This week Stuart Morgan (@in2sport) from the Australian Institute of Sport visited Swinburne to discuss current research projects and areas of potential collaboration with Swinburne. In terms of multi-disciplinary e-Research capability this was really interesting. It turns out sports research is not just about biology and physiology (I'm completely ignorant when it comes to Australian sport and sports research), but includes applications of machine learning, predictive analytics, computer vision, sports engineering, and data visualisation. The purpose of Stuart's visit was to start discussions about capability, with a view towards establishing a sports analytics cluster.
I knew that 3D advanced visualisation and pattern recognition was important and I was aware that astronomers and sport science researcher at Swinburne were working together on time-of-flight data analysis. What I hadn't quite appreciated, was the high demand of data-scientists and analysts in the sports industry. It seems obvious now, but a lot research is going into non-invasive tracking methods, for example optical tracking of hockey or rugby players, for training and match reviews as well as real-time decision support during a game. Optical tracking in swimming is another challenge, where lane ropes and swimmer positions are really difficult to see, let alone tracking individual arm movements.
Stuart also talked briefly about one project with Prof. Chris Fluke from the Centre of Supercomputing and Astrophysics. Using depth sensors and time-of-flight cameras they've been working towards creating 3D reconstructions of boxers dancing in a ring.
A number of potential area of collaboration were identified:
- Information retrieval
- Predictive analytics
- Empirical support for visualisation
- The ability to map/track body pose
- Synthetic training environments
by exploiting existing collaborative pathways such as ARC linkage grants, collaborations with the Swinburne Software Innovation Lab (SSIL), sports research grants and AIS funded top up grants for Australian Postgraduate Awards.
The proposed sports analytics cluster would be aligned with current demands in high-performance sport, would provide a career pathway for quantitative students, have an international research profile and meet industry needs for research in sports analytics. Ideally it would need something larger, like an overarching data science institute to provide critical mass and ensure long term resourcing.