Introductions
- u3037121
- Feb 25, 2017
- 2 min read
The objective of introducing Informatics and Analytics as a concept is to identify where they are present in the study of sports performance. Introductions as a theme shares the connectivist approach to learning, whereby "the content does not define the course" - Stephen Downes, 2012.
Sport Informatics -
"The integration of sport scientific knowledge in computer science" - Daniel Link and Martin Lames (2009).
Examples of Sports Informatics include:
- Data acquisition, processing and analysis
- Modelling and simulation
- Databases and expert systems
- Multimedia and presentation
- IT networks and communication
A broad description of Sport Informatics is that it covers all activities at the interface of computer science and sports science. As a concept, it can range from simple data handling tools to motion control sensors for modelling and simulating sport-related phenomena.
Sport Analytics -
"Management of structured historical data, the application of predictive analytic models that utilize that data, and the use of information systems to inform decision makers and enable them to help their organisations in gaining a competitive advantage in the field of play" (Alamar and Mehrotra, 2011a, 2011b, 2012).
There are three models of Sport Analytics:
- Data management
- Predictive models
- Information systems
A succinct summary of what Sports Analytics is, for me, came from Chris Anderson (2014) where he stated it as "the discovery, communication and implementation of actionable insights derived from structured information in order to improve the quality of decisions and performance in an organisation".
Learning Journey - the first steps
There are strengths and weaknesses to a course which has no particular sequence or timeframe. Many of the things I consider to be good about a non-linear course, others may think to be a weak point – it is very dependent on how the student learns. What I like most about this structure is that information which is the most relevant to how I effectively learn, can be sought out. As opposed to other units where information is presented in mass, and relevant points need to be sifted out. Personally, I do not relate to many negative points with this course structure. The way in which the WikiEducator site is set up, makes it extremely easy to come back to the relevant part of the course should you have a few days away from the content.
An important notion to start the course with was to identify the difference between Sports Informatics and Analytics.
Where I see the main difference is in the fact that Informatics refers to an ever changing set of circumstances and adapts with technologies as both computer and sport sciences evolve. As for Analytics, it deals with data that has already happened, as opposed to what is happening in the present and what could happen in the future.
While I believe that both have elements which deal with future performance, they have very different approaches. Informatics sets up its future using a highly technological platform and evolves with sport as it goes. Analytics uses historical data to form a predictive nature to uncovering the likely patterns that sport will follow as it evolves.
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