Injuries caused by overtraining are highly preventable, and there is an increasing demand for knowledge on how training load affects injury risk. However, there is little consensus on how to perform the analyses. In this project we will identify which methods are most suitable for this type of research.
Improving the Methodology of Training Load and Injury Research: An Analysis of Analyses
The overall aim of this PhD project is to identify and recommend suitable methods for research on the relationship between training load and injury risk
The PhD project consists of three subprojects.
Subproject I: Previous research have shown that not only can high training loads increase risk of injury, but possibly also too little training. In this subproject we will explore the non-linear relationship between training load and risk of injury.
Subproject II: Researchers in the field have used varying methods for dealing with missing data values. We will consider how missing values in sports data should be handled
Subproject III: In this subproject we will identify which statistical models are the most optimal choices in training load-injury research