Description
Designed in collaboration with industry, La Trobe’s Master of Sport Analytics gives you the skills and experience needed to excel in this exciting and fast-growing industry. It's an ideal choice if you're already working in sport and want to upskill, or have an interest in data analytics and want to apply your knowledge to sport. Whatever your background, our academics and industry partners will support you to succeed.
Learn how to use data to boost athlete performance and wellbeing. You’ll get hands-on experience with industry-standard technologies, such as wearable sensors (Catapult GPS and IMeasureU accelerometers), computer vision and video annotation software (Keemotion and Sportscode), and athlete management systems.
See where your new skills could take you. You’ll cover talent ID, athlete management, performance and injury modelling, and broadcasting and fan engagement during your degree. You’ll develop an intricate understanding of cutting-edge machine learning techniques and use advanced analytics tools, including R, Python and SQL – all required for a successful career in sport analytics and data science.
In your second year, you’ll have the opportunity to complete a practical learning project. You could work under the supervision of an industry expert or academic and hone your data analysis skills in a real industry setting. Previous students have completed projects with Tennis Australia, AFL Victoria, Champion Data, and Carlton and St Kilda Football Clubs.
You can also take advantage of flexible study options, mixing in-person subjects with online and blended study, and the opportunity to exit early with a Graduate Certificate after six months, or a Graduate Diploma after one year.
You'll learn:
- Sport analytics methods
- Understand the basic practices for capturing, handling, cleaning and processing data generated from sport.
- Generating insights from data
- Learn how to use data to develop insights into talent identification, athlete management, injury management and fan engagement.
- Machine learning techniques
- Understand and use data-programmed machines to detect patterns and predict future sporting events.
- Data visualisations
- Learn to select and use analytical tools and visualisations to clearly communicate outcomes and findings.
