Associate ProfessorDan Dwyer

My research interests are focussed on the measurement, analysis and prediction of performance in sport.

There is an old adage that if you can't measure something, you can't manage it. This concept can't be applied everywhere, but I do believe that it applies to the performance enhancement process in elite sport. Advances in technology provide new opportunities to measure the activity of athletes including their training load and their performance in competition. Many of these advances take the form of wearable technology (e.g. GPS-based athlete tracking) and computer vision.

It is often the case that when you use technology to measure something, it can be semi-automated and scalable, so you end up with a huge amount of data. This presents an opportunity and a challenge, in terms of analysis. Modern data science ca be applied to interrogate large databases in order to identify patterns, relationships and trends. One of the most useful applications is the creation of models that explain the complex relationships between the characteristics of the performance of an athlete (e.g. activity and performance in the first half) and the outcome of their performance (e.g. win/loss or finishing place). Models can be used to classify or predict performance, which can assist the strategic decision making of athletes and coaches.

Knowledge Areas
Sport science, sport performance analysis, sport data analytics, artificial intelligence, decision support, cycling, AFL, Netball, cricket, triathlon