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Strength Training for Athletes: Does It Really Help Sports Performance?

Michael R. McGuigan, Glenn A. Wright, and Steven J. Fleck

The use of strength training designed to increase underlying strength and power qualities in elite athletes in an attempt to improve athletic performance is commonplace. Although the extent to which strength and power are important to sports performance may vary depending on the activity, the associations between these qualities and performance have been well documented in the literature. The purpose of this review is to provide a brief overview of strength training research to determine if it really helps improve athletic performance. While there is a need for more research with elite athletes to investigate the relationship between strength training and athletic performance, there is sufficient evidence for strength training programs to continue to be an integral part of athletic preparation in team sports.

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Factors That Affect Selection of Elite Women’s Sculling Crews

Trent W. Lawton, John B. Cronin, and Michael R. McGuigan

Purpose:

There is no common theory on criteria to appropriately select crew rowers in pursuit of small performance gains. The purpose of this study was to establish whether anthropometry, rowing ergometry, or lower body strength were suitable criteria to identify differences between selected and nonselected sculling crews.

Method:

Twelve elite women performed a 2000-m ergometer time trial and a 5-repetition leg-press dynamometer test, were anthropometrically profiled, and participated in on-water national crew seat-racing trials. Log-transformed data were analyzed to compare percent (± SD) and standardized differences in group means (ES; ±90% confidence interval [CI]) between selected and nonselected oarswomen, with adjustments for body mass where appropriate.

Results:

Selected crew boats were 4.60% ± 0.02% faster and won by an average margin of 13.5 ± 0.7 s over 1500 m. There were no differences between crews on average in height, arm span, seated height, body mass, or 8-site skinfold sum (body fat). Difference in 2000-m ergometer times were also trivial (ES = 0.2, 90%CI = −0.6 to 1.1, P = .63); however, selected crews had moderately greater leg-press strength (ES = 1.1, 90%CI = 0.3−1.9, P = .03).

Conclusion:

Selected oarswomen with comparable anthropometry and 2000-m ergometer ability had greater lower body strength. Coaches of elite oarswomen might consider leg strength as part of crew-selection criteria, given acceptable on-water boatmanship and attainment of 2000-m ergometer benchmarks.

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Neuromuscular and Endocrine Responses of Elite Players to an Australian Rules Football Match

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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Monitoring Different Types of Resistance Training Using Session Rating of Perceived Exertion

Favil Singh, Carl Foster, David Tod, and Michael R. McGuigan

Purpose:

To evaluate the effectiveness of session rating of perceived exertion (RPE) to measure effort during different types of resistance training.

Method:

Fifteen male subjects (age 26.7 ± 4.3 years) performed 3 protocols. All protocols consisted of same 5 exercises but with different intensities, rest periods, and numbers of repetitions. One-repetition maximum (1-RM) was defined as the maximal amount of weight that an individual could lift 1 time without support. The strength protocol included 3 sets of 5 repetitions at 90% of 1-RM with 3 minutes rest between. The hypertrophy session included 3 sets of 10 repetitions at 70% with 1 minute of rest, and the power session included 3 sets of 5 repetitions at 50% with 3 minutes of rest. Session RPE is a modification of the standard RPE scale. Session and standard RPE were measured after the completion of each set and 30 minutes postexercise, respectively.

Results:

Results showed a difference between both the 2 RPE values of the strength and hypertrophy protocols (P ≤ .05) but no difference between mean and session RPE values for the power protocol. During the familiarization session, session RPE was measured at 5-minute intervals for 30 minutes postexercise. There was a significant difference (P ≤ .05) between the mean RPE values at the fifth and tenth minutes postexercise when compared with 30 minutes postexercise. All other session RPE values showed no significant difference.

Conclusion:

The session RPE method appears to be effective in monitoring different types of resistance training, and session RPE after 30 minutes was a better indicator of the overall resistance sessions than average RPE.

