Search

The purpose of this research was to compare the hip adduction and abduction relative strength, adduction-to-abduction strength ratio (ADD:ABD), and interlimb asymmetries of ice hockey athletes between the typically used bilateral position and 3 unilateral positions in joint-specific angles (0°, 25°, and 50° of hip abduction) relevant to an ice hockey stride. A secondary purpose was to explore any relationships between these measures and hip and groin noncontact injuries, and self-reported pain and disability. Twenty-five semiprofessional male ice hockey athletes (26.7 ± 6.7 years) were assessed for hip abduction range of motion (ROM), hip adduction and abduction relative strength, and completed the Copenhagen Hip and Groin Outcome Score (HAGOS) questionnaire. Within-subjects repeated-measures analysis of variance revealed a significant effect for the assessment position for adduction (F1,24 = 52.4, p < 0.01) and abduction relative strength (F1,24 = 152.1, p < 0.01), ADD:ABD (F1,24 = 38.9, p < 0.01), and the interlimb asymmetries for each of these variables (F1,24 = 9.8-12.3; p < 0.01), with large strength differences observed between the bilateral assessment and all unilateral assessment positions for adduction and abduction relative strength. In addition, 4 athletes experienced a noncontact hip or groin injury within 1 month after testing, and when compared with the rest of the cohort (n = 21) with Welch's t-tests, demonstrated significantly reduced hip abduction ROM (mean difference [MD] = -8.4 ± 2.5°; p < 0.01), sport subscale score for the HAGOS questionnaire (MD = -33.9 ± 7.1; p < 0.01), and a decline in hip adduction relative strength in the unilateral position of 50° compared with the position of 25° hip abduction (MD = -13.4 ± 3.8; p = 0.04). These results suggest that practitioners working with ice hockey athletes may benefit from profiling hip strength in these unilateral joint-specific angle positions because they provide an evidence base to determine the hip strength needs of ice hockey athletes in positions associated with skating performance and noncontact hip and groin injury mechanisms (between 25° and 50° of hip abduction). [ABSTRACT FROM AUTHOR]

Temporal changes in the total running demands of professional football competition have been well documented, with absolute running demands decreasing in the second half. However, it is unclear whether the peak match running demands demonstrate a similar decline. A total of 508 GPS files were collected from 44 players, across 68 matches of the Australian A-League. GPS files were split into the 1st and 2nd half, with the peak running demands of each half quantified across 10 moving average durations (1-10 min) for three measures of running performance (total distance, high-speed distance [> 19.8 km ⋅ h-1] and average acceleration). Players were categorised based on positional groups: attacking midfielder (AM), central defender (CD), defensive midfielder (DM), striker (STR), wide defender (WD) and winger (WNG). Linear mixed models and effect sizes were used to identify differences between positional groups and halves. Peak running demands were lower in the second half for STR across all three reported metrics (ES = 0.60--0.84), with peak average acceleration lower in the second half for DM, WD and WNG (ES = 0.60--0.70). Irrespective of match half, AM covered greater peak total distances than CD, STR, WD and WIN (ES = 0.60--2.08). Peak high-speed distances were greater across both halves for WIN than CD, DM and STR (ES = 0.78--1.61). Finally, STR had lower peak average acceleration than all positional groups across both halves (ES = 0.60--1.12). These results may help evaluate implemented strategies that attempt to mitigate reductions in second half running performance and inform position specific training practices. [ABSTRACT FROM AUTHOR]

