Student Author Information

Kelsey Seery, University of LynchburgFollow

Location

Schewel 215

Access Type

Campus Access Only

Presentation Type

Oral Presentation

Start Date

April 2022

Department

Exercise Physiology

Abstract

Abstract: Research on the relationship between the sleep quality of collegiate women’s soccer players and game workload is limited. The purpose of this study was to find a correlation between sleep quality and game workload at the NCAA Division III level in women’s soccer. Twenty Division III women’s soccer players (Age: 20.0 + 1.4 BMI: 22.48 + 2.03 VO2max: 45.19 + 1.19) volunteered for this study and were equipped with Sports Performance Tracker (SPT) GPS units (SPT2) to track individual game workload. The day of each game players completed a modified Pittsburgh Sleep Quality Index (PSQI) to quantify and rate their sleep quality. Data is currently being analyzed via Pearson’s correlation between sleep and the following criteria: average hard running (HRUN) (m/min), average relative total distance (m/min), and average intensity (INT). Tertiles will be created based upon sleep quality to compare HRUN, average relative total distance, and INT cross sectionally with an ANCOVA analysis. We expect the results of this study to be valuable because we can better utilize sleep as a recovery tool and better equip athletes for competition.

Faculty Mentor(s)

Jason Cholewa Sean Collins Nicki Favero

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Apr 6th, 2:00 PM

The relationship between sleep quality and game workload in NCAA DIII women’s soccer players

Schewel 215

Abstract: Research on the relationship between the sleep quality of collegiate women’s soccer players and game workload is limited. The purpose of this study was to find a correlation between sleep quality and game workload at the NCAA Division III level in women’s soccer. Twenty Division III women’s soccer players (Age: 20.0 + 1.4 BMI: 22.48 + 2.03 VO2max: 45.19 + 1.19) volunteered for this study and were equipped with Sports Performance Tracker (SPT) GPS units (SPT2) to track individual game workload. The day of each game players completed a modified Pittsburgh Sleep Quality Index (PSQI) to quantify and rate their sleep quality. Data is currently being analyzed via Pearson’s correlation between sleep and the following criteria: average hard running (HRUN) (m/min), average relative total distance (m/min), and average intensity (INT). Tertiles will be created based upon sleep quality to compare HRUN, average relative total distance, and INT cross sectionally with an ANCOVA analysis. We expect the results of this study to be valuable because we can better utilize sleep as a recovery tool and better equip athletes for competition.