Current research ideologies in sport science allow for the possibility of investigators producing statistically significant results to help fit the outcome into a predetermined theory. Additionally, under the current Neyman-Pearson statistical structure, some argue that null hypothesis significant testing (NHST) under the frequentist approach is flawed, regardless. For example, a p-value is unable to measure the probability that the studied hypothesis is true, unable to measure the size of an effect or the importance of a result, and unable to provide a good measure of evidence regarding a model or hypothesis. Many of these downfalls are key questions researchers strive to answer following an investigation. Therefore, a shift towards a magnitude-based inference model, and eventually a fully Bayesian framework, is thought to be a better fit from a statistical standpoint and may be an improved way to address biases within the literature. The goal of this article is to shed light on the current research and statistical shortcomings the field of sport science faces today, and offer potential solutions to help guide future research practices.

The purpose of the study was to compare the physiological responses of skeletal muscle to a resistance training (RT) program using repetition maximum (RM) or relative intensity (RI_SR). Fifteen well-trained males underwent RT 3 d·wk⁻¹ for 10 weeks in either an RM group (n = 8) or RI_SR group (n = 7). The RM group achieved a relative maximum each day, while the RI_SR group trained based on percentages. The RM group exercised until muscular failure on each exercise, while the RI_SR group did not reach muscular failure throughout the intervention. Percutaneous needle biopsies of the vastus lateralis were obtained pre-post the training intervention, along with ultrasonography measures. Dependent variables were: Fiber type-specific cross-sectional area (CSA); anatomical CSA (ACSA); muscle thickness (MT); mammalian target of rapamycin (mTOR); adenosine monophosphate protein kinase (AMPK); and myosin heavy chains (MHC) specific for type I (MHC1), type IIA (MHC2A), and type IIX (MHC2X). Mixed-design analysis of variance and effect size using Hedge’s g were used to assess within- and between-group alterations. RI_SR statistically increased type I CSA (p = 0.018, g = 0.56), type II CSA (p = 0.012, g = 0.81), ACSA (p = 0.002, g = 0.53), and MT (p < 0.001, g = 1.47). RI_SR also yielded a significant mTOR reduction (p = 0.031, g = −1.40). Conversely, RM statistically increased only MT (p = 0.003, g = 0.80). Between-group effect sizes supported RI_SR for type I CSA (g = 0.48), type II CSA (g = 0.50), ACSA (g = 1.03), MT (g = 0.72), MHC2X (g = 0.31), MHC2A (g = 0.87), and MHC1 (g = 0.59); with all other effects being of trivial magnitude (g < 0.20). Our results demonstrated greater adaptations in fiber size, whole-muscle size, and several key contractile proteins when using RI_SR compared to RM loading paradigms.

The current investigation was an examination of the repetition-to-repetition magnitudes and changes in kinetic and kinematic characteristics of the back squat using accentuated eccentric loading (AEL) and cluster sets. Trained male subjects (age = 26.1 ± 4.1 years, height = 183.5 ± 4.3 cm, body mass = 92.5 ± 10.5 kg, back squat to body mass ratio = 1.8 ± 0.3) completed four load condition sessions, each consisting of three sets of five repetitions of either traditionally loaded straight sets (TL), traditionally loaded cluster sets (TLC), AEL cluster sets (AEC), and AEL straight sets where only the initial repetition had eccentric overload (AEL1). Eccentric overload was applied using weight releasers, creating a total eccentric load equivalent to 105% of concentric one repetition maximum (1RM). Concentric load was 80% 1RM for all load conditions. Using straight sets (TL and AEL1) tended to decrease peak power (PP) (d = −1.90 to −0.76), concentric rate of force development (RFD_CON) (d = −1.59 to −0.27), and average velocity (MV) (d = −3.91 to −1.29), with moderate decreases in MV using cluster sets (d = −0.81 to −0.62). Greater magnitude eccentric rate of force development (RFD_ECC) was observed using AEC at repetition three (R3) and five (R5) compared to all load conditions (d = 0.21–0.65). Large within-condition changes in RFD_ECC from repetition one to repetition three (∆REP_1–3) were present using AEL1 (d = 1.51), demonstrating that RFD_ECC remained elevated for at least three repetitions despite overload only present on the initial repetition. Overall, cluster sets appear to permit higher magnitude and improved maintenance of concentric outputs throughout a set. Eccentric overload with the loading protocol used in the current study does not appear to potentiate concentric output regardless of set configuration but may cause greater RFD_ECC compared to traditional loading.

