Validity and within-device reliability of the Metric application for assessing barbell velocity and displacement

This study evaluated the validity and within-device reliability of the Metric smartphone application compared to a linear position transducer (LPT). Twenty-five resistance-trained participants (19 male, 6 female) completed incremental loading one-repetition maximum (1RM) assessments in the back squat, bench press, and deadlift. Mean concentric velocity (MCV) and displacement (CD) were measured simultaneously by two Metric devices and one GymAware LPT. The Metric application detected 94.3% of repetitions (F1-score: 0.971) compared to GymAware's 99.5% (F1-score: 0.997). Within-device reliability of Metric varied by exercise: highest in squat (MCV: ICC = 0.994, CV = 3.83%, SDC = 0.05 m/s [4.27% of 1RM]; CD: ICC = 0.991, CV = 1.53%, SDC = 0.02 m), then bench press (MCV: ICC = 0.981, CV = 7.57%, SDC = 0.08 m/s [6.38% of 1RM]; CD: ICC = 0.974, CV = 3.53%, SDC = 0.02 m), and lowest in deadlift (MCV: ICC = 0.941, CV = 13.29%, SDC = 0.13 m/s [14.05% of 1RM]; CD: ICC = 0.753, CV = 27.16%, SDC = 0.10 m). However, Metric did not meet our predetermined reliability criteria for velocity trackers (ICC ≥ 0.997, CV ≤ 3.5%). Substantial-to-perfect agreement between Metric and GymAware was found for squat MCV (CCC = 0.981–0.993), but only poor-to-moderate agreement for bench press and deadlift MCV (CCC = 0.866–0.946), and poor agreement across all exercises for CD (CCC < 0.768). While Metric offers a cost-effective and user-friendly alternative to LPTs, it cannot currently be recommended for research or practice where high precision is required.

Authors

Institutions

Publication Details

Journal
International Journal of Sports Science & Coaching
Published
2025-11-24
DOI
https://doi.org/10.1177/17479541251391967
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 within-device reliability of the Metric application for assessing barbell velocity and displacement

Christian Houmann Amdi, Matt Brughelli, Nathan Fane Tanira Puppyn, Stuart Hofmeyr
International Journal of Sports Science & Coaching
Sports Performance and Training
article

Validity and within-device reliability of the Metric application for assessing barbell velocity and displacement

Christian Houmann Amdi, Matt Brughelli, Nathan Fane Tanira Puppyn, Stuart Hofmeyr
article en

Abstract

This study evaluated the validity and within-device reliability of the Metric smartphone application compared to a linear position transducer (LPT). Twenty-five resistance-trained participants (19 male, 6 female) completed incremental loading one-repetition maximum (1RM) assessments in the back squat, bench press, and deadlift. Mean concentric velocity (MCV) and displacement (CD) were measured simultaneously by two Metric devices and one GymAware LPT. The Metric application detected 94.3% of repetitions (F1-score: 0.971) compared to GymAware's 99.5% (F1-score: 0.997). Within-device reliability of Metric varied by exercise: highest in squat (MCV: ICC = 0.994, CV = 3.83%, SDC = 0.05 m/s [4.27% of 1RM]; CD: ICC = 0.991, CV = 1.53%, SDC = 0.02 m), then bench press (MCV: ICC = 0.981, CV = 7.57%, SDC = 0.08 m/s [6.38% of 1RM]; CD: ICC = 0.974, CV = 3.53%, SDC = 0.02 m), and lowest in deadlift (MCV: ICC = 0.941, CV = 13.29%, SDC = 0.13 m/s [14.05% of 1RM]; CD: ICC = 0.753, CV = 27.16%, SDC = 0.10 m). However, Metric did not meet our predetermined reliability criteria for velocity trackers (ICC ≥ 0.997, CV ≤ 3.5%). Substantial-to-perfect agreement between Metric and GymAware was found for squat MCV (CCC = 0.981–0.993), but only poor-to-moderate agreement for bench press and deadlift MCV (CCC = 0.866–0.946), and poor agreement across all exercises for CD (CCC < 0.768). While Metric offers a cost-effective and user-friendly alternative to LPTs, it cannot currently be recommended for research or practice where high precision is required.

International Journal of Sports Science & Coaching
Auckland University of Technology (NZ)
Openalex Percentile: Top 54%
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.