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Related Experiment Video

Updated: Jun 20, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

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Published on: May 26, 2020

A Drone-Based Method to Measure Sprint Force-Velocity Profiles in 30-Meter Sprint Test - A Pilot Study.

Fahui Wang1, Christophe Hautier1, Lin Song2

  • 1Université Lyon 1, LIBM, UR 7424, Villeurbanne, France.

Journal of Sports Science & Medicine
|June 19, 2026
PubMed
Summary

A new drone system shows good reliability for tracking soccer player speed, but early acceleration data needs caution. Further algorithm improvements are needed for precise individual monitoring.

Keywords:
Computer visionaccelerationperformancereliability

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Area of Science:

  • Sports Science
  • Biomechanics
  • Performance Analysis

Background:

  • Accurate measurement of sprint performance is crucial in sports.
  • Traditional radar devices are common, but newer technologies like drone systems offer potential alternatives.
  • Evaluating the reliability and validity of these emerging technologies is essential for practical application.

Purpose of the Study:

  • To assess the test-retest reliability and concurrent validity of a drone system compared to a radar device for measuring sprint performance in collegiate soccer players.
  • To evaluate the agreement between the drone system and radar device across various force-velocity (F-V) variables.

Main Methods:

  • Seventeen male collegiate soccer players performed two maximal 30-meter sprints.
  • Test-retest reliability of the drone system was assessed using intraclass correlation coefficients (ICC), coefficient of variation (CV%), and standard error of measurement (SEM).
  • Concurrent validity was evaluated using linear mixed model (LMM) and Bland-Altman analysis to compare drone and radar data on F-V variables like maximal velocity (Vmax) and theoretical maximal horizontal force (F0).

Main Results:

  • The drone system demonstrated moderate to excellent test-retest reliability (0.59 ≤ ICC ≤ 0.95, CV% < 10%).
  • High practical agreement was found for maximal velocity (Vmax) and theoretical maximal velocity (V0) with minimal bias (≤ 1.12%) and narrow limits of agreement (< 10%).
  • Early-acceleration metrics (e.g., Amax, F0, Sfv) showed significant bias and wide limits of agreement (> 10%), indicating potential inaccuracies.

Conclusions:

  • The drone system is reliable and valid for monitoring the maximum speed phase of sprints.
  • Early-acceleration metrics derived from the drone system require cautious interpretation for individual athlete monitoring due to tracking instability.
  • Further optimization of drone system algorithms is recommended to improve accuracy during the initial acceleration phase.