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Linear regressions predict workload relative to body weight in squat exercises for trained and untrained males, indicating a low risk of injury with accurate predictions.
PURPOSE: This study developed simple linear equations that predict a workload relative to body weight for specific repetition maximums (RMs) in squat exercises in trained and untrained males.METHODS: Eighteen trained (22.7±0.9 years, 175.4±2.6 cm, 78.1±2.6 kg, body mass index: 25.4±1.6 kg/m², lean body mass: 67.0±0.7 kg) and 18 untrained males (21.4±0.7 years, 176.4±3.5 cm, 74.5±3.5 kg, body mass index: 23.9±1.7 kg/m², lean body mass: 61.1±1.0 kg) performed five sets of half-back squats on a Smith machine. The workload for the first set was determined by the equations obtained from a pilot study, and subsequent workloads were adjusted following the number of repetitions performed at previous sets. Linear regressions using workloads and repetitions completed in each set were conducted to obtain the final equations. The Pearson correlation coefficient was performed to test correlation between workload and repetition. Mean absolute percentage errors (MAPEs) were calculated to test the equations’ prediction accuracy.RESULTS: The final equation (correlation and MAPE) for trained individuals was y=-0.0105x+1.4637 (r=-0.33, p=.002, MAPE=9.4%) and for untrained was y=-0.0136x+0.87 (r=-0.38, p=.0002, MAPE=20.9%; y=workload per body weight, x=repetition).CONCLUSIONS: A workload for a specific RM with body weight as an input would be simply calculated and applied in the field of strength and conditioning to save time and minimise injury risks.
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Seunghun Lee (2025) studied this question.
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