Sport Informatics and Analytics/Capstone/Pattern Recognition

Pattern recognition

In the Pattern Recognition theme (T2), we considered:

• Systematic observation of performance.
• Supervised learning approaches to data analysis.
• Connections between performance trends and athlete actions.
• Use of open source tools such as R to analyse performance and visualise data.

We shared GPS data from an Australian Rules Football team's performance in a competitive game in order to explore the potential of such data to provide interesting and actionable insights. We presented Mladen Jovanović's analysis of the data set as a case study.

This theme included a topic on knowledge discovery in databases (KDD) and used two examples from the sport literature to explore the practice of KDD.