Purpose: To investigate differences between rating of perceived exertion (RPE) and percentage one-repetition maximum (1RM) load assignment in resistance-trained males (19–35 years) performing protocols with matched sets and repetitions differentiated by load-assignment.Methods: Participants performed squats then bench press 3x/weeks in a daily undulating format over 8-weeks. Participants were counterbalanced by pre-test 1RM then assigned to percentage 1RM (1RMG, n = 11); load-assignment via percentage 1RMs, or RPE groups (RPEG, n = 10); participant-selected loads to reach target RPE ranges. Ultrasonography determined pre and post-test pectoralis (PMT), and vastus lateralis muscle thickness at 50 (VLMT50) and 70% (VLMT70) femur-length.Results: Bench press (1RMG +9.64 ± 5.36; RPEG + 10.70 ± 3.30 kg), squat (1RMG + 13.91 ± 5.89; RPEG + 17.05 ± 5.44 kg) and their combined-total 1RMs (1RMG + 23.55 ± 10.38; RPEG + 27.75 ± 7.94 kg) increased (p < 0.05) in both groups as did PMT (1RMG + 1.59 ± 1.33; RPEG +1.90 ± 1.91 mm), VLMT50 (1RMG +2.13 ± 1.95; RPEG + 1.85 ± 1.97 mm) and VLMT70 (1RMG + 2.40 ± 2.22; RPEG + 2.31 ± 2.27 mm). Between-group differences were non-significant (p > 0.05). Magnitude-based inferences revealed 79, 57, and 72% chances of mean small effect size (ES) advantages for squat; ES 90% confidence limits (CL) = 0.50 ± 0.63, bench press; ES 90% CL = 0.28 ± 0.73, and combined-total; ES 90% CL = 0.48 ± 0.68 respectively, in RPEG. There were 4, 14, and 6% chances 1RMG had a strength advantage of the same magnitude, and 18, 29, and 22% chances, respectively of trivial differences between groups.Conclusions: Both loading-types are effective. However, RPE-based loading may provide a small 1RM strength advantage in a majority of individuals.

Zourdos, MC, Goldsmith, JA, Helms, ER, Trepeck, C, Halle, JL, Mendez, KM, Cooke, DM, Haischer, MH, Sousa, CA, Klemp, A, and Byrnes, RK. Proximity to failure and total repetitions performed in a set influences accuracy of intraset repetitions in reserve-based rating of perceived exertion. J Strength Cond Res 35(2S): S158–S165, 2021—The aim of this study was to assess the accuracy of predicting repetitions in reserve (RIR) intraset using the RIR-based rating of perceived exertion (RPE) scale. Twenty-five men (age: 25.3 ± 3.3 years, body mass: 89.0 ± 14.7 kg, height: 174.69 ± 6.7 cm, and training age: 4.7 ± 3.2 years) reported to the laboratory. Subjects performed a 1 repetition maximum (1RM) squat followed by one set to failure at 70% of 1RM. During the 70% set, subjects verbally indicated when they believed they were at a 5RPE (5RIR), 7RPE (3RIR), or 9RPE (1RIR), and then continued to failure. The difference between actual repetitions performed and participant-predicted repetitions was calculated as the RIR difference (RIRDIFF). The average load used for the 70% set was 123.10 ± 24.25 kg and the average repetitions performed were 16 ± 4. The RIRDIFF was lower (RPEs were more accurate) closer to failure (RIRDIFF at 9RPE = 2.05 ± 1.73; RIRDIFF at 7RPE = 3.65 ± 2.46; and RIRDIFF at 5RPE = 5.15 ± 2.92 repetitions). There were significant relationships between total repetitions performed and RIRDIFF at 5RPE (r = 0.65, p = 0.001) and 7RPE (r = 0.56, p = 0.004), but not at 9RPE (r = 0.01, p = 0.97). Thus, being farther from failure and performing more repetitions in a set were associated with more inaccurate predictions. Furthermore, a multiple linear regression revealed that more repetitions performed per set was a significant predictor of RIR prediction inaccuracy at the called 5 (p = 0.003) and 7 (p = 0.011) RPEs, while training age (p > 0.05) was not predictive of rating accuracy. These data indicate RIR predictions are improved during low to moderate repetition sets and when there is close proximity to failure.

