On performance analysis in elite netball: Data analytics through the use of machine learning and computer vision - Smith, P. D. (University of the Sunshine Coast, 2021)
The way team sports are played, coached, trained for, and analysed has substantially changed over the last century. With greater incentives for elite teams to achieve success has come the pressure to perform. This has resulted in every aspect of the game implementing a continuous improvement mentality to maximise its operational efficiency and performance to gain a competitive advantage. From this, understanding team or player performance is fundamental to achieving club objectives. This has resulted in the process and application of match performance analysis to be regarded as an essential component in the implementation of a system to maximise team success. The aims of this research were to establish key performance indicators for elite netball and test if they are independent of playing standard. It establishes a new suite of methods to provide context to existing performance metrics and enable greater insight into team strategy and tactical success including the locomotion used by athletes and their location throughout the match. Findings from this research have provided coaching staff at the elite level with a quantified, objective record of the match allowing them to compare a defined set of performance indicators to their own subjective evaluation. This has allowed the implementation of an informed game plan to maximise team performance, and developing targeted position specific training schedules that directly compare to the physical conditions encountered in a match.