Validity and reliability of the my jump® 2 app to measure vertical jump performance in beach volleyball players

This study aimed to assess the validity and reliability of the My Jump® 2 app for measuring vertical jump height on sand. We hypothesized that the app would demonstrate good reliability (ICC > 0.75) and acceptable agreement (bias < 2 cm, CCC ≥ 0.95) with 2D video analysis. Twenty-six male beach volleyball players performed four types of vertical jumps (CMJ, SJ, AJ, BJ) on sand. Jump height was measured using the My Jump® 2 app and 2D video analysis (Kinovea). Reliability was assessed with ICC(2,1), SEM, and MDC95. Validity was assessed using Pearson correlation, Lin’s Concordance Correlation Coefficient (CCC), Bland-Altman analysis (bias and 95 % limits of agreement), and linear regression to evaluate proportional bias and standard error of estimate (SEE). ICCs ranged from 0.447 to 0.594. SEM varied from 4.68 to 8.39 cm and MDC95 ranged from 12.98 to 23.24 cm. Pearson correlations were high ( r = 0.713–0.832), but CCC values indicated only moderate agreement (CCC = 0.487–0.632). The My Jump® 2 app consistently overestimated jump height, with bias ranging from 5.38 to 6.91 cm. Limits of agreement ranged from -11.33 to 22.08 cm. Linear regressions revealed proportional bias in all jump types. My Jump® 2 showed good reliability but limited agreement with the reference method on sand. While the app may be suitable for monitoring performance trends, its absolute accuracy is compromised under these conditions and should be interpreted with caution.

Authors

Institutions

Publication Details

Journal
Apunts Sports Medicine
Published
2025-10-19
DOI
https://doi.org/10.1016/j.apunsm.2025.100497
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validity and reliability of the my jump® 2 app to measure vertical jump performance in beach volleyball players

Rodrigo Ghedini Gheller, Ewertton de Souza Bezerra, João Otacílio Libardoni dos Santos, Leandro Augusto Pereira de Souza et al.
Apunts Sports Medicine
Sports Performance and Training
article

Validity and reliability of the my jump® 2 app to measure vertical jump performance in beach volleyball players

Rodrigo Ghedini Gheller, Ewertton de Souza Bezerra, João Otacílio Libardoni dos Santos, Leandro Augusto Pereira de Souza, J. Nunes, Geovanna de Paula Martins de Souza
article en

Abstract

This study aimed to assess the validity and reliability of the My Jump® 2 app for measuring vertical jump height on sand. We hypothesized that the app would demonstrate good reliability (ICC > 0.75) and acceptable agreement (bias < 2 cm, CCC ≥ 0.95) with 2D video analysis. Twenty-six male beach volleyball players performed four types of vertical jumps (CMJ, SJ, AJ, BJ) on sand. Jump height was measured using the My Jump® 2 app and 2D video analysis (Kinovea). Reliability was assessed with ICC(2,1), SEM, and MDC95. Validity was assessed using Pearson correlation, Lin’s Concordance Correlation Coefficient (CCC), Bland-Altman analysis (bias and 95 % limits of agreement), and linear regression to evaluate proportional bias and standard error of estimate (SEE). ICCs ranged from 0.447 to 0.594. SEM varied from 4.68 to 8.39 cm and MDC95 ranged from 12.98 to 23.24 cm. Pearson correlations were high ( r = 0.713–0.832), but CCC values indicated only moderate agreement (CCC = 0.487–0.632). The My Jump® 2 app consistently overestimated jump height, with bias ranging from 5.38 to 6.91 cm. Limits of agreement ranged from -11.33 to 22.08 cm. Linear regressions revealed proportional bias in all jump types. My Jump® 2 showed good reliability but limited agreement with the reference method on sand. While the app may be suitable for monitoring performance trends, its absolute accuracy is compromised under these conditions and should be interpreted with caution.

Apunts Sports MedicineVol. 61(229)
Universidade Federal do Amazonas (BR)
Openalex Percentile: Top 61%
Sports Performance and Training
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.