data. Three superordinate themes were identified as key factors that influenced the early sporting development of world-class Caribbean athletes: (1) conducive sporting environment, (2) functional social support network, and (3) key organizational input. Findings revealed that perceived high levels of deliberate play activity in childhood (6 - 12 years) and an intense track and field competition culture in adolescence (13 - 20 years) were conducive to the continued engagement and progression of world-class Caribbean track and field athletes at the junior level. Furthermore, world-class athletes perceived themselves to be positively influenced by the support received from their immediate social support network and key organizations during this period. This study showed that a conducive sporting environment coupled with optimal social and organizational support may have encouraged world-class Caribbean athletes to remain engaged in track and field and to successfully progress within the sport at the junior level. Findings shed light on the sporting culture at the junior level within the Caribbean region and provide insight into key environmental factors that can influence and foster the development of future World Champions and Olympians.

Australian Football League Injury Characteristics Differ Between Matches and Training: A Longitudinal Analysis of Changes in the Setting, Site, and Time Span From 1997 to 2016

Background:

Injury surveillance has been used to quantify the scope of the injury burden in Australian football. However, deeper statistical analyses are required to identify major factors that contribute to the injury risk and to understand how these injury patterns change over time.

Purpose:

To compare Australian Football League (AFL) injury incidence, severity, prevalence, and recurrence by setting, site, and time span from 1997 to 2016.

Study Design:

Descriptive epidemiology study.

Methods:

A total of 15,911 injuries and medical illnesses recorded by team medical staff at each club were obtained from the AFL’s injury surveillance system and analyzed using linear mixed models with 3 fixed effects (setting, time span, site) and 1 random effect (club). All types of injuries and medical illnesses were included for analysis, provided that they caused the player to miss at least 1 match during the regular season or finals. Five-season time spans (1997-2001, 2002-2006, 2007-2011, and 2012-2016) were used for comparisons. Incidence rates were expressed at the player level. Recurrences were recoded to quantify recurrent injuries across multiple seasons.

Results:

Compared with training injuries, match injuries had a 2.8 times higher incidence per season per club per player (matches: 0.070 ± 0.093; training: 0.025 ± 0.043; P < .001). Match injuries resulted in 1.9 times more missed matches per club per season (matches: 17.2 ± 17.0; training: 9.1 ± 10.5; P < .001). and were more likely to be recurrences (matches: 11.6% ± 20.0%; training: 8.6% ± 21.8%; P < .001). From the 1997-2001 to 2007-2011 time spans, overall injury severity increased from a mean of 3.2 to 3.7 missed matches (P ≤ .01). For the most recent 2012-2016 time span, injuries resulted in 3.6 missed matches, on average. Hip/groin/thigh injuries had the highest incidence (0.125 ± 0.120) and prevalence (19.2 ± 16.4) rates, and recurrences (29.3% ± 27.9%) were 15% more likely at this site than any other injury site.

Conclusion:

The risks of match injuries are significantly higher than those of training injuries in the AFL. Compared with the 1997-2001 time span, injuries became more severe during the 2007-2011 time span.

Training and Competition Activity Profiles of Australian Football Field Umpires

Jessiman, SW, Harvey, B, Corrigan, SL, and Gastin, PB. Training and competition activity profiles of Australian football field umpires. J Strength Cond Res 34(10): 2956-2964, 2020-The purpose of this study was to determine the activity profiles of Australian football (AF) field umpires during training and competition, and subsequently assess the specificity to competition of locomotor training sessions. Microtechnology incorporating a 5-Hz (interpolated to 15 Hz) global positioning system sensor tracked the movements of 24 field umpires during matches at the Melbourne Cricket Ground and fitness and skill-based training sessions before competition. Paired t-tests or Wilcoxon signed-rank tests determined whether significant differences existed between single training session and competition paired samples, with Cohen's d effect size and percent differences describing the magnitude of the training-competition differences. Absolute measures of total (d = 5.4; percent difference = 85.8%) and high-speed distance (>14.4 km·h) (1.0; 36.9%), as well as accelerations (3.3; 106.3%) and decelerations (3.2; 107.5%) were significantly greater during competition compared with training (p < 0.001). When standardized for time, high-speed distance (1.4; 52.0%), sprint distance (>23.0 km·h) (0.9; 121.5%), sprint efforts (1.0; 107.4%), and high acceleration (1.1; 114.3%) and deceleration (0.6; 66.7%) events (≥3 m·s) were greater during training (p < 0.001). No difference between training and competition was observed for relative distance. A single training session did not match the volume of work during competition, due primarily to large differences in duration. By contrast, training sessions were higher in intensity, likely to compensate for the shorter duration of training. Further research is required to determine whether the total weekly training load is sufficient to maintain and develop the competition-specific fitness of AF field umpires.