In professional team sports, the collection and analysis of athlete-monitoring data are common practice, with the aim of assessing fatigue and subsequent adaptation responses, examining performance potential, and minimizing the risk of injury and/or illness. Athlete-monitoring systems should be underpinned by appropriate data analysis and interpretation, to enable the rapid reporting of simple and scientifically valid feedback. Using the correct scientific and statistical approaches can improve the confidence of decisions made from athlete-monitoring data. However, little research has discussed and proposed an outline of the process involved in the planning, development, analysis, and interpretation of athlete-monitoring systems. This review discusses a range of methods often employed to analyze athlete-monitoring data to facilitate and inform decision-making processes. There is a wide range of analytical methods and tools that practitioners may employ in athlete-monitoring systems, as well as several factors that should be considered when collecting these data, methods of determining meaningful changes, and various data-visualization approaches. Undeipinning a successful athlete-monitoring system is the ability of practitioners to communicate and present important information to coaches, ultimately resulting in enhanced athletic performance. [ABSTRACT FROM AUTHOR]

The peak match running demands of football (soccer) have been quantified across time durations of 1--10 min, however, little is known as to when the peak match running demands occur within match play. Data were collected from 44 elite footballers, across 68 fixtures (Files = 413, mean ± SD; 11 ± 8 observations per player, range; 1--33), with peak match running demands quantified for each playing half at ten incremental rolling average durations (1 min rolling averages, 2 min rolling averages, etc.). Data were assessed if players completed the full match. Three measures of running performance were assessed total distance (TD), highspeed distance (> 19.8 km · h-1) (HSD) and average acceleration (AveAcc)], with the in-game commencement time of the peak running demands recorded. Descriptive statistics and normality were calculated for each rolling average duration, with the self-containment of shorter rolling average epochs within longer epochs also assessed (e.g. Do the 1 min peak running demands occur within the 10 min peak running demands). Peak TD and AveAcc demands occurred early in each half (median time = 7--17 min and 6--16 min, respectively). Conversely, peak HSD covered was uniformly distributed (Skewness = 0--0.5, Kurtosis = 1.7--2.0). There were low-moderate levels of self-containment for each peak match running period (10--51%), dependent upon metric. Peak match running demands for TD and AveAcc occurred at similar stages of a match where TD and acceleration volumes are typically greatest, whereas peak HSD demands appeared more unpredictable. These timings may help inform training prescriptions in preparation of athletes for competition. [ABSTRACT FROM AUTHOR]

Peak match running intensities have recently been introduced to quantify the peak running demands of football competition, across incremental time intervals, to inform training practices. However, their between-match variation is yet to be comprehensively reported, limiting the ability to determine meaningful changes in peak match running intensities. The current study aimed to quantify the between-match variability in peak match running intensities across discrete moving average durations (1--10 min). GPS data were collected from 44 elite football players across 68 matches (mean ± SD; 13 ± 10 observations per player). For inclusion players must have completed 70mins of a match across a minimum of two matches. Performance metrics included total and high-speed (> 19.8 km ⋅ h-1) running distances and average acceleration (m ⋅ s-2), expressed relative to time. For each metric, the coefficient of variation and smallest worthwhile difference were calculated. The peak match running intensity data was similar to previously reported data from various football competitions. The between-match CV of relative total distance ranged between 6.8--7.3%, with the CV for average acceleration and relative high-speed running being 5.4--5.8% and 20.6--29.8%, respectively. The greater variability observed for relative high-speed running is likely reflective of the varying constraints and contextual factors that differ between matches. The reported between-match variability helps to provide context when interpreting match performance and prescribing training drills using peak match running intensity data. [ABSTRACT FROM AUTHOR]

