Predicting self‐reported injury status among runners training for the New York City Marathon

Key Points

• The research aims to predict injury status among runners training for the New York City Marathon using machine learning techniques.
• Utilized survey and running activity data for analysis.
• Focused on runners not already changing their training due to injuries.
• Employed machine learning for predictive modeling.
• Showed low discriminatory power in predicting weekly running injuries.
• Highlighted the significance of prior week's injury status for predictions.
• Indicated the need for larger sample sizes and additional predictors for better accuracy.