Inertial Sensors are a Valid Tool to Detect and Consistently Quantify Jumping

Considering the large and repetitive loads associated with jumping in team sports, automatic detection and quantification of jumping may show promise in reducing injury risks. The aim of this study was to validate commercially available inertial-movement analysis software to detect and quantify jumping in team sports. In addition, the test-retest reliability of the software to quantify jumping was assessed. Seventy-six healthy male participants completed a team sport circuit six times containing seven common movements (including three countermovement and two single-leg jumps) whilst wearing an inertial sensor (Catapult Sports, Australia). Jump detection accuracy was assessed by comparing the known number of jumps to the number recorded by the inertial movement analysis software. A further 27 participants separately performed countermovement and single-leg jumps at 33%, 66% and 100% of maximal jump height over two sessions. Jump height quantification accuracy was assessed by comparing criterion three-dimensional motion analysis-derived heights to that recorded by the inertial movement analysis software. Test-retest reliability was assessed by comparing recorded jump heights between both testing sessions. Catapult's inertial movement analysis software displayed excellent jump detection accuracy (96.9%) and test-retest jump height quantification reliability (ICC: 0.86 [countermovement jump], 0.88 [single-leg jump]). However, significant mean bias (-2.74 cm [95% LoA -10.44 - 4.96]) was observed for jump height quantification. Overall, Catapult's inertial movement analysis software appears to be a suitable method of automatically detecting jumping in team sports, and although reliable, caution is advised when using the IMA software to quantify jump height.

The influence of match characteristics and experience on decision-making performance in AFL umpires

OBJECTIVES

The purpose of this study was to investigate the effects of match characteristics and elite level umpiring experience on the decision-making performance of umpires in the Australian Football League (AFL).

DESIGN

Cross Sectional Study.

METHODS

All decisions from the 2014 AFL home and away season made by 32 male AFL field umpires (age 33.1±5.0years, AFL umpire experience 122±105 matches) were classified by a panel of four expert umpire coaches into correct, missed and unwarranted categories. The 8001 decisions were then further categorised based on the match time, score differential, field location, home ground advantage, match attendance and elite level umpiring experience. Chi-square with standardised residuals and two-way analysis of variance were used to analyse the data.

RESULTS

Higher elite level umpiring experience and a larger score differential at the time of the decision resulted in improved decision-making accuracy. Home ground advantage, attendance and match time did not influence the decision-making performance of umpires. Impact averse decisions occurred in the back line of play, with umpires tending to be conservative with decisions that may impact the score.

CONCLUSIONS

Decisions that have an increased influence on an umpire's decision-making performance include score differential and elite umpiring experience. Implications on umpiring performance regarding the venue, attendance and the duration of a match were not apparent.