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Effects of Different Uphill Interval-Training Programs on Running Economy and Performance

Kyle R. Barnes, Will G. Hopkins, Michael R. McGuigan, and Andrew E. Kilding

Purpose:

Runners use uphill running as a movement-specific form of resistance training to enhance performance. However, the optimal parameters for prescribing intervals are unknown. The authors adopted a dose-response design to investigate the effects of various uphill interval-training programs on physiological and performance measures.

Methods:

Twenty well-trained runners performed an incremental treadmill test to determine aerobic and biomechanical measures, a series of jumps on a force plate to determine neuromuscular measures, and a 5-km time trial. Runners were then randomly assigned to 1 of 5 uphill interval-training programs. After 6 wk all tests were repeated. To identify the optimal training program for each measure, each runner’s percentage change was modeled as a quadratic function of the rank order of the intensity of training. Uncertainty in the optimal training and in the corresponding effect on the given measure was estimated as 90% confidence limits using bootstrapping.

Results:

There was no clear optimum for time-trial performance, and the mean improvement over all intensities was 2.0% (confidence limits ±0.6%). The highest intensity was clearly optimal for running economy (improvement of 2.4% ± 1.4%) and for all neuromuscular measures, whereas other aerobic measures were optimal near the middle intensity. There were no consistent optima for biomechanical measures.

Conclusions:

These findings support anecdotal reports for incorporating uphill interval training in the training programs of distance runners to improve physiological parameters relevant to running performance. Until more data are obtained, runners can assume that any form of high-intensity uphill interval training will benefit 5-km time-trial performance.

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Higher- Versus Lower-Intensity Strength-Training Taper: Effects on Neuromuscular Performance

Hayden J. Pritchard, Matthew J. Barnes, Robin J. Stewart, Justin W. Keogh, and Michael R. McGuigan

Purpose: To investigate the effects of strength-training tapers of different intensities but equal volume reductions on neuromuscular performance. Methods: Eleven strength-trained men (21.3 [3.3] y, 92.3 [17.6] kg, relative 1-repetition-maximum deadlift 1.9 [0.2] times bodyweight) completed a crossover study. Specifically, two 4-wk strength-training blocks were followed by a taper week with reduced volume (∼70%) involving either increased (5.9%) or decreased (−8.5%) intensity. Testing occurred pretraining (T1), posttraining (T2), and posttaper (T3). Salivary testosterone and cortisol, plasma creatine kinase, a Daily Analysis of Life Demands in Athletes questionnaire, countermovement jump (CMJ), isometric midthigh pull, and isometric bench press were measured. Results: CMJ height improved significantly over time (P < .001), with significant increases from T1 (38.0 [5.5] cm) to both T2 (39.3 [5.3] cm; P = .010) and T3 (40.0 [5.3] cm; P = .001) and from T2 to T3 (P = .002). CMJ flight time:contraction time increased significantly over time (P = .004), with significant increases from T1 (0.747 [0.162]) to T2 (0.791 [0.163]; P = .012). Isometric midthigh-pull relative peak force improved significantly over time (P = .033), with significant increases from T1 (34.7 [5.0] N/kg) to T2 (35.9 [4.8] N/kg; P = .013). No significant changes were found between tapers. However, the higher-intensity taper produced small effect-size increases at T3 vs T1 for isometric midthigh-pull relative peak force, CMJ height, and flight time:contraction time, while the lower-intensity taper only produced small effect-size improvements at T3 vs T1 for CMJ height. Conclusions: A strength-training taper with volume reductions had a positive effect on power, with a tendency for the higher-intensity taper to produce more favorable changes in strength and power.