Milne, EC, Vickery, WM, Dascombe, BJ, and Borges, NR. Development of a twenty20 field-based simulation for cricket fast bowlers (FBS-T20). J Strength Cond Res 36(10): 2905–2911, 2022—This project assessed the validity and reliability of a novel Twenty20 cricket pace bowling simulation (FBS-T20) that could be used to facilitate match-specific testing and training outside of match play. Six recreational pace bowlers completed 3 identical sessions of the FBS-T20. The FBS-T20 consisted of 4 bowling and 16 fielding overs. During the bowling overs, a bowling accuracy test and bowling approach speed were measured, whereas during the fielding overs, 10-m sprint performance was assessed. Distance covered, heart rate (HR), and rating of perceived exertion (RPE) were also collected throughout the FBS-T20. Validity was determined through comparison with previously reported Twenty20 pace bowling match demands, and intersession reliabilities were assessed. Distances covered in speed zones were valid (p > 0.05) with the exception of significantly lower jog values in the FBS-T20 (957–1,279 vs. 2,195 m; p = 0.04-<0.001). The maximal HR was found to be valid, but the mean HR was significantly higher than previously published data (147–151 bpm vs. 133 bpm; p = 0.014–0.003). Distances covered demonstrated high levels of reliability, with increasing reliability found after additional sessions (coefficient of variation [CV]% = 3.8–14.4). The HR (CV% = 4.8–6.3) and session RPE (CV% = 10.8) demonstrated moderate reliability, whereas approach speed, 10-m sprint, and bowling skills test results possessed low levels of reliability. The FBS-T20 is a practically viable testing and training tool that is valid and reliable for distances covered at high speeds. One full familiarization session is recommended for optimal reliability. [ABSTRACT FROM AUTHOR]

The purpose of this study was to compare double-handed backhand kinematics of the non-dominant wrist of tennis players using either an eastern or continental grip position with the non-dominant hand. Trajectory data were captured using sixty reflective markers on sixteen sub-elite right-handed tennis players using a 12-camera VICON motion capture system (250 Hz). Participants executed double-handed backhands using two non-dominant grip positions (Eastern [E] and Continental [C]), aiming for two crosscourt zones (Deep [D] and Short [S]), totalling to four conditions (ED, CD, ES and CS). Three successful attempts from each condition were selected for analysis. The eastern grip demonstrated faster horizontal racket head velocity compared to the continental grip. However, no differences were observed in accuracy or spin rate between grips (p > 0.05). In the non-dominant upper limb, elbow flexion was smaller in the continental condition throughout the swing, whilst wrist extension and ulnar deviation was larger. Collectively, these data suggest that the continental grip may place the wrist in a position vulnerable to overuse injury. Future research into the kinetics of the double-handed backhand would help better understand the onset of ulnar-side wrist pain in tennis. [ABSTRACT FROM AUTHOR]