Elite Junior Australian Football Players Experience Significantly Different Loads Across Levels of Competition and Training Modes

Lathlean, TJH, Gastin, PB, Newstead, S, and Finch, CF. Elite junior Australian football players experience significantly different loads across levels of competition and training modes. J Strength Cond Res 32(7): 2031-2038, 2018-Well-developed physical qualities such as high jumping ability, running endurance, acceleration, and speed can help aspiring junior elite Australian football (AF) players transition to the Australian Football League competition. To do so, players need to experience sufficient load to enhance their physical resilience without increasing their risk of negative outcomes in terms of impaired wellness or injury. The aim of this study was to investigate the differences in load for different levels of competition and training modes across one competitive season. Elite junior AF players (n = 562, aged 17.7 ± 0.3, range: 16-18 years) were recruited from 9 teams across the under-18 state league competition in Victoria. All players recorded their training and match intensities according to the session rating of perceived exertion method. Training sessions were categorized according to skills, strength, conditioning, and other activities, whereas matches were identified according to level of competition. The loads in U18 state league matches (656.7 ± 210.9 au) were significantly higher (p = 0.027) than those in school matches (643.3 ± 260.9 au) and those in U18 representative matches (617.2 ± 175.4). Players, who undertook more than one match per week, experienced significantly less load in subsequent matches (p < 0.001). Furthermore, U18 state league training sessions carried the most load when compared with other training modes. This article highlights that different combinations of training and match involvement affect overall player load, which may predispose players to negative outcomes such as impaired wellness or increased injury risk.

Development of a golf-specific load monitoring tool: Content validity and feasibility

Athletes often record details of their training and competitions, supported by information such as environmental conditions, travel, as well as how they felt. However, it is not known how prevalent these practices are in golfers, or how valuable this process is perceived. The purpose of this study was to develop a golf-specific load monitoring tool (GLMT), and establish the content validity and feasibility of this tool amongst high-level golfers. In the first phase of development, 21 experts were surveyed to determine the suitability of items for inclusion in the GLMT. Of the 36 items, 21 received >78% agreement, a requirement to establish content validity and for inclusion in the GLMT. Total duration was the preferred metric for golf-specific activities, whilst rating of perceived exertion (RPE) was preferred for measuring physical training. In the second phase, feasibility of the tool was assessed by surveying 13 high-level male golfers following 28-days of daily GLMT use. All items included in the GLMT were deemed feasible to record, with all players participating in the feasibility study providing high to very high ratings. Golfers responded that they would consider using a load monitoring tool of this nature long term, provided it can be completed in less than five minutes per day.

Validity of the ActiGraph GT3X+ and BodyMedia SenseWear Armband to estimate energy expenditure during physical activity and sport

OBJECTIVES

The purpose of this study was to assess the validity of the ActiGraph GT3X+ (GT3X+) and the BodyMedia SenseWear Armband (SWA) to estimate energy expenditure (EE) during physical activity and field sport movements.

DESIGN

Criterion validity.

METHODS

Twenty-six active adults completed a single 90min session involving alternating intervals of exercise (5min) and recovery (10min). Exercise involved walking (4km/h), jogging (8km/h), running (12km/h) or a sport-simulated circuit (three intervals). Participants wore two triaxial accelerometers (GT3X+ and SWA) and a portable gas analyser (MetaMax 3B), used as the criterion measure.

RESULTS

Total EE was significantly underestimated (p<0.01) by the GT3X+ (mean bias±SD: -374.5±132.84kJ; % difference=-29.3%) and SWA (-244.3±148.0kJ; -18.2%). Overestimations were made by both accelerometers during the walk (GT3X+: 27.4±30.8kJ; SWA: 32.1±15.4kJ) and jog (38.0±30.0kJ; 34.5±31.6kJ). Underestimations were evident during the run (-41.2±25.1kJ; -43.8±33.5kJ) and circuit (C1: GTX+: -127.2±41.6kJ; SWA: -86.1±40.2kJ). Error of estimation increased in magnitude as the intensity of exercise increased (GT3X+: 40.8-143.0kJ; SWA: 35.5-102.0kJ).

CONCLUSIONS

The ActiGraph GT3X+ and BodyMedia SWA do not provide valid EE estimates across a range of exercise modalities and intensities when compared to a criterion measure. Poor accuracy and large precision errors, particularly during high intensity and intermittent movement patterns, suggest these devices have limitations and should be used cautiously in the field.

