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Purpose <p>This study aimed to describe athlete workload over the course of a four-year collegiate lacrosse career.</p> Methods <p>Workload was evaluated each day of training and games using global positioning system microtechnology. Total workload for each athlete was calculated for each season of each year for total distance, high-intensity distance, accelerations, decelerations, and sprints. Data were tabulated as absolute and relative workloads with absolute workload representing an individual athlete and relative workload representing that athlete’s percentage of team mean workload.</p> Results <p>The workload of the entire lacrosse team was collected over four years containing the full career of six athletes. Across the five workload variables analyzed, athletes either maintained a workload near team mean workload or demonstrated an increase in workload towards the end of their careers.</p> Conclusion <p>As careers progressed, the variation in athlete workload decreased, and athletes approached the team’s average workload. Microtechnology may be useful in monitoring athlete workload over the course of a career.</p>

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Quantification of Workload Across the Careers of Division I Women’s Lacrosse Athletes: A Case Series

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月19日

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  • Jordan Gentry,
  • Jennifer A. Bunn,
  • Bradley J. Myers

摘要

Purpose

This study aimed to describe athlete workload over the course of a four-year collegiate lacrosse career.

Methods

Workload was evaluated each day of training and games using global positioning system microtechnology. Total workload for each athlete was calculated for each season of each year for total distance, high-intensity distance, accelerations, decelerations, and sprints. Data were tabulated as absolute and relative workloads with absolute workload representing an individual athlete and relative workload representing that athlete’s percentage of team mean workload.

Results

The workload of the entire lacrosse team was collected over four years containing the full career of six athletes. Across the five workload variables analyzed, athletes either maintained a workload near team mean workload or demonstrated an increase in workload towards the end of their careers.

Conclusion

As careers progressed, the variation in athlete workload decreased, and athletes approached the team’s average workload. Microtechnology may be useful in monitoring athlete workload over the course of a career.