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The study aim was to compare different predictive models in one repetition maximum (1RM) estimation from load-velocity profile (LVP) data. Fourteen strength-trained men underwent initial 1RMs in the free-weight back squat, followed by two LVPs, over three sessions. Profiles were constructed via a combined method (jump squat (0 load, 30–60% 1RM) + back squat (70–100% 1RM)) or back squat only (0 load, 30–100% 1RM) in 10% increments. Quadratic and linear regression modeling was applied to the data to estimate 80% 1RM (kg) using 80% 1RM mean velocity identified in LVP one as the reference point, with load (kg), then extrapolated to predict 1RM. The 1RM prediction was based on LVP two data and analyzed via analysis of variance, effect size (g/ηp2), Pearson correlation coefficients (r), paired t-tests, standard error of the estimate (SEE), and limits of agreement (LOA). p < 0.05. All models reported systematic bias < 10 kg, r > 0.97, and SEE < 5 kg, however, all linear models were significantly different from measured 1RM (p = 0.015 <0.001). Significant differences were observed between quadratic and linear models for combined (p < 0.001; ηp2 = 0.90) and back squat (p = 0.004, ηp2 = 0.35) methods. Significant differences were observed between exercises when applying linear modeling (p < 0.001, ηp2 = 0.67–0.80), but not quadratic (p = 0.632–0.929, ηp2 = 0.001–0.18). Quadratic modeling employing the combined method rendered the greatest predictive validity. Practitioners should therefore utilize this method when looking to predict daily 1RMs as a means of load autoregulation.

This study aimed to compare the effectiveness of high, moderate, and low resistance training volume-load of maximum strength training on muscle strength and swimming performance in competitive swimmers. Thirty-three male swimmers were randomly allocated to high (age = 16.5 ± 0.30 years), moderate (age = 16.1 ± 0.32 years) and a low resistance training volume-load group (age = 15.9 ± 0.31). This study was carried out in mid-season (January to March). Pre and post strength (e.g., repetition maximum [1RM] leg extension and bench press tests), swimming (25, 50 m front-crawl), start (speed, time, distance) and turn (time of turn) performance tests were conducted. Our findings revealed a large main effect of time for 1RM bench press: d = 1.38; 1RM leg extension: d = 1.55, and for 25 (d = 1.12), and 50 m (d = 1.97) front-crawl, similarly for start and turn performance (d = 1.28–1.46). However, no significant Group × Time interactions were shown in all strength swimming performances, start and turn tests (p > 0.05). In conclusion, low training loads have been shown to elicit the same results as moderate, and high training loads protocol. Therefore, this study shows evidence that the addition of low training volume-loads as a regular part of a maximal strength training regime will elicit improvements in strength and swimming performance.

Maximal strength is considered a fundamental aspect of athletic performance across a wide range of sports and is also needed for a range of activities of daily life. Yet, compared to males there are fewer publications examining females, with most showing similar coefficients of correlation between dynamic strength and different athletic performances. In both, males and females, results are biased by mostly small sample sizes (sample bias) leading to a fluctuation around the true correlation coefficient of the entire population. This crosssectional analysis involving 1544 participants employed multivariate and correlative analyses to clarify the importance of maximum strength in the parallel back squats on the jump performance controlling for variables such as type of sport, sex, age, and performance level. The analysis revealed two principal components that reflect distinct types of variability within the dataset: the first, primarily associated with performance capabilities, accounts for 58.45% of the variance, while the second, emphasizing demographic differences, accounts for a considerably lower variance of 25.08%. The correlation analyses in this study identified maximal strength as a significant factor influencing jumping performance, accounting for 48-53% of the variance in jump height. The analysis presents a saturation curve, with potential diminishing returns at higher strength levels. Age and sex had little to no effect on overall correlation coefficients. The overall correlation coefficients and the analyses for the subgroups (by sport and performance level) can differ considerably, which can be explained (mathematically) by the artificial formation of clusters, homogeneous subject groups, or small sample sizes.