Athlete Self-Report Measure Use and Associated Psychological Alterations

The experience of athletes and practitioners has led to the suggestion that use of an athlete self-report measure (ASRM) may increase an athlete's self-awareness, satisfaction, motivation, and confidence. This study sought to provide empirical evidence for this assertion by evaluating psychological alterations associated with ASRM use across a diverse athlete population. Athletes (n = 335) had access to an ASRM for 16 weeks and completed an online survey at baseline, and weeks 4, 8, and 16. Generalized estimating equations were used to evaluate the associations between ASRM compliance and outcome measures. Compared to baseline, confidence and extrinsic motivation were most likely increased at weeks 4, 8, and 16. Satisfaction and intrinsic motivation were most likely decreased at week 4, but no different to baseline values at weeks 8 and 16. Novice athletes and those who were instructed to use an ASRM (rather than using one autonomously) were less responsive to ASRM use. This study provides preliminary evidence for ASRM to prompt initial dissatisfaction and decreased intrinsic motivation which, along with increased confidence and extrinsic motivation, may provide the necessary stimulus to improve performance-related behaviors. Novice and less autonomous athletes may benefit from support to develop motivation, knowledge, and skills to use the information gleaned from an ASRM effectively.

Rule modification in junior sport: Does it create differences in player movement?

OBJECTIVES

To determine the effects of rule modification on player movement during matchplay in junior Australian football (AF).

DESIGN

Quasi-experimental study design.

METHODS

Time-motion analysis was used to record variables pertaining to player movement including total distance covered, high-speed running (HSR) distance (>14.4km/h) and HSR efforts. GPS data obtained from 145 players (7-12 years) were analysed across four junior AF leagues and three age group combinations (U8/U9, U9/U10 and U11/U12). The four leagues were collapsed into two separate conditions (compliant and non-compliant) based on their adherence to a modified junior sport policy. To control for the influence of age and physical maturity, a secondary analysis was performed on an adequately matched U8 subset of data (n=48).

RESULTS

Significant differences (p<0.05) were found between compliant and non-compliant leagues for age and all player movement variables, with participants in the compliant leagues achieving less player movement. Significant differences were also evident between conditions in the U8 subset in total and relative distance and HSR efforts, with moderate to very large differences (29-60%) observed for all player movement variables.

CONCLUSIONS

Rule modifications limits the extent and intensity of player movement in junior AF compared to standard playing conditions. The unintended effect of reduced physical activity with rule modifications should be compensated for with additional activities wherever possible. League administrators and policy makers should consider the objectives of rule modifications and weigh up both positive and negative outcomes.

Match running performance and skill execution improves with age but not the number of disposals in young Australian footballers

This study investigated age-related differences in maturity, physical and functional characteristics and playing performance in youth Australian Football (AF). Young male players (n = 156) were recruited from 12 teams across 6 age groups (U10-U15) of a recreational AF club. All players were tested for body size, maturity and fitness. Player performance was assessed during a match in which disposals (kicks and handballs) and their effectiveness were coded from a video recording and match running performance measured using Global Positioning System. Significant main effects (P < 0.01) for age group were observed for age, years to peak height velocity, body mass, height, 20 m sprint, maximal speed over 20 m, vertical jump, 20 m multistage shuttle run, match distance, high-speed running distance, peak speed, number of effective disposals and percentage of effective disposals. Age-related differences in fitness characteristics (speed, lower body power and endurance) appeared to transfer to match running performance. The frequency in which players disposed of the football did not differ between age groups, however the effectiveness of each disposal (i.e., % effective disposals) improved with age. Match statistics, particularly those that evaluate skill execution outcome (i.e., effectiveness), are useful to assess performance and to track player development over time. Differences between age groups, and probably variability within age groups, are strongly associated with chronological age and maturity.

