We assessed the accuracy of intraset repetitions in reserve (RIR) predictions on single-joint machine-based movements of trained and untrained men and women. Participants were 27 men ( M age = 22, SE = 0.6 years; M weight = 90.8, SE = 4.0 kg; M height = 182.3, SE = 1.4 cm; M training experience = 66, SE = 9 months) and 31 women ( M age = 20, SE = 0.4 years; M weight = 67.8, SE = 2.3 kg; M height = 167.6, SE = 1.1 cm; M training experience = 22, SE = 4 months). In one session, participants performed a five-repetition maximum (5RM) test on biceps curl, triceps pushdown, and seated row exercises; we then estimated one repetition maximum (1RM). Participants then performed four sets of each exercise, in a randomized order, to the point of momentary muscular failure at 72.5% of 1RM. During each set, participants indicated when they first perceived 5RIR and then predicted RIR on every repetition thereafter until failure. The difference between actual repetitions performed and predicted repetitions at each intraset prediction was determined to be the RIR difference (RIRDIFF). A 3-way repeated measures ANCOVA found that a 3-way interaction was not statistically significant ( p = 0.435) and no covariates of sex ( p = 0.917), training experience ( p = 0.462) nor experience rating RIR significantly affected RIRDIFF ( p = 0.462–0.917). There were significant main effects for the proximity to failure of the prediction and the set number ( p < 0.01) but not for exercise ( p = 0.688). Thus, intraset RIR predictions were more accurate when closer to failure and in later sets, but sex, training experience, and experience rating RIR did not significantly influence RIR prediction accuracy on machine-based single-joint exercises.

The purpose of this investigation was to determine if average concentric velocity (ACV) of a single repetition at 70% of one-repetition maximum (1RM), ACV of the first repetition of a set to failure at 70% of 1RM, or the velocity loss during the set could predict the number of repetitions performed in the back squat. Fifty-six resistance-trained individuals participated in the study (male = 41, age = 23 ± 3 yrs, 1RM = 162.0 ± 40.0 kg; female = 15, age = 21 ± 2 yrs, 1RM = 81.5 ± 12.5 kg). After 1RM testing, participants performed single repetition sets with 70% of 1RM and a set to failure with 70% of 1RM. ACV was recorded on all repetitions. Regression model comparisons were performed, and Akaike Information Criteria (AIC) and Standard Error of the Estimate (SEE) were calculated to determine the best model. Neither single repetition ACV at 70% of 1RM (R² = 0.004, p = 0.637) nor velocity loss (R² = 0.011, p = 0.445) were predictive of total repetitions performed in the set to failure. The simple quadratic model using the first repetition of the set to failure () was identified as the best and most parsimonious model (R2 = 0.259, F = 9.247, p < 0.001) due to the lowest AIC value (311.086). A SEE of 2.21 repetitions was identified with this model. This average error of ~2 repetitions warrants only cautious utilization of this method to predict total repetitions an individual can perform in a set, with additional autoregulatory or individualization strategies being necessary to finalize the training prescription.

In this study we investigated whether the accuracy of intraset repetitions in reserve (RIR) predictions changes over time. Nine trained men completed three bench press training sessions per week for 6 weeks (following a 1-week familiarization). The final set of each session was performed until momentary muscular failure, with participants verbally indicating their perceived 4RIR and 1RIR. RIR prediction errors were calculated as raw differences (RIRDIFF), with positive and negative values indicating directionality, and absolute RIRDIFF (absolute value of raw RIRDIFF) indicating error scores. We constructed mixed effect models with time (i.e., session) and proximity to failure as fixed effects, repetitions as a covariate, and random intercepts per participant to account for repeated measures, with statistical significance set at p ≤ .05. We observed a significant main effect for time on raw RIRDIFF ( p < .001), with an estimated marginal slope of −.077 repetitions, indicating a slight decrease in raw RIRDIFF over time. Further, the estimated marginal slope of repetitions was −.404 repetitions, indicating a decrease in raw RIRDIFF as more repetitions were performed. There were no significant effects on absolute RIRDIFF. Thus, RIR rating accuracy did not significantly improve over time, though there was a greater tendency to underestimate RIR in later sessions and during higher repetition sets.

This investigation employed a between-participant design comparing acute and chronic changes in brain-derived neurotrophic factor (BDNF), cathepsin B (CatB), insulin-like growth factor-1 (IGF-1), and interleukin-6 (IL-6) across four resistance training (RT) protocols differing in proximity to failure, while also examining inter-biomarker correlations. Thirty-eight resistance-trained men completed an eight-week intervention, training three times per week, allocated to one of four groups based on repetitions-in-reserve (RIR): 4–6 RIR, 1–3 RIR, 0–3 RIR, and 0 RIR. Serum was collected immediately before and after training on day 1 of weeks 1 and 7. The analysis revealed the main effects of Session for BDNF and IL-6 (posterior probability > 99%), indicating exercise-induced elevation independent of proximity to failure. Additionally, CatB demonstrated a Session × Week interaction (posterior probability > 99%), indicating a difference in the acute response between week 7 and week 1. No compelling evidence emerged for IGF-1 effects, and inter-biomarker correlations were weak and inconsistent. Notably, this is the first investigation to demonstrate RT-induced transient CatB elevation. These findings suggest that exercise-induced neuroprotective biomarker responses may be achieved while training relatively far from failure, potentially avoiding the neuromuscular fatigue, injury risk, and recovery demands associated with failure training.

Strength and conditioning coaches often recommend athletes perform loaded jumps with an external load that maximizes peak power output to improve performance. However, there is debate regarding the training load that maximizes acute total body power, and power at individual lower extremity joints. The purpose of this study was to investigate lower extremity kinetic and kinematic variables across a spectrum of loads during jump squats using a hexagonal barbell. Participants performed jumps with a range of loads from 10% to 60% of hexagonal barbell deadlift estimated 1-repetition maximum (e1RM), as well as an unloaded countermovement jump. Using cameras and force plates, lower extremity angles, velocities, moments, powers, as well as total body power, were assessed for each jump. As load increased, there was a decrease in power at the total body level and the hip, but ankle power increased. All joint moment magnitudes increased with load, and flexion angle and velocity at the hip and knee decreased with load. Results suggest that increasing load impacts kinetic and kinematic variables and alters the jumping task, and that the majority of these changes occur when loading exceeds approximately 20-30% 1RM. Further, knee kinetics measures were most strongly related to total body power.