Examining the Force-Traces of Countermovement Jumps and Standing Broad Jumps for Kinematic Coordination Indicators

Background/Objectives: Jumping is a common movement pattern, often used in testing for both performance monitoring and decision-making in return to sport. Current methods of assessing movement coordination are time-, technology- and expertise-dependent. The use of force–time curves to analyse the execution of the movement would provide an accessible and detailed analysis of movement. Methods: Thirty endurance runners and triathletes (18–40 years) completed five maximal countermovement jumps (CMJs) and five maximal standing broad jumps (SBJs). Participants were grouped (HIGH, MOD and LOW) according to the magnitude of the time interval between peak hip and peak knee extension velocity. A separate grouping according to the magnitude of the time interval between peak knee and peak ankle extension velocity was created. A one-way Statistical non-Parametric Mapping ANOVA, with alpha set at 0.05 and iterations at 10,000, was used to compare vertical ground reaction force (CMJ and SBJ), horizontal ground reaction force (SBJ) and resultant ground reaction force (SBJ) between the three hip–knee groups and a separate analysis for the three knee–ankle groups. Results: Significant differences were observed between time interval groups in both hip–knee coordination and knee–ankle coordination for both jump types (p < 0.001) at several regions of the force–time curves. Conclusions: The results suggest there is potential for statistical parametric mapping analysis to detect differences in movement coordination patterns from force curves. Further research is needed to help explain the differences observed in the curves for the kinematic groupings, to explore different combinations of hip–knee and knee–ankle kinematic patterns and to associate curve characteristics with performance indicators.

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Publication Details

Journal
Biomechanics
Published
2025-11-07
DOI
https://doi.org/10.3390/biomechanics5040095
Primary Topic
Sports Performance and Training
Type
article
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article

Examining the Force-Traces of Countermovement Jumps and Standing Broad Jumps for Kinematic Coordination Indicators

Anna Lorimer, Vernon G. Coffey, Hans‐Jürgen Schmidt
Biomechanics
Sports Performance and Training
article

Examining the Force-Traces of Countermovement Jumps and Standing Broad Jumps for Kinematic Coordination Indicators

Anna Lorimer, Vernon G. Coffey, Hans‐Jürgen Schmidt
article en

Abstract

Background/Objectives: Jumping is a common movement pattern, often used in testing for both performance monitoring and decision-making in return to sport. Current methods of assessing movement coordination are time-, technology- and expertise-dependent. The use of force–time curves to analyse the execution of the movement would provide an accessible and detailed analysis of movement. Methods: Thirty endurance runners and triathletes (18–40 years) completed five maximal countermovement jumps (CMJs) and five maximal standing broad jumps (SBJs). Participants were grouped (HIGH, MOD and LOW) according to the magnitude of the time interval between peak hip and peak knee extension velocity. A separate grouping according to the magnitude of the time interval between peak knee and peak ankle extension velocity was created. A one-way Statistical non-Parametric Mapping ANOVA, with alpha set at 0.05 and iterations at 10,000, was used to compare vertical ground reaction force (CMJ and SBJ), horizontal ground reaction force (SBJ) and resultant ground reaction force (SBJ) between the three hip–knee groups and a separate analysis for the three knee–ankle groups. Results: Significant differences were observed between time interval groups in both hip–knee coordination and knee–ankle coordination for both jump types (p < 0.001) at several regions of the force–time curves. Conclusions: The results suggest there is potential for statistical parametric mapping analysis to detect differences in movement coordination patterns from force curves. Further research is needed to help explain the differences observed in the curves for the kinematic groupings, to explore different combinations of hip–knee and knee–ankle kinematic patterns and to associate curve characteristics with performance indicators.

BiomechanicsVol. 5(4)
Bond University (AU)
Openalex Percentile: Top 57%
Sports Performance and Training
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