Utility of the multi-component training distress scale to monitor swimmers during periods of training overload

The purpose of the present study was to determine the efficacy of the multi-component training distress scale (MTDS), in monitoring swimmers prior to national competition. Twenty-one national-level adolescent swimmers completed eight weeks of testing. Once a week participants completed an 8 × 50 m sprint test, vertical jump test, sit-and-reach test, the MTDS and the Recovery-Stress Questionnaire for Athletes (REST-Q). All testing was incorporated into the swimmers' normal training programme. The REST-Q accounted for the following variances in performance: flexibility (14.6%, p = 0.009), power output (17.7%, p = 0.003), swimming speed (15.5%, p = 0.006) and swimming endurance (17.5%, p = 0.002). In comparison, the MTDS accounted for the following variances in performance: flexibility (12.1%, p = 0.095), power output (16.4%, p = 0.023), swimming speed (20.5%, p = 0.003) and swimming speed endurance (23.8%, p = 0.001). The findings of the current study suggest that both the REST-Q Sport and the MTDS have the capacity to predict performance on a range of fitness components associated with swimming.

Short Duration Heat Acclimation in Australian Football Players

This study examined if five sessions of short duration (27 min), high intensity, interval training (HIIT) in the heat over a nine day period would induce heat acclimation in Australian football (AF) players. Fourteen professional AF players were matched for VO2peak (mL·kg(-1)·min(-1)) and randomly allocated into either a heat acclimation (Acc) (n = 7) or Control (Con) group (n = 7). The Acc completed five cycle ergometer HIIT sessions within a nine day period on a cycle ergometer in the heat (38.7 ± 0.5 °C; 34.4 ± 1.3 % RH), whereas Con trained in thermo-neutral conditions (22.3 ± 0.2 °C; 35.8 ± 0. % RH). Four days prior and two days post HIIT participants undertook a 30 min constant load cycling test at 60% V̇O2peak in the heat (37.9 ± 0.1 °C; 28.5 ± 0.7 % RH) during which VO2, blood lactate concentration ([Lac(-)]), heart rate (HR), rating of perceived exertion (RPE), thermal comfort, core and skin temperatures were measured. Heat acclimation resulted in reduced RPE, thermal comfort and [Lac(-)] (all p < 0.05) during the submaximal exercise test in the heat. Heart rate was lower (p = 0.007) after HIIT, in both groups. Heat acclimation did not influence any other measured variables. In conclusion, five short duration HIIT sessions in hot dry conditions induced limited heat acclimation responses in AF players during the in-season competition phase. In practice, the heat acclimation protocol can be implemented in a professional team environment; however the physiological adaptations resulting from such a protocol were limited. Key pointsSome minor heat acclimation adaptations can be induced in professional AF players with five 27 min non-consecutive, short duration HIIT sessions in the heat.The heat acclimation protocol employed in this study was able to be implemented in a professional team sport environment during an actual competitive season.Elevating and maintaining a high core temperature sufficient for heat acclimation likely requires a longer heat training session or some pre-heating prior to exercise.

Impact of Sport Context and Support on the Use of a Self-Report Measure for Athlete Monitoring

Athlete self-report measures (ASRM) are a popular method of athlete monitoring in high-performance sports. With increasing recognition and accessibility, ASRM may potentially be utilized by athletes from diverse sport contexts. The purpose of the present study was to improve understanding of ASRM implementation across different sport contexts by observing uptake and compliance of a newly implemented ASRM over 16 weeks, and investigating the perceived roles and factors influencing implementation. Athletes (n=131) completed an electronic survey at baseline and week 16 on their perceptions and experiences with ASRM implementation respectively. Despite initial interest, only 70 athletes attempted to use the ASRM. Of these athletes, team sport athletes who were supported by their coach or sports program to use the ASRM were most compliant (p < 0.001) with a mean compliance of 84 ± 21 %. Compliance for self-directed individual and team sport athletes was 28 ± 40 % and 8 ± 18 % respectively. Self-directed athletes were motivated to monitor themselves, and rated desired content and minimal burden as key factors for initial and ongoing compliance. Supported athletes were primarily motivated to comply for the benefit of their coach or sports program rather than themselves, however rated data output as a key factor for their continued use. Factors of the measure outweighed those of the social environment regardless of sport context, however the influence of social environmental factors should not be discounted. The findings of the present study demonstrate the impact of sport context on the implementation of an ASRM and the need to tailor implementation strategies accordingly. Key pointsAthletes perceive ASRM and the factors influencing implementation differently. Therefore, to encourage compliance, it is important to tailor implementation strategies to the athlete and their sport context to increase appeal and minimize unappealing factors.Athletes using an ASRM on their own accord typically favor a measure which meets their needs and interests, with minimal burden.Athletes using an ASRM under the direction and support of their coach or sports program typically favor feedback and a positive social environment.