Purpose: To compare relative and absolute speed and metabolic thresholds for quantifying match output in elite rugby league. Methods: Twenty-six professional players competing in the National Rugby League were monitored with global positioning systems (GPS) across a rugby-league season. Absolute speed (moderate-intensity running [MIRTh > 3.6 m/s] and high-intensity running [HIRTh > 5.2 m/s]) and metabolic (>20 W/kg) thresholds were compared with individualized ventilatory (first [VT1IFT] and second [VT2IFT]) thresholds estimated from the 30-15 Intermittent Fitness Test (30-15IFT), as well as the metabolic threshold associated with VT2IFT (HPmetVT2), to examine difference in match-play demands. Results: VT2IFT mean values represent 146%, 138%, 167%, and 144% increases in the HIR dose across adjustables, edge forwards, middle forwards, and outside backs, respectively. Distance covered above VT2IFT was almost certainly greater (ES range = 0.79-1.03) than absolute thresholds across all positions. Trivial to small differences were observed between VT1IFT and MIRTh, while small to moderate differences were reported between HPmetVT2 and HPmetTh. Conclusions: These results reveal that the speed at which players begin to run at higher intensities depends on individual capacities and attributes. As such, using absolute HIR speed thresholds underestimates the physical HIR load. Moreover, absolute MIR and high metabolic thresholds may over- or underestimate the work undertaken above these thresholds depending on the respective fitness of the individual. Therefore, using relative thresholds enables better prescription and monitoring of external training loads based on measured individual physical capacities. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the influence of daily and exponentially weighted moving training loads on subsequent nighttime sleep. Methods: Sleep of 14 professional rugby league athletes competing in the National Rugby League was recorded using wristwatch actigraphy. Physical demands were quantified using GPS technology, including total distance, high-speed distance, acceleration/ deceleration load (SumAccDec; AU), and session rating of perceived exertion (AU). Linear mixed models determined effects of acute (daily) and subacute (3- and 7-d) exponentially weighted moving averages (EWMA) on sleep. Results: Higher daily SumAccDec was associated with increased sleep efficiency (effect-size correlation; ES = 0.15; ±0.09) and sleep duration (ES = 0.12; ±0.09). Greater 3-d EWMA SumAccDec was associated with increased sleep efficiency (ES = 0.14; ±0.09) and an earlier bedtime (ES = 0.14; ±0.09). An increase in 7-d EWMA SumAccDec was associated with heightened sleep efficiency (ES = 0.15; ±0.09) and earlier bedtimes (ES = 0.15; ±0.09). Conclusions: The direction of the associations between training loads and sleep varied, but the strongest relationships showed that higher training loads increased various measures of sleep. Practitioners should be aware of the increased requirement for sleep during intensified training periods, using this information in the planning and implementation of training and individualized recovery modalities. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether preseason training plans for Australian football can be computer generated using current training-load guidelines to optimize injury-risk reduction and performance improvement. Methods: A constrained optimization problem was defined for daily total and sprint distance, using the preseason schedule of an elite Australian football team as a template. Maximizing total training volume and maximizing Banister-model-projected performance were both considered optimization objectives. Cumulative workload and acute:chronic workload-ratio constraints were placed on training programs to reflect current guidelines on relative and absolute training loads for injury-risk reduction. Optimization software was then used to generate preseason training plans. Results: The optimization framework was able to generate training plans that satisfied relative and absolute workload constraints. Increasing the off-season chronic training loads enabled the optimization algorithm to prescribe higher amounts of "safe" training and attain higher projected performance levels. Simulations showed that using a Banister-model objective led to plans that included a taper in training load prior to competition to minimize fatigue and maximize projected performance. In contrast, when the objective was to maximize total training volume, more frequent training was prescribed to accumulate as much load as possible. Conclusions: Feasible training plans that maximize projected performance and satisfy injury-risk constraints can be automatically generated by an optimization problem for Australian football. The optimization methods allow for individualized training-plan design and the ability to adapt to changing training objectives and different training-load metrics. [ABSTRACT FROM AUTHOR]

Tredrea, MSJ, Middleton, KJ, Bourne, MN, Carey, DL, Scanlan, AT, and Dascombe, BJ. Load centralization does not affect the kinetic and kinematic output of countermovement jumps. J Strength Cond Res 36(4): 1084-1089, 2022-This study aimed to compare the kinetics, kinematics, and performance of countermovement jumps (CMJs) when completed with 2 different loading conditions (centralized or peripheral) across increasing loads. Seventeen subjects (12 men and 5 women) randomly completed 2 series of CMJs with increasing loads separated by a 30-minute rest period between conditions. Subjects were loaded with either a weighted vest (centralized) or straight barbell (peripheral). A randomized, counterbalanced crossover design was used with incremental loads of 10, 20, 30, 40, and 50% of body mass added to the vest or barbell. Measures of peak force, acceleration, velocity, and power were calculated across each subphase of the CMJs. No significant differences were observed in kinetic or kinematic variables between loading conditions. Within each condition there were significant reductions (p < 0.05) in peak concentric velocity and acceleration, as well as significant increases (p < 0.05) in peak force when the external load increased. Furthermore, braking and propulsive phase duration significantly increased (p < 0.05) and jump height significantly decreased (p < 0.05) as the external load increased. Countermovement jump performance was similar in both central and peripheral loading, whereas increasing load significantly affected jump height, force, velocity, and acceleration variables irrespective of load position. The training stimulus from an external load placed centrally or peripherally is similar regardless of where it is positioned; however, from a practical perspective, a weighted vest may provide a more mobile and safer alternative than a barbell. [ABSTRACT FROM AUTHOR]

