Quantification of external load and determinants of performance in rugby
The simple reliance on the perception of effort and the duration of motor engagement during rugby training sessions or rugby matches is not sufficient to accurately quantify the training load of athletes, let alone their performance. Today, the use of GPS sensors integrating inertial measurement units (IMUs) allows for precise quantification of certain external training load indicators (distance covered, acceleration, speed, etc.) and provides information on match performance. However, the speeds reached vary according to positions and athletes. It is therefore necessary to adjust speed intensity thresholds to individualize the analysis of distances covered at certain intensity zones, which is rarely applied in the field. Moreover, there is no consensus on the method of determining the intensity zones necessary for match monitoring, and the link with performance remains to be established. Individually determined intensity zones using a field test will allow for the measurement of distance covered at certain speeds in a personalized manner. By combining this personalized data with other data collected using IMUs during matches, it will be possible to better characterize the external load and match performance. Recommendations based on advanced analyses of GPS and IMU data will enable better physical preparation of athletes to improve their individual performance.
The general objective of the project is to implement a method for monitoring the external training load and individual performance of identified rugby union athletes in Quebec by analyzing their movements on the field using GPS and IMU data.
The student will need to:
• Measure the athletes' maximum sprint speed.
• Record matches and training sessions over two seasons using a tool combining GPS and IMU.
• Develop metrics to measure external training load from GPS and IMU data during matches and training sessions.
• Objectively measure athletes' performance during matches.
• Determine the link between match performance and the external load metrics recorded during matches and training sessions.
Required knowledge
Rugby 7 or 15.
Sports science.
Signal processing.
Python or Matlab programming.
GPS and IMU embedded sensors.