Classification of team sport activities using a single wearable tracking device

Wearable tracking devices incorporating accelerometers and gyroscopes are increasingly being used for activity analysis in sports. However, minimal research exists relating to their ability to classify common activities. The purpose of this study was to determine whether data obtained from a single wearable tracking device can be used to classify team sport-related activities. Seventy-six non-elite sporting participants were tested during a simulated team sport circuit (involving stationary, walking, jogging, running, changing direction, counter-movement jumping, jumping for distance and tackling activities) in a laboratory setting. A MinimaxX S4 wearable tracking device was worn below the neck, in-line and dorsal to the first to fifth thoracic vertebrae of the spine, with tri-axial accelerometer and gyroscope data collected at 100Hz. Multiple time domain, frequency domain and custom features were extracted from each sensor using 0.5, 1.0, and 1.5s movement capture durations. Features were further screened using a combination of ANOVA and Lasso methods. Relevant features were used to classify the eight activities performed using the Random Forest (RF), Support Vector Machine (SVM) and Logistic Model Tree (LMT) algorithms. The LMT (79-92% classification accuracy) outperformed RF (32-43%) and SVM algorithms (27-40%), obtaining strongest performance using the full model (accelerometer and gyroscope inputs). Processing time can be reduced through feature selection methods (range 1.5-30.2%), however a trade-off exists between classification accuracy and processing time. Movement capture duration also had little impact on classification accuracy or processing time. In sporting scenarios where wearable tracking devices are employed, it is both possible and feasible to accurately classify team sport-related activities.

Classification of team sport activities using a single wearable tracking device

Wearable tracking devices incorporating accelerometers and gyroscopes are increasingly being used for activity analysis in sports. However, minimal research exists relating to their ability to classify common activities. The purpose of this study was to determine whether data obtained from a single wearable tracking device can be used to classify team sport-related activities. Seventy-six non-elite sporting participants were tested during a simulated team sport circuit (involving stationary, walking, jogging, running, changing direction, counter-movement jumping, jumping for distance and tackling activities) in a laboratory setting. A MinimaxX S4 wearable tracking device was worn below the neck, in-line and dorsal to the first to fifth thoracic vertebrae of the spine, with tri-axial accelerometer and gyroscope data collected at 100Hz. Multiple time domain, frequency domain and custom features were extracted from each sensor using 0.5, 1.0, and 1.5s movement capture durations. Features were further screened using a combination of ANOVA and Lasso methods. Relevant features were used to classify the eight activities performed using the Random Forest (RF), Support Vector Machine (SVM) and Logistic Model Tree (LMT) algorithms. The LMT (79-92% classification accuracy) outperformed RF (32-43%) and SVM algorithms (27-40%), obtaining strongest performance using the full model (accelerometer and gyroscope inputs). Processing time can be reduced through feature selection methods (range 1.5-30.2%), however a trade-off exists between classification accuracy and processing time. Movement capture duration also had little impact on classification accuracy or processing time. In sporting scenarios where wearable tracking devices are employed, it is both possible and feasible to accurately classify team sport-related activities.

Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review

Background

Monitoring athlete well-being is essential to guide training and to detect any progression towards negative health outcomes and associated poor performance. Objective (performance, physiological, biochemical) and subjective measures are all options for athlete monitoring.

Objective

We systematically reviewed objective and subjective measures of athlete well-being. Objective measures, including those taken at rest (eg, blood markers, heart rate) and during exercise (eg, oxygen consumption, heart rate response), were compared against subjective measures (eg, mood, perceived stress). All measures were also evaluated for their response to acute and chronic training load.