The aim of the study was to compare the effects of two different training protocols, which differ in the duration of the eccentric phase, on the one-repetition maximum (1RM), thickness and contractile properties of elbow flexors. Twenty untrained college students were randomly divided into two experimental groups, based on the training tempo: FEG (Faster Eccentric Group: 1/0/1/0) and SEG (Slower Eccentric Group: 4/0/1/0). Training intervention was a biceps bending exercise, conducted twice a week for 7 weeks. The intensity (60-70% RM), sets (3-4) and rest intervals (120 s) were held constant, while repetitions were performed until it was not possible to maintain a set duration. In the initial and final measurements, 1RM, muscle thickness and tensiomyography parameters - contraction time (Tc) and radial deformation (Dm) - were evaluated. An ANCOVA model (using baseline outcomes as covariates) was applied to determine between-group differences at post-test, while Pearson's product-moment correlation coefficient was used to investigate the relationship between absolute changes in muscle thickness and Dm. Muscle strength increase was greater for SEG than for FEG (6.0 ± 1.76 vs. 3.30 ± 2.26 kg, p < 0.01). In both groups muscle thickness increased equally (FEG: 3.24 ± 2.01 vs. SEG: 3.57 ± 1.17 mm, p < 0.01), while an overall reduction in Dm was observed (FEG: 1.99 ± 1.20 vs. SEG: 2.26 ± 1.03 mm, p < 0.01). Values of Tc remained unchanged. A significant negative relationship was observed between changes in muscle thickness and Dm (r = -0.763, Adj.R² = 0.560, p < 0.01). These results indicate that the duration of the eccentric phase has no effect on muscle hypertrophy in untrained subjects, but that slower eccentric movement significantly increases 1RM.

Purpose: The study aimed to investigate the temporal effects of static and dynamic post-activation potentiation (PAP) conditioning activities on agility performance.Material and Methods: Fourteen male adolescent soccer players participated in the study. Participants performed three different conditioning activities randomly on non-consecutive days. Conditioning activities consisted of static, dynamic, and control protocols. The dynamic protocol was performed with the dynamic squat at 85% of 1-repetition maximum while the static protocol was performed 3 repetitions x 3 seconds of the isometric squat. The control protocol only completed a standardized warm-up. After the baseline measurements were taken, all protocols completed the agility test in 15th seconds, 2,4,6,8,10,12,14th minutes. Repeated measures in ANOVA were used to determine differences between PAP protocols and the Bonferroni post hoc test was employed to determine which protocol caused a significant difference.Results: There was no significant difference between protocols in baseline (p<.925, ηp2 = 0.006), however, the control protocol caused a significant difference in 15th seconds and 2nd minutes compared to static and dynamic protocols (p<.001, ηp2 = 0.73, 0.72, respectively). In the 4th and 6th minutes static and dynamic protocols caused a significant difference compared to control (p<.001, ηp2 = 0.46-0.89, respectively), and in the 8th-minute static and dynamic protocols reached the peak performance (p<.001, ηp2 = 0.96). Although in the 10-12-14th minutes static and dynamic protocols’ performance values gradually reduced. However, they always were better compared to the control protocol (p<.001, ηp2 = 0.91-0.93-0.96, respectively).Conclusions: Adolescent soccer players can benefit from both static and dynamic PAP protocols before competition or halftime to improve performance.

In recent years, the EnodePro® device has been one of the most frequently used velocity sensors to track the bar velocity in resistance training, with the aim of providing load–velocity profiles. However, recent articles highlight a lack of reliability and validity in the estimated maximal strength, which can cause a serious health risk due to the overestimation of the bar velocity. With this study, we aimed to investigate whether imprecision in the measurement could explain the variance in this measurement error. Methods: The research question was evaluated by comparing the integrated velocities from the EnodePro® with the velocities from a high-resolution displacement sensor for the squat and bench press. The velocity was measured with loads corresponding to 30%, 50%, and 70% of the one-repetition maximum (1RM) in moderately trained participants (n = 53, f = 16, m = 37). Intraclass correlation coefficients (ICC) for agreement were supplemented by an exploration of the systematic bias and the random error (mean absolute error (MAE), mean absolute percentage error (MAPE)). Results: The results indicated movement specificity, with the ICC values for the squat ranging from 0.204 to 0.991 and with ICC = 0.678–0.991 for the bench press. Systematically higher velocities were reported by the EnodePro® sensor (p < 0.001–0.176), with an MAE = 0.036–0.198 m/s, which corresponds to an MAPE of 4.09–42.15%. Discussion: The EnodePro® seems to provide overly high velocities, which could result in the previously reported overestimation of the 1RM. Despite the validity problems of force/load–velocity profiles, we suggest evaluating the bar velocity with accurate measurement devices, which is, contrary to previous reports, not the case with the EnodePro®.

This study aims to analyze the influence of relative strength performance, determined by parallel back squats (REL SQ), on 30 m sprinting (LS) and on jumping performance (squat [SJ], countermovement [CMJ]) in a large sample (n = 492) of elite youth soccer players. The soccer players were divided into subgroups based on their strength performance: strength level 1 (0.0–0.5 REL SQ), strength level 2 (>0.5–1.0 REL SQ), strength level 3 (>1.0 to 1.5 REL SQ), strength level 4 (>1.5 to 2.0 REL SQ), and strength level 5 (>2.0 REL SQ). The results of this study show that REL SQ explains 45–53% (r = |0.67–0.73|) of the variance of SJ, CMJ, and LS for the total sample. Strength levels 2–4 showed similar coefficients of correlation in jumping performance (r = |0.42–0.55|) and strength levels 2 and 3 in sprint performance (r = |0.41|). The respective extreme strength levels showed lower coefficients of correlation with the sprinting and jumping performance variables (r = |0.11–0.29|). No coefficients could be calculated for strength level 5 because no athlete achieved an appropriate strength level (>2.0 REL SQ). The data from this study show a clear influence of REL SQ on sprint and jump performance, even in a large sample.