Purpose: To quantify the duration and position-specific peak running intensities of international rugby union for the prescription and monitoring of specific training methodologies. Methods: Global positioning systems (GPS) were used to assess the activity profile of 67 elite-level rugby union players from 2 nations across 33 international matches. A moving-average approach was used to identify the peak relative distance (m/min), average acceleration/deceleration (AveAcc; m/s2), and average metabolic power (Pmet) for a range of durations (1-10 min). Differences between positions and durations were described using a magnitude-based network. Results: Peak running intensity increased as the length of the moving average decreased. There were likely small to moderate increases in relative distance and AveAcc for outside backs, halfbacks, and loose forwards compared with the tight 5 group across all moving-average durations (effect size [ES] = 0.27-1.00). Pmet demands were at least likely greater for outside backs and halfbacks than for the tight 5 (ES = 0.86-0.99). Halfbacks demonstrated the greatest relative distance and Pmet outputs but were similar to outside backs and loose forwards in AveAcc demands. Conclusions: The current study has presented a framework to describe the peak running intensities achieved during international rugby competition by position, which are considerably higher than previously reported whole-period averages. These data provide further knowledge of the peak activity profiles of international rugby competition, and this information can be used to assist coaches and practitioners in adequately preparing athletes for the most demanding periods of play. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the effects of a training camp on the sleep characteristics of professional rugby league players compared with a home period. Methods: During a 7-d home and 13-d camp period, time in bed (TIB), total sleep time (TST), sleep efficiency (SE), and wake after sleep onset were measured using wristwatch actigraphy. Subjective wellness and training loads (TL) were also collected. Differences in sleep and TL between the 2 periods and the effect of daytime naps on nighttime sleep were examined using linear mixed models. Pearson correlations assessed the relationship of changes in TL on individuals' TST. Results: During the training camp, TST (-85 min), TIB (-53 min), and SE (-8%) were reduced compared with home. Those who undertook daytime naps showed increased TIB (+33 min), TST (+30 min), and SE (+0.9%). Increases in daily total distance and training duration above individual baseline means during the training camp shared moderate (r = -.31) and trivial (r = -.04) negative relationships with TST. Conclusions: Sleep quality and quantity may be compromised during training camps; however, daytime naps may be beneficial for athletes due to their known benefits, without being detrimental to nighttime sleep. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the ability of various internal and external training-load (TL) monitoring measures to predict injury incidence among positional groups in professional rugby league athletes. Methods: TL and injury data were collected across 3 seasons (2013-2015) from 25 players competing in National Rugby League competition. Daily TL data were included in the analysis, including session rating of perceived exertion (sRPE-TL), total distance (TD), high-speed-running distance (>5 m/s), and high-metabolic-power distance (HPD; >20 W/kg). Rolling sums were calculated, nontraining days were removed, and athletes' corresponding injury status was marked as "available" or "unavailable." Linear (generalized estimating equations) and nonlinear (random forest; RF) statistical methods were adopted. Results: Injury risk factors varied according to positional group. For adjustables, the TL variables associated most highly with injury were 7-d Td and 7-d HPD, whereas for hit-up forwards they were sRPE-TL ratio and 14-d TD. For outside backs, 21- and 28-d sRPE-TL were identified, and for wide-running forwards, sRPE-TL ratio. The individual RF models showed that the importance of the TL variables in injury incidence varied between athletes. Conclusions: Differences in risk factors were recognized between positional groups and individual athletes, likely due to varied physiological capacities and physical demands. Furthermore, these results suggest that robust machine-learning techniques can appropriately monitor injury risk in professional team-sport athletes. [ABSTRACT FROM AUTHOR]