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Determining the Optimum Bar Velocity in the Barbell Hip Thrust Exercise

Irineu Loturco, Timothy Suchomel, Chris Bishop, Ronaldo Kobal, Lucas A. Pereira, and Michael R. McGuigan

Purpose: To identify the bar velocities that optimize power output in the barbell hip thrust exercise. Methods: A total of 40 athletes from 2 sports disciplines (30 track-and-field sprinters and jumpers and 10 rugby union players) participated in this study. Maximum bar-power outputs and their respective bar velocities were assessed in the barbell hip thrust exercise. Athletes were divided, using a median split analysis, into 2 groups according to their bar-power outputs in the barbell hip thrust exercise (“higher” and “lower” power groups). The magnitude-based inferences method was used to analyze the differences between groups in the power and velocity outcomes. To assess the precision of the bar velocities for determining the maximum power values, the coefficient of variation (CV%) was also calculated. Results: Athletes achieved the maximum power outputs at a mean velocity, mean propulsive velocity, and peak velocity of 0.92 (0.04) m·s−1 (CV: 4.1%), 1.02 (0.05) m·s−1 (CV: 4.4%), and 1.72 (0.14) m·s−1 (CV: 8.4%), respectively. No meaningful differences were observed in the optimum bar velocities between higher and lower power groups. Conclusions: Independent of the athletes’ power output and bar-velocity variable, the optimum power loads frequently occur at very close bar velocities.

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Dimensionality Reduction for Countermovement Jump Metrics

Lachlan P. James, Haresh Suppiah, Michael R. McGuigan, and David L. Carey

Purpose: Dozens of variables can be derived from the countermovement jump (CMJ). However, this does not guarantee an increase in useful information because many of the variables are highly correlated. Furthermore, practitioners should seek to find the simplest solution to performance testing and reporting challenges. The purpose of this investigation was to show how to apply dimensionality reduction to CMJ data with a view to offer practitioners solutions to aid applications in high-performance settings. Methods: The data were collected from 3 cohorts using 3 different devices. Dimensionality reduction was undertaken on the extracted variables by way of principal component analysis and maximum likelihood factor analysis. Results: Over 90% of the variance in each CMJ data set could be explained in 3 or 4 principal components. Similarly, 2 to 3 factors could successfully explain the CMJ. Conclusions: The application of dimensional reduction through principal component analysis and factor analysis allowed for the identification of key variables that strongly contributed to distinct aspects of jump performance. Practitioners and scientists can consider the information derived from these procedures in several ways to streamline the transfer of CMJ test information.

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Influence of Neuromuscular Fatigue on Accelerometer Load in Elite Australian Football Players

Stuart J. Cormack, Mitchell G. Mooney, Will Morgan, and Michael R. McGuigan

Purpose:

To determine the impact of neuromuscular fatigue (NMF) assessed from variables obtained during a countermovement jump on exercise intensity measured with triaxial accelerometers (load per minute [LPM]) and the association between LPM and measures of running activity in elite Australian Football.

Methods:

Seventeen elite Australian Football players performed the Yo-Yo Intermittent Recovery Test level 2 (Yo-Yo IR2) and provided a baseline measure of NMF (flight time:contraction time [FT:CT]) from a countermovement jump before the season. Weekly samples of FT:CT, coaches’ rating of performance (votes), LPM, and percent contribution of the 3 vectors from the accelerometers in addition to high-speed-running meters per minute at >15 km/h and total distance relative to playing time (m/min) from matches were collected. Samples were divided into fatigued and nonfatigued groups based on reductions in FT:CT. Percent contributions of vectors to LPM were assessed to determine the likelihood of a meaningful difference between fatigued and nonfatigued groups. Pearson correlations were calculated to determine relationships between accelerometer vectors and running variables, votes, and Yo-Yo IR2 score.

Results:

Fatigue reduced the contribution of the vertical vector by (mean ± 90% CI) –5.8% ± 6.1% (86% likely) and the number of practically important correlations.

Conclusions:

NMF affects the contribution of individual vectors to total LPM, with a likely tendency toward more running at low speed and less acceleration. Fatigue appears to limit the influence of the aerobic and anaerobic qualities assessed via the Yo-Yo IR2 test on LPM and seems implicated in pacing.

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Neuromuscular and Endocrine Responses of Elite Players During an Australian Rules Football Season

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.