Research Project
Researchers: Dr. Bahadorreza Ofoghi (Managed by) , Ms Tamara Urech
Brief description This project focuses on using statistical and machine learning techniques for analyzing triathlon performance data with the aim of understanding medaling patterns. Triathlon is a high profile multi-component sport which requires strategic understanding and planning with respect to each of the three sports involved, i.e., swimming, cycling, and running, to achieve the best overall standing. We use correlation measures, data summarization, and probabilistic modeling on triathlon historical data since 1989 to: i) investigate which component (swimming, cycling, or running) has the greatest contribution to the overall ranking of male and female triathletes, ii) what minimum time gap behind the lead athlete (for each component) may still retain a high likelihood of medaling, and iii) model triathlon performances for future decision making. Project Organization Unit: Institute of Sport, Exercise and Active Living (ISEAL), Victoria University