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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

Concurrent validity and reliability of torso-worn inertial measurement unit for jump power and height estimation.

The purpose of the present study was to evaluate the concurrent validity and test-retest repeatability of torso-worn IMU-derived power and jump height in a counter-movement jump test. Twenty-seven healthy recreationally active males (age, 21.9 [SD 2.0] y, height, 1.76 [0.7] m, mass, 73.7 [10.3] kg) wore an IMU and completed three counter-movement jumps a week apart. A force platform and a 3D motion analysis system were used to concurrently measure the jumps and subsequently derive power and jump height (based on take-off velocity and flight time). The IMU significantly overestimated power (mean difference = 7.3 W/kg; P < 0.001) compared to force-platform-derived power but good correspondence between methods was observed (Intra-class correlation coefficient [ICC] = 0.69). IMU-derived power exhibited good reliability (ICC = 0.67). Velocity-derived jump heights exhibited poorer concurrent validity (ICC = 0.72 to 0.78) and repeatability (ICC = 0.68) than flight-time-derived jump heights, which exhibited excellent validity (ICC = 0.93 to 0.96) and reliability (ICC = 0.91). Since jump height and power are closely related, and flight-time-derived jump height exhibits excellent concurrent validity and reliability, flight-time-derived jump height could provide a more desirable measure compared to power when assessing athletic performance in a counter-movement jump with IMUs.

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.

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.

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.

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.

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.

Role of a self-report measure in athlete preparation.

Athlete self-report measures (ASRM) are a common and cost-effective method of athlete monitoring. It is purported that ASRM be used to detect athletes at risk of overtraining, injury, or illness, allowing intervention through training modification. However, it is not known whether ASRM are actually being used for or are achieving these objectives in the applied sport setting. Therefore, the aim of this study was to better understand how ASRM are being used in elite sports and their role in athletic preparation. Semistructured interviews were conducted one-on-one with athletes, coaches, and sports science and medicine staff (n = 30) at a national sporting institute. Interview recordings were transcribed and analyzed for emergent themes. Twelve day-to-day and 7 longer-term practices were identified which contributed to a 4-step process of ASRM use (record data, review data, contextualize, and act). In addition to the purported uses, ASRM facilitated information disclosure and communication among athletes and staff and between staff, and improved the understanding and management of athlete preparation. These roles of ASRM are best achieved through engagement of athletes, coaches, and support staff in the systematic cyclic process.