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Daniel G. Baker and Robert U. Newton

Purpose:

To examine the upper body strength, speed, power, and strength-endurance of rugby-league players of different ranks. These data could provide information pertinent to the importance of these factors for different grades of rugby league and for positional groups in those different grades.

Methods:

Sixty rugby-league players, 20 participants each in the elite, national first-division league (NRL), state-based second-division league (SRL), and intracity third-division league (CRL), served as subjects. Maximal upper body strength, power, speed, and muscle endurance were assessed using the bench-press exercise.

Results:

The NRL players were significantly stronger (141.4 ± 15.4 kg) than SRL (126.6 ± 13.1 kg, ES = 1.033) and CRL (108.1 kg ± 11.6, ES = 2.458) and more powerful (NRL = 680 ± 99 W) than SRL (591 ± 72 W, ES = 1.037) and CRL players (521 ± 71 W, ES = 1.867). The differences in speed (NRL = 345 ± 31 W, SRL = 319 ± 29 W, CRL = 303 ± 29 W; ES = 0.884 and 1.409, respectively) and strength-endurance (NRL = 36 ± 7 reps, SRL = 32 reps ± 7, CRL = 24 ± 5 reps; ES = 0.521 and 1.984, respectively) were not as pronounced.

Conclusions:

Of the tests undertaken, maximal strength best describes players who attain NRL ranking. Maximum power and strength-endurance were also strong descriptors of attainment of NRL level. Upper body speed appears less likely to strongly discriminate between players who attain NRL level and those who do not. These results tended to hold true across the different team positional groupings.

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Stuart J. Cormack, Robert U. Newton, and Michael R. McGuigan

Purpose:

To examine the acute and short-term responses of variables obtained during a single countermovement jump (CMJ1); repeated countermovement jump involving 5 consecutive efforts without a pause (CMJ5); and cortisol, testosterone, and testos-terone-to-cortisol ratio (T:C) to an elite Australian Rules Football (ARF) match with a view to determining which variables may be most useful for ongoing monitoring.

Methods:

Twenty-two elite ARF players participating in a preseason cup match performed a CMJ1 and a CMJ5 and provided saliva samples 48 h before the match (48pre), prematch (Pre), postmatch, 24 h post (24post), 72 h post (72post), 96 h post (96post), and 120 h post (120post). The magnitude of change in variables at each time point compared with Pre and 48pre was analyzed using the effect size (ES) statistic.

Results:

A substantial decrement in the pre- to postmatch comparison occurred in the ratio of CMJ1 Flight time:Contraction time (ES −0.65 ± 0.28). Cortisol (ES 2.34 ± 1.06) and T:C (ES −0.52 ± 0.42) displayed large pre- to postmatch changes. The response of countermovement variables at 24post and beyond compared with pre-match and 48pre was varied, with only CMJ1 Flight time:Contraction time displaying a substantial decrease (ES −0.32 ± 0.26) postmatch compared with 48pre. Cortisol displayed a clear pattern of response with substantial elevations up to 24post compared with Pre and 48pre.

Conclusion:

CMJ1 Flight time:Contraction time appears to be the most useful variable for monitoring neuromuscular status in elite ARF players due to its substantial change compared with 48pre and prematch. Monitoring cortisol, due to its predictable pattern of response, may provide a useful measure of hormonal status.

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Joseph O.C. Coyne, Robert U. Newton, and G. Gregory Haff

Purpose: A simple and 2 different exponentially weighted moving average methods were used to investigate the relationships between internal training load and elite weightlifting performance. Methods: Training impulse data (sessional ratings of perceived exertion × training duration) were collected from 21 elite weightlifters (age = 26.0 [3.2] y, height = 162.2 [11.3] cm, body mass = 72.2 [23.8] kg, previous 12-mo personal best total 96.3% [2.7%] of world record total) during the 8 weeks prior to the 2016 Olympic Games qualifying competition. The amount of training modified or cancelled due to injury/illness was also collected. The training stress balance (TSB) and acute to chronic workload ratio (ACWR) were calculated with the 3 moving average methods. Along with the amount of modified training, TSB and ACWR across the moving average methods were then examined for their relationship to competitive performance. Results: There were no consistent associations between performance and training load on the day of competition. The volatility (SD) of the ACWR in the last 21 days preceding the competition was moderately correlated with performance across moving average methods (r = −.41 to .48, P = .03–.07). TSB and ACWR volatility in the last 21 days were also significantly lower for successful performers but only as a simple moving average (P = .03 and .03, g = 1.15 and 1.07, respectively). Conclusions: Practitioners should consider restricting change and volatility in an athlete’s TSB or ACWR in the last 21 days prior to a major competition. In addition, a simple moving average seemed to better explain elite weightlifting performance than the exponentially weighted moving averages in this investigation.

