Informatics and Analytics

As this course comes to an end, I thought it would be prudent to provide a recap of what I have learnt throughout the semester.

Theme 1: Introductions

• Ethical Issues

• Communities of Practice

Theme 2: Pattern Recognition

• Using 'R'

• Knowledge Discovery

Theme 3: Performance Monitoring

• The Quantified Self

Theme 4: Audiences and Messages

• Visualizing Data

• Feedforward

The combination of all themes provided a complete picture to how Sports Informatics and Analytics are prevalent throughout the sporting industry. It also provided the opportunity to experience how they can be used to further enhance and develop performance across a variety of sports. In a world where information is just a click of a button away, combining pattern recognition and performance monitoring and then communicating it in a way that appeals to wide variety of audiences, has the capacity to provide unprecedented opportunity to make a difference on the sporting landscape.

The content explored throughout this unit most certainly outlined how these themes can be applied in a sporting context in my own experiences. The ability to quantify oneself and be an active and productive member of a sporting community goes a long way toward bettering the standard which is performed at.

Sport provides so many different areas for observation that it can be difficult to ascertain what is relevant and what is not. Having a sound concept of what Feedforward is has provided knowledge to be able to find the most relevant areas of focus in my own sporting context and apply them to my experiences. Albeit basic, reviewing programs such as 'R' and viewing the process behind how data is captured has opened my eyes as to what is deemed as commonplace in a sporting environment when it comes to analysis.

Overall I enjoyed compiling this E-Portfolio and found the self-paced nature of the course content very fulfilling and successful in terms of my own development. Until next time!