Search Results

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.

Purpose: To examine the reliability of peak velocity (PV), mean propulsive velocity (MPV), and mean velocity (MV) in the development of load–velocity profiles (LVP) in the full-depth free-weight back squat performed with maximal concentric effort. Methods: Eighteen resistance-trained men performed a baseline 1-repetition maximum (1-RM) back-squat trial and 3 subsequent 1-RM trials used for reliability analyses, with 48-h intervals between trials. 1-RM trials comprised lifts from 6 relative loads including 20%, 40%, 60%, 80%, 90%, and 100% 1-RM. Individualized LVPs for PV, MPV, or MV were derived from loads that were highly reliable based on the following criteria: intraclass correlation coefficient (ICC) >.70, coefficient of variation (CV) ≤10%, and Cohen d effect size (ES) <0.60. Results: PV was highly reliable at all 6 loads. MPV and MV were highly reliable at 20%, 40%, 60%, 80%, and 90% but not 100% 1-RM (MPV: ICC = .66, CV = 18.0%, ES = 0.10, SEM = 0.04 m·s⁻¹; MV: ICC = .55, CV = 19.4%, ES = 0.08, SEM = 0.04 m·s⁻¹). When considering the reliable ranges, almost perfect correlations were observed for LVPs derived from PV_20–100% (r = .91–.93), MPV_20–90% (r = .92–.94), and MV_20–90% (r = .94–.95). Furthermore, the LVPs were not significantly different (P > .05) between trials or movement velocities or between linear regression versus 2nd-order polynomial fits. Conclusions: PV_20–100%, MPV_20–90%, and MV_20–90% are reliable and can be utilized to develop LVPs using linear regression. Conceptually, LVPs can be used to monitor changes in movement velocity and employed as a method for adjusting sessional training loads according to daily readiness.

Purpose: To analyze the differences in the force–velocity (F–v) profile assessed under unconstrained (ie, using free weights) and constrained (ie, on a Smith machine) vertical jumps, as well as to determine the between-day reliability. Methods: A total of 23 trained participants (18 [1] y) performed an incremental load squat jump test (with ∼35%, 45%, 60%, and 70% of the subjects’ body mass) on 2 different days using free weights and a Smith machine. Nine of these participants repeated the tests on 2 other days for an exploratory analysis of between-day reliability. F–v variables (ie, maximum theoretical force [F ₀], velocity [v ₀], and power, and the imbalance between the actual and the theoretically optimal F–v profile) were computed from jump height. Results: A poor agreement was observed between the F–v variables assessed under constrained and unconstrained conditions (intraclass correlation coefficient [ICC] < .50 for all). The height attained during each single jump performed under both constrained and unconstrained conditions showed an acceptable reliability (coefficient of variation < 10%, ICC > .70). The F–v variables computed under constrained conditions showed an overall good agreement (ICC = .75–.95 for all variables) and no significant differences between days (P > .05), but a high variability for v ₀, the imbalance between the actual and the theoretically optimal F–v profile, and maximal theoretical power (coefficient of variation = 17.0%–27.4%). No between-day differences were observed for any F–v variable assessed under unconstrained conditions (P > .05), but all of the variables presented a low between-day reliability (coefficient of variation > 10% and ICC < .70 for all). Conclusions: F–v variables differed meaningfully when obtained from constrained and unconstrained loaded jumps, and most importantly seemed to present a low between-day reliability.

Purpose: To examine the reliability and usefulness of the isometric midthigh pull (IMTP) and isometric squat (ISqT) performed at the same knee and hip angles. The scores produced in each test were compared to determine the magnitude of differences between tests. Methods: Twenty-six male and female athletes (age, 23.6 [4.3] y; height, 1.75 [0.07] m; and body mass, 68.8 [9.7] kg) performed 2 maximal repetitions of the IMTP and ISqT following a specific warm-up. Results: Maximum force, absolute peak force (PF), relative PF, allometrically scaled PF, rate of force development (0–200 and 0–250 ms), and impulse (0–300 ms) were deemed reliable (intraclass correlation coefficient [ICC] ≥.86 and coefficient of variation [CV] ≤9.4%) in the IMTP and ISqT based on predetermined criteria (ICC ≥.8 and CV ≤10%). Impulse (0–200 and 0–250 ms) was reliable in the ISqT (ICC ≥.92 and CV ≤9.9%). Participants produced significantly (P < .05) greater PF and impulse (0–300 ms) during the ISqT compared with the IMTP. When split by sex, female participants produced significantly greater PF (P = .042) during the ISqT, with no significant differences among male participants (P = .245). Both tests are capable of detecting changes in performance in maximum force and absolute PF. Conclusions: Both tests are reliable for non-time-dependent maximal strength measures when measured at the same knee and hip angles. The ISqT may be preferred when coaches want to test an athlete’s true maximum lower-limb strength, especially female athletes.

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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