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Kieran P. Young, G. Gregory Haff, Robert U. Newton, and Jeremy M. Sheppard

Purpose:

The purpose of this study was to evaluate the reliability of an isometric-bench-press (IBP) test performed across 4 elbow angles and a ballistic bench throw (BBT) using a relative load, as well as evaluating the reliability of the dynamic strength index (DSI: BBT peak force/IBP peak force).

Methods:

Twenty-four elite male athletes performed the IBP and a 45% 1-repetition-maximum BBT on 2 separate days with 48 h between testing occasions. Peak force, peak power, peak velocity, peak displacement, and peak rate of force development (PRFD) were assessed using a force plate and linear position transducer. Reliability was assessed by intraclass correlation (ICC), coefficient of variation (%CV) and typical error.

Results:

Performance measures in the BBT, such as peak force, peak velocity, peak power, and peak displacement, were considered reliable (ICC = .85–.92, %CV = 1.7–3.3), while PRFD was not (ICC = .43, %CV = 4.1). Similarly, for the IBP, peak force across all angles was considered reliable (ICC = .89–.97, %CV = 1.2–1.6), while PRFD was not (ICC = .56–.65, %CV = 0.5–7.6). The DSI was also reliable (ICC = .93, %CV = 3.5).

Conclusions:

Performance measures such as peak force in the IBP and BBT are reliable when assessing upper-body pressing-strength qualities in elite male athletes. Furthermore, the DSI is reliable and could potentially be used to detect qualities of relative deficiency and guide specific training interventions.

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Kieran P. Young, G. Gregory Haff, Robert U. Newton, Tim J. Gabbett, and Jeremy M. Sheppard

Purpose:

To evaluate whether the dynamic strength index (DSI: ballistic peak force/isometric peak force) could be effectively used to guide specific training interventions and detect training-induced changes in maximal and ballistic strength.

Methods:

Twenty-four elite male athletes were assessed in the isometric bench press and a 45% 1-repetition-maximum (1RM) ballistic bench throw using a force plate and linear position transducer. The DSI was calculated using the peak force values obtained during the ballistic bench throw and isometric bench press. Athletes were then allocated into 2 groups as matched pairs based on their DSI and strength in the 1RM bench press. Over the 5 wk of training, athletes performed either high-load (80–100% 1RM) bench press or moderate-load (40–55% 1RM) ballistic bench throws.

Results:

The DSI was sensitive to disparate training methods, with the bench-press group increasing isometric bench-press peak force (P = .035, 91% likely), and the ballistic-bench-throw group increasing bench-throw peak force to a greater extent (P ≤ .001, 83% likely). A significant increase (P ≤ .001, 93% likely) in the DSI was observed for both groups.

Conclusions:

The DSI can be used to guide specific training interventions and can detect training-induced changes in isometric bench-press and ballistic bench-throw peak force over periods as short as 5 wk.

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Stuart J. Cormack, Robert U. Newton, Michael R. McGuigan, and Tim L.A. Doyle

Purpose:

To establish the reliability of various measures obtained during single and repeated countermovement jump (CMJ) performance in an elite athlete population.

Methods:

Two studies, each involving 15 elite Australian Rules Football (ARF) players were conducted where subjects performed two days, separated by one week, of AM and PM trials of either a single (CMJ1) or 5 repeated CMJ (CMJ5). Each trial was conducted on a portable force-plate. The intraday, interday, and overall typical error (TE) and coefficient of variation (CV%) were calculated for numerous variables in each jump type.

Results:

A number of CMJ1 and CMJ5 variables displayed high intraday, interday, and overall reliability. In the CMJ1 condition, mean force (CV 1.08%) was the most reliable variable. In the CMJ5, fight time and relative mean force displayed the highest repeatability with CV of 1.88% and 1.57% respectively. CMJ1Mean force was the only variable with an overall TE < smallest worthwhile change (SWC).

Conclusion:

Selected variables obtained during CMJ1 and CMJ5 performance can be used to assess the impact of both acute and chronic training and competition. Variables derived from the CMJ5 may respond differently than their CMJ1 counterparts and should provide insights into differential mechanisms of response and adaptation.