Methods

The databases Academic search complete, MEDLINE, PsycINFO, SPORTDiscus and PubMed were searched in May 2014. Fifty-six original studies reported concurrent subjective and objective measures of athlete well-being. The quality and strength of findings of each study were evaluated to determine overall levels of evidence.

Results

Subjective and objective measures of athlete well-being generally did not correlate. Subjective measures reflected acute and chronic training loads with superior sensitivity and consistency than objective measures. Subjective well-being was typically impaired with an acute increase in training load, and also with chronic training, while an acute decrease in training load improved subjective well-being.

Summary

This review provides further support for practitioners to use subjective measures to monitor changes in athlete well-being in response to training. Subjective measures may stand alone, or be incorporated into a mixed methods approach to athlete monitoring, as is current practice in many sport settings.

Game and Training Load Differences in Elite Junior Australian Football

Game demands and training practices within team sports such as Australian football (AF) have changed considerably over recent decades, including the requirement of coaching staff to effectively control, manipulate and monitor training and competition loads. The purpose of this investigation was to assess the differences in external and internal physical load measures between game and training in elite junior AF. Twenty five male, adolescent players (mean ±SD: age 17.6 ± 0.5 y) recruited from three elite under 18 AF clubs participated. Global positioning system (GPS), heart rate (HR) and rating of perceived exertion (RPE) data were obtained from 32 game files during four games, and 84 training files during 19 training sessions. Matched-pairs statistics along with Cohen's d effect size and percent difference were used to compare game and training events. Players were exposed to a higher physical load in the game environment, for both external (GPS) and internal (HR, Session-RPE) load parameters, compared to in-season training. Session time (d = 1.23; percent difference = 31.4% (95% confidence intervals = 17.4 - 45.4)), total distance (3.5; 63.5% (17.4 - 45.4)), distance per minute (1.93; 33.0% (25.8 - 40.1)), high speed distance (2.24; 77.3% (60.3 - 94.2)), number of sprints (0.94; 43.6% (18.9 - 68.6)), mean HR (1.83; 14.3% (10.5 - 18.1)), minutes spent above 80% of predicted HRmax (2.65; 103.7% (89.9 - 117.6)) and Session-RPE (1.22; 48.1% (22.1 - 74.1)) were all higher in competition compared to training. While training should not be expected to fully replicate competition, the observed differences suggest that monitoring of physical load in both environments is warranted to allow comparisons and evaluate whether training objectives are being met. Key pointsPhysical loads, including intensity, are typically lower in training compared to competition in junior elite Australian football.Monitoring of player loads in team sports should include both internal and external measures.Selected training drills should look to replicate game intensities, however training is unlikely to match the overall physical demands of competition.

Validation of a Trunk-mounted Accelerometer to Measure Peak Impacts during Team Sport Movements

This study assessed the validity of an accelerometer to measure impacts in team sports. 76 participants completed a team sport circuit. Accelerations were collected concurrently at 100 Hz using an accelerometer and a 36-camera motion analysis system. The largest peak accelerations per movement were compared in 2 ways: i) pooled together and filtered at 13 different cut-off frequencies (range 6-25 Hz) to identify the optimal filtering frequency, and ii) the optimal cut-off frequency split into the 7 movements performed (n=532). Raw and 25-16 Hz filtering frequencies significantly overestimated and 6 Hz underestimated motion analysis peak accelerations (P <0.007). The 12 Hz filtered accelerometer data revealed the strongest relationship with motion analysis data (accuracy - 0.01±0.27 g, effect size - 0.01, agreement - 0.55 to 0.53 g, precision 0.27 g, and relative error 5.5%; P=1.00). The accelerometer underestimated peak accelerations during tackling and jumping, and overestimated during walking, jogging, sprinting and change of direction. Lower agreement and reduced precision were associated with sprinting, jumping and tackling. The accelerometer demonstrated an acceptable level of concurrent validity compared to a motion analysis system when filtered at a cut-off frequency of 12 Hz. The results advocate the use of accelerometers to measure movements in team sport.