Purpose: The influence of various factors on training-load (TL) responses in basketball has received limited attention. This study aimed to examine the temporal changes and influence of cumulative training dose on TL responses and interrelationships during basketball activity. Methods: Ten state-level Australian male junior basketball players completed 4 x 10-min standardized bouts of simulated basketball activity using a circuit-based protocol. Internal TL was quantified using the session rating of perceived exertion (sRPE), summated heart-rate zones (SHRZ), Banister training impulse (TRIMP), and Lucia TRIMP models. External TL was assessed via measurement of mean sprint and circuit speeds. Temporal TL comparisons were performed between 10-min bouts, while Pearson correlation analyses were conducted across cumulative training doses (0-10, 0-20, 0-30, and 0-40 min). Results: sRPE TL increased (P < .05) after the first 10-min bout of basketball activity. sRPE TL was only significantly related to Lucia TRIMP (r = .66--.69; P < .05) across 0-10 and 0-20 min. Similarly, mean sprint and circuit speed were significantly correlated across 0-20 min (r = .67; P < .05). In contrast, SHRZ and Banister TRIMP were significantly related across all training doses (r = .84-.89; P < .05). Conclusions: Limited convergence exists between common TL approaches across basketball training doses lasting beyond 20 min. Thus, the interchangeability of commonly used internal and external TL approaches appears dose-dependent during basketball activity, with various psychophysiological mediators likely underpinning temporal changes. [ABSTRACT FROM AUTHOR]

Background: Rugby league coaches adopt replacement strategies for their interchange players to maximize running intensity; however, it is important to understand the factors that may influence match performance. Purpose: To assess the independent factors affecting running intensity sustained by interchange players during professional rugby league. Methods: Global positioning system (GPS) data were collected from all interchanged players (starters and nonstarters) in a professional rugby league squad across 24 matches of a National Rugby League season. A multilevel mixed-model approach was employed to establish the effect of various technical (attacking and defensive involvements), temporal (bout duration, time in possession, etc), and situational (season phase, recovery cycle, etc) factors on the relative distance covered and average metabolic power (Pmet) during competition. Significant effects were standardized using correlation coefficients, and the likelihood of the effect was described using magnitude-based inferences. Results: Superior intermittent running ability resulted in very likely large increases in both relative distance and Pmet. As the length of a bout increased, both measures of running intensity exhibited a small decrease. There were at least likely small increases in running intensity for matches played after short recovery cycles and against strong opposition. During a bout, the number of collision-based involvements increased running intensity, whereas time in possession and ball time out of play decreased demands. Conclusions: These data demonstrate a complex interaction of individual- and match-based factors that require consideration when developing interchange strategies, and the manipulation of training loads during shorter recovery periods and against stronger opponents may be beneficial. [ABSTRACT FROM AUTHOR]

The purpose of the present study was to examine the influence of direct supervision on muscular strength, power, and running speed during 12 weeks of resistance training in young rugby league players. Two matched groups of young (16.7 [+ or -] 1.1 years [mean [+ or - SD]), talented rugby league players completed the same periodized resistance-training program in either a supervised (SUP) (N = 21) or an unsupervised (UNSUP) (N = 21) environment. Measures of 3 repetition maximum (3RM) bench press, 3RM squat, maximal chin-ups, vertical jump, 10- and 20-m sprints, and body mass were completed pretest (week 0), midtest (week 6), and posttest (week 12) training program. Results show that 12 weeks of periodized resistance training resulted in an increased body mass, 3RM bench press, 3RM squat, maximum number of chin-ups, vertical jump height, and 10- and 20-m sprint performance in both groups (p < 0.05). The SUP group completed significantly more training sessions, which were significantly correlated to strength increases for 3RM bench press and squat (p < 0.05). Furthermore, the SUP group significantly increased 3RM squat strength (at 6 and 12 weeks) and 3RM bench press strength (12 weeks) when compared to the UNSUP group (p < 0.05). Finally, the percent increase in the 3RM bench press, 3RM squat, and chin-[up.sub.max] was also significantly greater in the SUP group than in the UNSUP group (p < 0.05). These findings show that the direct supervision of resistance training in young athletes results in greater training adherence and increased strength gains than does unsupervised training. KEY WORDS. strength coaching, young athletes, strength training

