Skip to content

Normative Data

The values below are compiled from peer-reviewed studies and should be used as directional benchmarks, not absolute standards. Individual values vary with age, sex, sport, position, and training history.

PopulationMean (cm)Range (cm)
Untrained females25–3018–38
Untrained males35–4228–52
Trained team sport females32–4026–48
Trained team sport males42–5235–62
Elite volleyball / basketball50–6542–72
Elite track & field (jumpers)60–7552–85
PopulationMean (N/kg)
Recreational22–28
Trained team sport28–36
Elite strength/power36–48
LevelRSI-mod
Recreational0.2–0.35
Trained0.35–0.55
High performance0.55–0.80
Elite (jumpers/sprinters)0.80–1.2+
LevelRSI
Recreational0.8–1.2
Trained1.2–1.8
Elite1.8–2.5+
ClassificationAI (%)
Low asymmetry< 10
Moderate10–15
High (flag for review)> 15

Asymmetry thresholds are metric-dependent. Peak force AI >15% is more clinically significant than impulse AI >15%.

PopulationMean (N/kg)
Recreationally trained22–28
Strength-trained athletes28–36
Elite weightlifters / throwers36–50+

  • Linthorne, N.P. (2001). Analysis of standing vertical jumps using a force platform. American Journal of Physics.
  • McMahon, J.J. et al. (2018). Understanding the key phases of the countermovement jump force-time curve. Strength & Conditioning Journal.
  • Meylan, C. et al. (2017). Vertical jumps: biomechanical analysis and testing procedures. Strength & Conditioning Journal.
  • Gathercole, R. et al. (2015). Alternative countermovement-jump analysis to quantify acute neuromuscular fatigue. International Journal of Sports Physiology and Performance.
  • Dos’Santos, T. et al. (2017). The effect of limb dominance on change of direction biomechanics. Journal of Strength and Conditioning Research.