Purpose: To examine the validity of 2 linear position transducers, the Tendo Weightlifting Analyzer System (TWAS) and Open Barbell System (OBS), compared with a criterion device, the Optotrak Certus 3-dimensional motion-capture system (OC3D). Methods: A total of 25 men (age, 25 [3] y; height, 174.0 [6.7] cm; body mass, 89.0 [14.7] kg; squat 1-repetition maximum [1RM], 175.8 [34.7] kg) with ≥2 y of resistance-training experience completed a back 1RM and 1 set to failure at 70% of 1RM. Average concentric velocity (ACV) and peak concentric velocity (PCV) were recorded by all 3 devices during the final warm-up set, all 1RM attempts, and every repetition during the 70% set. Results: In total, 575 samples were obtained. Bland–Altman plots, mountain plots, a 1-way analysis of variance, SEM, and intraclass correlation coefficients were used to analyze validity. The analysis of variance showed no difference (P = .089) between devices for ACV. However, for PCV, TWAS was significantly different (ie, inaccurate) from OC3D (P < .001) and OBS (P = .001), but OBS was similar (P = .412) to OC3D. For ACV, intraclass correlation coefficients were higher for OBS than for TWAS. Bland–Altman plots showed agreement for ACV for both devices against OC3D but large limits of agreement for PCV for both devices. Mountain plots showed valid ACV for both devices, however, but slightly greater ACV and PCV accuracy with OBS than TWAS. Conclusions: Both devices may provide valid ACV measurements, but some metrics suggest more accurate ACV with OBS vs TWAS. For PCV, neither device is particularly accurate; however, OBS seems to be more accurate than TWAS.

Cooke, DM, Haischer, MH, Carzoli, JP, Bazyler, CD, Johnson, TK, Varieur, R, Zoeller, RF, Whitehurst, M, and Zourdos, MC. Body mass and femur length are inversely related to repetitions performed in the back squat in well-trained lifters. J Strength Cond Res 33(3): 890–895, 2019—The purpose of this research note was to examine whether relationships existed between anthropometrics (body mass, body fat percentage [BF%], and femur length) and descriptive characteristics (age and sex) with repetitions performed to failure at 70% of 1 repetition maximum (1RM) in the back squat. Fifty-eight subjects (males = 43, females = 15; age: 23 ± 3 years, training age: 5.5 ± 2.5 years, body mass: 80.65 ± 16.34 kg, BF%: 10.98 ± 3.53%, and femur length: 47.1 ± 2.6 cm) completed a 1RM squat followed by one set to failure at 70% of 1RM. Total repetitions performed at 70% of 1RM were 14 ± 4 (range: 6–26). Bivariate correlations showed significant inverse relationships between body mass (r = −0.352, p = 0.003), BF% (r = −0.278, p = 0.014), and femur length (r = −0.265, p = 0.019), with repetitions performed. No significant relationships existed between age and sex (p > 0.05), with repetitions performed. All these variables entered into a standard multivariate regression. The model R 2 was 0.200, and body mass had the largest influence (p = 0.057) because relative importance analysis demonstrated body mass to contribute to 43.87% of the variance (of the R 2) in repetitions performed. No other variable was significant or approached significance (p > 0.05). Our results reveal that body mass, BF%, and femur length all are inversely related to repetitions performed at 70% of 1RM in the back squat.

Haischer, MH, Cooke, DM, Carzoli, JP, Johnson, TK, Shipherd, AM, Zoeller, RF, Whitehurst, M, and Zourdos, MC. Impact of cognitive measures and sleep on acute squat strength performance and perceptual responses among well-trained men and women. J Strength Cond Res 35(2S): S16–S22, 2021—This study assessed the efficacy of currently used assessments for sleep, anxiety, and stress in predicting 1-repetition maximum (1RM) back squat performance. Fifty-three men (age, 23 ± 3 years; body mass, 86.67 ± 13.93 kg; training age, 6.0 ± 2.5 years; 1RM = 163.5 ± 39.5 kg) and 15 women (age, 21 ± 1.5 years; body mass, 63.34 ± 9.6 kg; training age, 4 ± 1.5 years; 1RM = 81.5 ± 12.5 kg) participated. Subjects completed the Daily Analysis of Life Demands for Athletes (DALDA), the revised Competitive State Anxiety Inventory-2 (CSAI-2R), and Oviedo Sleep Questionnaire (OSQ) to evaluate stress, anxiety, and sleep, respectively. Subjects then completed the perceived self-efficacy (PSE) scale, to predict what loads they were 100, 75, and 50% confident that they could lift for a 1RM; then completed 1RM testing with rating of perceived exertion (RPE) and average concentric velocity (ACV) obtained on each attempt. The performance-dependent variable was calculated by subtracting the PSE responses from the actual 1RM (1RM-PSE difference). Bootstrapping with 1,000 replicate samples was used with linear regression to increased robustness of the statistical analyses, and 95% confidence intervals (CIs) were calculated. Hours of sleep was an inverse predictor of ACV (p = 0.014; 95% CI = 0.046 to−0.011) and a positive predictor of RPE (p = 0.005; 95% CI = 0.068–0.342). Furthermore, the hypersomnia subscale of the OSQ was a negative predictor of 1RM-PSE difference at 50% confidence (p = 0.028; 95% CI = −3.507 to −0.528), and CSAI-2R total score was a negative predictor of RPE at 1RM (p = 0.043; 95% CI = −0.041 to −0.003); however, the DALDA did not exhibit any significant relationships. These data highlight the importance of monitoring anxiety and sleep when assessing readiness for maximal strength performance.