Correlations between horizontal jump and sprint acceleration and maximal speed performance: a systematic review and meta-analysis

Objectives

The purpose of this study is to determine the associations between horizontal jump and sprint acceleration, as well as maximal speed performance.

Methods

A systematic literature search was performed using PubMed, MEDLINE (EBSCOhost), and Web of Science. The studies that were included in this review must meet the following criteria: (1) well-trained individuals over the age of 18 years old; (2) Pearson's correlation coefficients between sprint time and horizontal jump distance were provided; (3) the sprint distance was limited to 0-100 m. The quality of the studies was assessed using a modified version of the Downs and Black Quality Index test. A random-effects model was used to determine the effect sizes, and heterogeneity between studies was examined using the Q statistic and I².

Results

From the identified 2,815 studies, 27 studies were included in this study (two from reference lists). The sprint time of the sprint acceleration phase was moderately and negatively correlated with the standing long jump (r =  - 0.45, z = 7.48, p < 0.001), single leg standing long jump (r =  - 0.48, z = 3.49, p < 0.001) and horizontal drop jump distance (r =  - 0.48, z = 3.49, p < 0.001), and was largely and negatively correlated with multiple jump distance (r =  - 0.69, z = 6.02, p < 0.001). Out of five studies assessed the standing triple jump, three studies reported significant positive association with the sprint acceleration performance. The sprint time of maximal speed phase was very largely and negatively associated with standing long jump distance (r =  - 0.73, z = 4.44, p < 0.001) and multiple jump distance (r =  - 0.76, z = 6.86, p < 0.001).

Conclusions

This review indicates the moderate to very large associations between horizontal jump and sprint acceleration and maximal speed performance, and the highest magnitude of associations between them is found in the multiple jump. Moreover, compared to the sprint acceleration performance, there are greater associations between maximal speed performance and standing long jump and multiple jump distance.

Kinetic time-curves can classify individuals in distinct levels of drop jump performance

This study examined whether analysing kinetic features of drop jumps (DJ) as one-dimensional biomechanical curves can reveal specific patterns that are consistent and can cluster DJ performance. Hierarchical clustering analysis on DJ from 40 cm data performed by 128 physically active male participants (23.0 ± 4.5 yrs, 1.84 ± 0.07 m, 79.1 ± 10.8 kg) was performed on the derived time-normalised force, power and vertical stiffness curves to unmask the underlying patterns and to explore the dissimilarities identified from the subgroup (cluster) analysis. Results revealed poor, average and top DJ performers. Top performers exhibited larger peak force, power and vertical stiffness compared to the other two groups, and the poor performers had lower values compared to the average performers (p < .05). The time curves of force, power and vertical stiffness exhibited between cluster dissimilarities from ~25% to ~70%, and ~20% to 40% plus ~55% to 70% from the beginning of the ground contact, respectively. The force and power time-curves distinguished DJ ability similarly since they shared 69% of the cases in the top performers' cluster. The content of cases (membership) for vertical stiffness was different from the membership for the force and power time-curve clusters. In conclusion, stiffness should be considered during plyometric training, but does not distinctly define DJ performance.