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Joseph O.C. Coyne, Sophia Nimphius, Robert U. Newton, and G. Gregory Haff

Purpose: Criticisms of the acute to chronic workload ratio (ACWR) have been that the mathematical coupling inherent in the traditional calculation of the ACWR results in a spurious correlation. The purposes of this commentary are (1) to examine how mathematical coupling causes spurious correlations and (2) to use a case study from actual monitoring data to determine how mathematical coupling affects the ACWR. Methods: Training and competition workload (TL) data were obtained from international-level open-skill (basketball) and closed-skill (weightlifting) athletes before their respective qualifying tournaments for the 2016 Olympic Games. Correlations between acute TL, chronic TL, and the ACWR as coupled/uncoupled variations were examined. These variables were also compared using both rolling averages and exponentially weighted moving averages to account for any potential benefits of one calculation method over another. Results: Although there were some significant differences between coupled and uncoupled chronic TL and ACWR data, the effect sizes of these differences were almost all trivial (g = 0.04–0.21). Correlations ranged from r = .55 to .76, .17 to .53, and .88 to .99 for acute to chronic TL, acute to uncoupled chronic TL, and ACWR to uncoupled ACWR, respectively. Conclusions: There may be low risk of mathematical coupling causing spurious correlations in the TL–injury-risk relationship. Varying levels of correlation seem to exist naturally between acute and chronic TL variables regardless of coupling. The trivial to small effect sizes and large to nearly perfect correlations between coupled and uncoupled AWCRs also imply that mathematical coupling may have little effect on either calculation method, if practitioners choose to apply the ACWR for TL monitoring purposes.

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Stuart J. Cormack, Robert U. Newton, Michael R. McGuigan, and Prue Cormie

Purpose:

To examine variations in neuromuscular and hormonal status and their relationship to performance throughout a season of elite Australian Rules Football (ARF).

Methods:

Fifteen elite ARF players performed a single jump (CMJ1) and 5 repeated countermovement jumps (CMJ5), and provided saliva samples for the analysis of cortisol (C) and testosterone (T) before the season commenced (Pre) and during the 22-match season. Magnitudes of effects were reported with the effect size (ES) statistic. Correlations were performed to analyze relationships between assessment variables and match time, training load, and performance.

Results:

CMJ1Flight time:Contraction time was substantially reduced on 60% of measurement occasions. Magnitudes of change compared with Pre ranged from 1.0 ± 7.4% (ES 0.04 ± 0.29) to −17.1 ± 21.8% (ES −0.77 ± 0.81). Cortisol was substantially lower (up to −40 ± 14.1%, ES of −2.17 ± 0.56) than Pre in all but one comparison. Testosterone response was varied, whereas T:C increased substantially on 70% of occasions, with increases to 92.7 ± 27.8% (ES 2.03 ± 0.76). CMJ1Flight time:Contraction time (r = .24 ± 0.13) and C displayed (r = −0.16 ± 0.1) small correlations with performance.

Conclusion:

The response of CMJ1Flight time:Contraction time suggests periods of neuromuscular fatigue. Change in T:C indicates subjects were unlikely to have been in a catabolic state during the season. Increase in C compared with Pre had a small negative correlation with performance. Both CMJ1Flight time:Contraction time and C may be useful variables for monitoring responses to training and competition in elite ARF athletes.

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Joseph O.C. Coyne, Sophia Nimphius, Robert U. Newton, and G. Gregory Haff

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Joseph O.C. Coyne, Aaron J. Coutts, Robert U. Newton, and G. Gregory Haff

Purpose: To investigate the relationships between internal and external training load (TL) metrics with elite international women’s basketball performance. Methods: Sessional ratings of perceived exertion, PlayerLoad/minute, and training duration were collected from 13 elite international-level female basketball athletes (age 29.0 [3.7] y, stature 186.0 [9.8] cm, body mass 77.9 [11.6] kg) during the 18 weeks prior to the International Basketball Federation Olympic qualifying event for the 2016 Rio Olympic Games. Training stress balance, differential load, and the training efficiency index were calculated with 3 different smoothing methods. These TL metrics and their change in the last 21 days prior to competition were examined for their relationship to competition performance as coach ratings of performance. Results: For a number of TL variables, there were consistent significant small to moderate correlations with performance and significant small to large differences between successful and unsuccessful performances. However, these differences were only evident for external TL when using exponentially weighted moving averages to calculate TL. The variable that seemed most sensitive to performance was the change in training efficiency index in the last 21 days prior to competition (performance r = .47–.56, P < .001 and difference between successful and unsuccessful performance P < .001, f2 = 0.305–0.431). Conclusions: Internal and external TL variables were correlated with performance and distinguished between successful and unsuccessful performances among the same players during international women’s basketball games. Manipulating TL in the last 3 weeks prior to competition may be worthwhile for basketball players’ performance, especially in internal TL.