Predicting Athlete Workload in Women's Rugby Sevens Using GNSS Sensor Data, Contact Count and Mass

Area of Science:

• Sports Science
• Biomechanics
• Performance Analysis

Background:

• Session rating of perceived exertion (sRPE) is a common athlete load monitoring tool, but quantifying sport-specific factors remains challenging.
• Existing global navigation satellite system (GNSS) methods for load quantification may not accurately reflect female athlete loads in sports like rugby.
• Rugby sevens involves high-speed running, physical contact, and acceleration/deceleration, all contributing to athlete load.

Purpose of the Study:

• To investigate the specific contributions of mass, physical contact, and speed-based accelerations/decelerations to athlete load in women's rugby sevens.
• To develop a more accurate model for quantifying athlete load in women's rugby sevens using GNSS data and other relevant metrics.
• To address the limitations of current methods in accurately assessing female athlete workloads.

Main Methods:

• Analysis of data from 99 international women's rugby sevens matches involving 19 full-time athletes.
• Utilized global navigation satellite system (GNSS) measures, session rating of perceived exertion (sRPE), athlete mass, and contact counts.
• Employed a linear mixed-model regression to evaluate the relationships between these variables and sRPE.

Main Results:

• The developed model identified significant contributions from low-speed decelerations (at both low and high speeds), athlete mass, distance covered, and contact count.
• These factors collectively explained 48.7% of the global variance in session rating of perceived exertion (sRPE).
• The findings highlight the importance of specific movement patterns and physical attributes in determining athlete load.

Conclusions:

• Integrating acceleration/deceleration data from GNSS sensors, alongside athlete mass and contact counts, offers a novel and more accurate approach to quantifying athlete load in women's rugby sevens.
• This refined methodology improves upon existing load monitoring tools by better capturing the unique demands of the sport for female athletes.
• The study provides a foundation for more precise training load management and injury prevention strategies in women's rugby sevens.