Predicting Self-Reported Illness for Professional Team-Sport Athletes

Area of Science:

• Sports Medicine
• Exercise Physiology
• Athletic Performance

Background:

• Professional team-sport athletes face numerous stressors impacting health.
• Understanding illness incidence is crucial for athlete well-being and performance.
• Training load and well-being are key factors influencing athlete health.

Purpose of the Study:

• To identify contributing factors to illness incidence in professional team-sport athletes.
• To analyze the relationship between training load, self-reported illness, and well-being.
• To utilize self-report data for novel insights into athlete health.

Main Methods:

• Recruited 32 professional rugby league players.
• Collected training load, self-reported illness, and well-being data over 29 weeks.
• Used session rating of perceived exertion to determine internal training load.

Main Results:

• Increased internal training load (strain >2282 AU, weekly TL >2786 AU, monotony >0.78 AU) predicted illness risk.
• Reduced overall well-being (<7.25 AU) combined with increased training load contributed to illness.
• Predictive models identified key thresholds for increased illness susceptibility.

Conclusions:

• Self-report data effectively reveals interactions between stressors and illness susceptibility in athletes.
• Findings can inform coaching staff for better player monitoring and illness prevention.
• Implementing preventive measures based on training load and well-being data is recommended.