Relative anthropometric parameters as predictors of strength abilities of Olympic weightlifters

Valentin Panayotov; Krassimir Petkov; Rasho Makaveev

doi:10.58524/jcss.v5i1.958

Authors

Valentin Panayotov National Sports Academy, Bulgaria https://orcid.org/0000-0001-8148-4649
Krassimir Petkov National Sports Academy, Bulgaria https://orcid.org/0009-0005-4376-9594
Rasho Makaveev National Sports Academy, Bulgaria https://orcid.org/0000-0002-7670-9222

DOI:

https://doi.org/10.58524/jcss.v5i1.958

Keywords:

Anthropometric predictors, Body muscularity indexes, Back squat, Maximal strength, Olympic weightlifting

Abstract

Background: Body proportions and muscular development are closely linked to force production capacity, yet their application as predictive tools in Olympic weightlifting training and athlete selection remains insufficiently explored.

Aims: The study aimed to quantify the relationships between specific relative indexes of body muscularity and maximal force generated during two classic multi-joint resistance exercises – the back squat and the clean and jerk deadlift.

Methods: 17 athletes participated in the study, all of whom were national-level competitors. Linear regression equations were estimated between four relative body muscularity parameters (Height/Body mass³(BMH), Height/Shin circumference (HS), Height/Thigh circumference (HT), Height/Arm circumference (HA), and Height/Chest circumference (HC)) and maximal strength in back squat and clean and jerk deadlift.

Results: We calculated statistically significant Pearson correlation coefficients and linear regression coefficients between the studied relative body muscularity parameters and maximal muscle strength in the back squat and deadlift. The adjusted R-squared values ranged from 0.082 to 0.768 across the regression equations.

Conclusion: All studied relative parameters were statistically significant predictors of maximal strength in the deadlift and squat, with only 3 exceptions (BMH for the deadlift and BMH and HS for the squat). These results (in conjunction with the high adjusted R-squared values of the regressions) indicate that the constructed statistical models explain a relatively high proportion of the variation in the results. These findings can be used in training practice as guidelines for anthropometric changes to improve sports performance.

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