Monitoring athletes through self-report: factors influencing implementation

Monitoring athletic preparation facilitates the evaluation and adjustment of practices to optimize performance outcomes. Self-report measures such as questionnaires and diaries are suggested to be a simple and cost-effective approach to monitoring an athlete's response to training, however their efficacy is dependent on how they are implemented and used. This study sought to identify the perceived factors influencing the implementation of athlete self-report measures (ASRM) in elite sport settings. Semi-structured interviews were conducted with athletes, coaches and sports science and medicine staff at a national sporting institute (n = 30). Interviewees represented 20 different sports programs and had varying experience with ASRM. Purported factors influencing the implementation of ASRM related to the measure itself (e.g., accessibility, timing of completion), and the social environment (e.g., buy-in, reinforcement). Social environmental factors included individual, inter-personal and organizational levels which is consistent with a social ecological framework. An adaptation of this framework was combined with the factors associated with the measure to illustrate the inter-relations and influence upon compliance, data accuracy and athletic outcomes. To improve implementation of ASRM and ultimately athletic outcomes, a multi-factorial and multi-level approach is needed. Key pointsEffective implementation of a self-report measure for monitoring athletes requires a multi-factorial and multi-level approach which addresses the particular measure used and the surrounding social environment.A well-designed self-report measure should obtain quality data with minimal burden on athletes and staff.A supportive social environment involves buy-in and coordination of all parties, at both an individual and organization level.

Development and implementation of a novel measure for quantifying training loads in rowing: the T2minute method

The systematic management of training requires accurate training load measurement. However, quantifying the training of elite Australian rowers is challenging because of (a) the multicenter, multistate structure of the national program; (b) the variety of training undertaken; and (c) the limitations of existing methods for quantifying the loads accumulated from varied training formats. Therefore, the purpose of this project was to develop a new measure for quantifying training loads in rowing (the T2minute method). Sport scientists and senior coaches at the National Rowing Center of Excellence collaborated to develop the measure, which incorporates training duration, intensity, and mode to quantify a single index of training load. To account for training at different intensities, the method uses standardized intensity zones (T zones) established at the Australian Institute of Sport. Each zone was assigned a weighting factor according to the curvilinear relationship between power output and blood lactate response. Each training mode was assigned a weighting factor based on whether coaches perceived it to be "harder" or "easier" than on-water rowing. A common measurement unit, the T2minute, was defined to normalize sessions in different modes to a single index of load; one T2minute is equivalent to 1 minute of on-water single scull rowing at T2 intensity (approximately 60-72% VO2max). The T2minute method was successfully implemented to support national training strategies in Australian high performance rowing. By incorporating duration, intensity, and mode, the T2minute method extends the concepts that underpin current load measures, providing 1 consistent system to quantify loads from varied training formats.

Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running

The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging.

Convergent validity of a novel method for quantifying rowing training loads

Elite rowers complete rowing-specific and non-specific training, incorporating continuous and interval-like efforts spanning the intensity spectrum. However, established training load measures are unsuitable for use in some modes and intensities. Consequently, a new measure known as the T2minute method was created. The method quantifies load as the time spent in a range of training zones (time-in-zone), multiplied by intensity- and mode-specific weighting factors that scale the relative stress of different intensities and modes to the demands of on-water rowing. The purpose of this study was to examine the convergent validity of the T2minute method with Banister's training impulse (TRIMP), Lucia's TRIMP and Session-RPE when quantifying elite rowing training. Fourteen elite rowers (12 males, 2 females) were monitored during four weeks of routine training. Unadjusted T2minute loads (using coaches' estimates of time-in-zone) demonstrated moderate-to-strong correlations with Banister's TRIMP, Lucia's TRIMP and Session-RPE (rho: 0.58, 0.55 and 0.42, respectively). Adjusting T2minute loads by using actual time-in-zone data resulted in stronger correlations between the T2minute method and Banister's TRIMP and Lucia's TRIMP (rho: 0.85 and 0.81, respectively). The T2minute method is an appropriate in-field measure of elite rowing training loads, particularly when actual time-in-zone values are used to quantify load.