Comparisons between different methods of calculating dynamic strength index: Effect on training recommendations

An impulse-based dynamic strength index (iDSI) that constitutes time-dependent force expression in contrast to the common peak force-based DSI (fDSI) may be more insightful when considering training recommendations. However, a limitation of the iDSI is that any change in countermovement jump (CMJ) propulsion phase duration could affect longitudinal comparisons. A fixed duration (e.g., 250 ms) iDSI however could overcome this limitation. The purpose of the study was to determine the effect of different methods of calculating DSI (fDSI, iDSI matched, iDSI fixed) on the DSI value and resultant training prioritization. Thirty-seven team sport athletes (female = 13, male = 25, age = 22.2 ± 2.8 years, height = 174.4 ± 6.0 cm, mass = 74.9 ± 11.9 kg) performed three maximal effort CMJ and three isometric mid-thigh pull (IMTP) trials on force plates Fixed iDSI was identified from IMTP onset-250 ms, while matched iDSI was identified from IMTP onset-matched to CMJ propulsion phase duration. Participants were characterized using thresholds >0.80, 0.60-0.80 and <0.60 for maximal force, balanced, and dynamic force-based training, respectively. Mean ± SD of fDSI, fixed iDSI and matched iDSI were 0.82 ± 0.12, 0.88 ± 0.11 and 0.82 ± 0.11, respectively. Fixed iDSI was significantly and meaningfully greater than both fDSI and matched iDSI (p < 0.049, d > 0.408), with no differences between the latter (p = 1.000, d = 0.007). There were large intra-individual differences in the training recommendations, 44.7% of the recommendations were consistent between fDSI and matched iDSI and 55.3% were consistent for fDSI and fixed iDSI. In contrast, there was a greater consistency in training recommendations between fixed iDSI and matched iDSI (84.2%). Despite the consideration of time-dependent force expression in iDSI calculations there are meaningful differences in their observations. This difference should be considered when tracking physical performance over time, where a fixed iDSI could be preferential to ensure consistency.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-09-18
DOI
https://doi.org/10.1371/journal.pone.0331519
Citations
1
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
1.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparisons between different methods of calculating dynamic strength index: Effect on training recommendations

Paul Comfort, Stuart N. Guppy, Nicholas Joel Ripley, Jack Fahey
1 citations
PLoS ONE
Sports Performance and Training
1.72
article

Comparisons between different methods of calculating dynamic strength index: Effect on training recommendations

Paul Comfort, Stuart N. Guppy, Nicholas Joel Ripley, Jack Fahey
article en
1 citations

Abstract

An impulse-based dynamic strength index (iDSI) that constitutes time-dependent force expression in contrast to the common peak force-based DSI (fDSI) may be more insightful when considering training recommendations. However, a limitation of the iDSI is that any change in countermovement jump (CMJ) propulsion phase duration could affect longitudinal comparisons. A fixed duration (e.g., 250 ms) iDSI however could overcome this limitation. The purpose of the study was to determine the effect of different methods of calculating DSI (fDSI, iDSI matched, iDSI fixed) on the DSI value and resultant training prioritization. Thirty-seven team sport athletes (female = 13, male = 25, age = 22.2 ± 2.8 years, height = 174.4 ± 6.0 cm, mass = 74.9 ± 11.9 kg) performed three maximal effort CMJ and three isometric mid-thigh pull (IMTP) trials on force plates Fixed iDSI was identified from IMTP onset-250 ms, while matched iDSI was identified from IMTP onset-matched to CMJ propulsion phase duration. Participants were characterized using thresholds >0.80, 0.60-0.80 and <0.60 for maximal force, balanced, and dynamic force-based training, respectively. Mean ± SD of fDSI, fixed iDSI and matched iDSI were 0.82 ± 0.12, 0.88 ± 0.11 and 0.82 ± 0.11, respectively. Fixed iDSI was significantly and meaningfully greater than both fDSI and matched iDSI (p < 0.049, d > 0.408), with no differences between the latter (p = 1.000, d = 0.007). There were large intra-individual differences in the training recommendations, 44.7% of the recommendations were consistent between fDSI and matched iDSI and 55.3% were consistent for fDSI and fixed iDSI. In contrast, there was a greater consistency in training recommendations between fixed iDSI and matched iDSI (84.2%). Despite the consideration of time-dependent force expression in iDSI calculations there are meaningful differences in their observations. This difference should be considered when tracking physical performance over time, where a fixed iDSI could be preferential to ensure consistency.

PLoS ONEVol. 20(9)
Edith Cowan University (AU), University of Salford (GB)
Openalex Percentile: Top 14%
Sports Performance and Training
1.72
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.