Rugby league involves frequent periods of high-intensity running including acceleration and deceleration efforts, often occurring at low speeds. Purpose: To quantify the energetic cost of running and acceleration efforts during rugby league competition to aid in prescription and monitoring of training. Methods: Global positioning system (GPS) data were collected from 37 professional rugby league players across 2 seasons. Peak values for relative distance, average acceleration/deceleration, and metabolic power (Pmet) were calculated for 10 different moving-average durations (1-10 min) for each position. A mixed-effects model was used to assess the effect of position for each duration, and individual comparisons were made using a magnitude-based-inference network. Results: There were almost certainly large differences in relative distance and Pmet between the 10-min window and all moving averages <5 min in duration (ES = 1.21-1.88). Fullbacks, halves, and hookers covered greater relative distances than outside backs, edge forwards, and middle forwards for moving averages lasting 2-10 min. Acceleration/deceleration demands were greatest in hookers and halves compared with fullbacks, middle forwards, and outside backs. Pmet was greatest in hookers, halves, and fullbacks compared with middle forwards and outside backs. Conclusions: Competition running intensities varied by both position and moving-average duration. Hookers exhibited the greatest Pmet of all positions, due to high involvement in both attack and defense. Fullbacks also reached high Pmet, possibly due to a greater absolute volume of running. This study provides coaches with match data that can be used for the prescription and monitoring of specific training drills. [ABSTRACT FROM AUTHOR]

Purpose: To identify contributing factors to the incidence of illness for professional team-sport athletes, using training load (TL), self-reported illness, and well-being data. Methods: Thirty-two professional rugby league players (26.0 ± 4.8 y, 99.1 ± 9.6 kg, 1.84 ± 0.06 m) were recruited from the same club. Players participated in prescribed training and responded to a series of questionnaires to determine the presence of self-reported illness and markers of well-being. Internal TL was determined using the session rating of perceived exertion. These data were collected over 29 wk, across the preparatory and competition macrocycles. Results: The predictive models developed recognized increases in internal TL (strain values of >2282 AU, weekly TL >2786 AU, and monotony >0.78 AU) to best predict when athletes are at increased risk of self-reported illness. In addition, a reduction in overall well-being (<7.25 AU) in the presence of increased internal TL, as previously stated, was highlighted as a contributor to self-reported-illness occurrence. Conclusions: These results indicate that self-report data can be successfully used to provide a novel understanding of the interactions between competition-associated stressors experienced by professional team-sport athletes and their susceptibility to illness. This may help coaching staff more effectively monitor players during the season and potentially implement preventive measures to reduce the likelihood of illnesses occurring. [ABSTRACT FROM AUTHOR]

High levels of lean mass are important in collision-based sports for the development of strength and power, which may also assist during contact situations. While skinfold-based measures have been shown to be appropriate for cross-sectional assessments of body composition, their utility in tracking changes in lean mass is less clear. Purpose: To determine the most effective method of quantifying changes in lean mass in rugby league athletes. Methods: Body composition of 21 professional rugby league players was assessed on 2 or 3 occasions separated by >6 wk, including bioelectrical impedance analysis (BIA), leanmass index (LMI), and a skin fold-based prediction equation (SkF). Dual-X-ray absorptiometry provided a criterion measure of fat-free mass (FFM). Correlation coefficients (r) and standard errors of the estimate (SEE) were used as measures of validity for the estimates. Results: All 3 practical estimates exhibited strong validity for cross-sectional assessments of FFM (r > .9, P < .001). The correlation between change scores was stronger for the LMI (r = .69, SEE 1.3 kg) and the SkF method (r = .66, SEE = 1.4 kg) than tor BIA (r = .50, SEE = 1.6 kg). Conclusions: The LMI is probably as accurate in predicting changes in FFM as SkF and very likely to be more appropriate than BIA. The LMI offers an adequate, practical alternative for assessing in FFM among rugby league athletes. [ABSTRACT FROM AUTHOR]