The aim of this study was to evaluate the level of agreement in measuring back squat kinematics between an inertial measurement unit (IMU) and a 3D motion capture system (3DMOCAP). Kinematic variables included concentric peak velocity (CPV), concentric mean velocity (CMV), eccentric peak velocity (EPV), eccentric mean velocity (EMV), mean propulsive velocity (MPV), and POP-100: a proprietary variable. Sixteen resistance-trained males performed an incrementally loaded one repetition maximum (1RM) squat protocol. A series of Pearson correlations, 2 × 4 RM ANOVA, Cohen’s d effect size differences, coefficient of variation (CV), and standard error of the estimate (SEE) were calculated. A large relationship existed for all variables between devices (r = 0.78–0.95). Between-device agreement for CPV worsened beyond 60% 1RM. The remaining variables were in agreement between devices with trivial effect size differences and similar CV magnitudes. These results support the use of the IMU, regardless of relative intensity, when measuring EMV, EPV, MPV, and POP-100. However, practitioners should carefully select kinematic variables of interest when using the present IMU device for velocity-based training (VBT), as certain measurements (e.g., CMV, CPV) do not possess practically acceptable reliability or accuracy. Finally, the IMU device exhibited considerable practical data collection concerns, as one participant was completely excluded and 13% of the remaining attempts displayed obvious internal error.

The purpose of the current study was (1) to examine the differences between standing and lying measures of vastus lateralis (VL), muscle thickness (MT), pennation angle (PA), and cross-sectional area (CSA) using ultrasonography; and (2) to explore the relationships between lying and standing measures with isometric and dynamic assessments of force production—specifically peak force, rate of force development (RFD), impulse, and one-repetition maximum back squat. Fourteen resistance-trained subjects (age = 26.8 ± 4.0 years, height = 181.4 ± 6.0 cm, body mass = 89.8 ± 10.7 kg, back squat to body mass ratio = 1.84 ± 0.34) agreed to participate. Lying and standing ultrasonography images of the right VL were collected following 48 hours of rest. Isometric squat assessments followed ultrasonography, and were performed on force platforms with data used to determine isometric peak force (IPF), as well as RFD and impulse at various time points. Forty-eight hours later, one-repetition maximum back squats were performed by each subject. Paired-samples t-tests revealed statistically significant differences between standing and lying measurements of MT (p < 0.001), PA (p < 0.001), and CSA (p ≤ 0.05), with standing values larger in all cases. Further, standing measures were correlated more strongly and abundantly to isometric and dynamic performance. These results suggest that if practitioners intend to gain insight into strength-power potential based on ultrasonography measurements, performing the measurement collection with the athlete in a standing posture may be preferred.

The purpose of the current study was two-fold: (1) To examine the variation in velocity and power with increasing intensity in the back squat among subjects; and (2) To explore individual subject characteristics as possible explanations for variations of velocity in the back squat. Fourteen recreationally trained male subjects with experience in the back squat agreed to participate in the study (age = 25.0 ± 2.6 years, height = 178.9 ± 8.1 cm, body mass = 88.2 ± 15.8 kg). One-repetition maximums (1RM) were performed for each subject on force platforms with four linear position transducers attached to the barbell. The 1RM assessment was immediately preceded by warm-up sets at 65%, 75%, 85%, and 95% of estimated 1RM for 5, 3, 2, and 1 repetitions, respectively. Mean concentric velocity (MCV) and mean power were recorded for each intensity condition and were analyzed using Pearson correlation to determine the relationship between each variable and relative intensity (%1RM). Statistically significant negative relationships existed between %1RM and MCV (r = −0.892) and mean power (r = −0.604). Between-subject coefficient of variation tended to increase as %1RM increased for both MCV and mean power. These results suggest that MCV is superior to mean power as an indicator of relative intensity in the back squat. Additionally, the between-subject variation observed at higher intensities for MCV and mean power support the use of velocity ranges by strength and conditioning coaches.