Biology of Sport
eISSN: 2083-1862
ISSN: 0860-021X
Biology of Sport
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abstract:
Original paper

Do small samples bias the correlation between strength and jump performance? Multivariate insights into age and sex amidst strength saturation: an analysis of 1,544 participants from different sports

Michael Keiner
1
,
Konstantin Warneke
2
,
Andre Sander
3
,
Hagen Hartmann
1
,
Carl Maximilian Wagner
1
,
Björn Kadlubowski
1
,
Andreas Wittke
4
,
Torsten Brauner
5
,
Andreas Konrad
6
,
David G. Behm
7
,
Klaus Wirth
8

  1. Department of Training and Exercise Science, German University of Health & Sport, Ismaning, Germany
  2. Department of Movement Sciences, University of Klagenfurt, Klagenfurt am Wörthersee, Austria
  3. German Luge and Bobsled Federation, Berchtesgaden, Germany
  4. Department of Sport Science, German University of Health & Sport, Ismaning, Germany
  5. Department of Biomechanics, German University of Health & Sport, Ismaning, Germany
  6. Institute of Human Movement Science, Sport and Health, University of Graz, Graz, Austria
  7. School of Human Kinetics and Recreation, Memorial University of Newfoundland, St. John’s, Canada
  8. Department of Training and Exercise Science, University of Applied Sciences Wiener Neustadt, Austria
Biol Sport. 2025;42(2):3–11
Online publish date: 2024/08/30
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Maximal strength is considered a fundamental aspect of athletic performance across a wide range of sports and is also needed for a range of activities of daily life. Yet, compared to males there are fewer publications examining females, with most showing similar coefficients of correlation between dynamic strength and different athletic performances. In both, males and females, results are biased by mostly small sample sizes (sample bias) leading to a fluctuation around the true correlation coefficient of the entire population. This crosssectional analysis involving 1544 participants employed multivariate and correlative analyses to clarify the importance of maximum strength in the parallel back squats on the jump performance controlling for variables such as type of sport, sex, age, and performance level. The analysis revealed two principal components that reflect distinct types of variability within the dataset: the first, primarily associated with performance capabilities, accounts for 58.45% of the variance, while the second, emphasizing demographic differences, accounts for a considerably lower variance of 25.08%. The correlation analyses in this study identified maximal strength as a significant factor influencing jumping performance, accounting for 48 53% of the variance in jump height. The analysis presents a saturation curve, with potential diminishing returns at higher strength levels. Age and sex had little to no effect on overall correlation coefficients. The overall correlation coefficients and the analyses for the subgroups (by sport and performance level) can differ considerably, which can be explained (mathematically) by the artificial formation of clusters, homogeneous subject groups, or small sample sizes.
keywords:

1RM, Relative strength, Squat, Squat jump, Countermovement jump

 
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