Background: The main goal of this study was to assess the acute effects of the intake of 9 and 11 mg/kg/ body mass (b.m.) of caffeine (CAF) on maximal strength and muscle endurance in athletes habituated to caffeine. Methods: The study included 16 healthy strength-trained male athletes (age = 24.2 ± 4.2 years, body mass = 79.5 ± 8.5 kg, body mass index (BMI) = 24.5 ± 1.9, bench press 1RM = 118.3 ± 14.5 kg). All participants were habitual caffeine consumers (4.9 ± 1.1 mg/kg/b.m., 411 ± 136 mg of caffeine per day). This study had a randomized, crossover, double-blind design, where each participant performed three experimental sessions after ingesting either a placebo (PLAC) or 9 mg/kg/b.m. (CAF-9) and 11 mg/kg/b.m. (CAF-11) of caffeine. In each experimental session, participants underwent a 1RM strength test and a muscle endurance test in the bench press exercise at 50% 1RM while power output and bar velocity were measured in each test. Results: A one-way repeated measures ANOVA revealed a significant difference between PLAC, CAF-9, and CAF-11 groups in peak velocity (PV) (p = 0.04). Post-hoc tests showed a significant decrease for PV (p = 0.04) in the CAF-11 compared to the PLAC group. No other changes were found in the 1RM or muscle endurance tests with the ingestion of caffeine. Conclusion: The results of the present study indicate that high acute doses of CAF (9 and 11 mg/kg/b.m.) did not improve muscle strength nor muscle endurance in athletes habituated to this substance.

This study assessed the test–retest reliability of athletic performance tests in a cohort of trained Norwegian female handball players, as well as a sub-analysis of the test–retest reliability for naturally menstruating players. Eighteen handball players (naturally menstruating: n = 8) completed performance test batteries on three separate occasions. The performance test battery included: a 1-repetition Smith machine back squat, maximal handgrip strength tests, counter-movement jumps, squat jumps, a modified agility T-test, and 15-m linear sprints. For the naturally menstruating players, the testing sessions were completed at three hormonally-distinct points within a menstrual cycle (i.e., early follicular, ovulation, and mid-luteal phases). Reliability statistics (intraclass correlations, standard error of measurement, minimum difference, and coefficient of variation) were calculated for each performance test. Good-to-excellent test–retest reliability was found for all performance measures (intraclass correlation2,1 point estimates = 0.82 to 0.94), although max squat jumps were somewhat lower (intraclass correlation2,1 = 0.75 [95 % confidence interval = 0.55, 0.88]). Subgroup analysis for naturally menstruating players also revealed consistently high reliability values for all tests (intraclass correlation2,1 point estimate = 0.83 to 0.74). These reliability data support the periodic use of selected athletic tests in routine handball assessments, in order to identify changes in sporting performance and monitor player progress. As test reliability does not appear to be influenced by the menstrual cycle phase, coaches and sports practitioners may schedule testing sessions for all athletes, without concern of a confounding effect from menstrual phases.

PurposeConsiderable debate exists as to whether increases in strength that occur with resistance exercise are the result of increases in muscle size. Most studies have attempted to answer this question using assessments of whole muscle size and voluntary muscle strength, but examining changes at the individual muscle fiber level may also provide some insight. The purpose of this meta-analysis was to compare adaptations at the whole muscle and individual fiber level.MethodsA meta-analysis was conducted in February, 2018 including all previously published papers and was analyzed using a random effects model.ResultsThere were no differences (p = 0.88) when comparing hypertrophy at the whole muscle (4.6%) and individual fiber level (7.0%), but significantly larger (p < 0.001) strength gains were observed at the whole muscle level (43.3%) relative to the individual fiber (19.5%). Additionally, there was an increase in the specific tension of type 1 muscle fibers (p = 0.013), but not type 2 muscle fibers (p = 0.23) which was driven by similar increases in strength (type 1: 17.5%, type 2A: 17.7%), despite differences in muscle size (type 1: 6.7%, type 2A: 12.1%).ConclusionThese results support the hypothesis that the neural adaptations play a large role in increasing isotonic whole muscle strength, but also demonstrate that an improvement in specific tension of type 1 muscle fibers is present. These results would suggest that some mechanism intrinsic to the muscle fiber, and independent of muscle growth, may also be contributing to strength increases in response to resistance exercise providing an avenue for future research.