The information available to practitioners working within sport is diverse and constantly increasing due to advancements in technology and increase in availability of data. For example, the physical and skilled output of athletes can be captured via wearable sensors and optical tracking systems, Similarly, data on an athlete's on-field performance, recruiting profile, training load and wellbeing can all be monitored over time, by a variety of technologies and data types. Therefore, there is a need in sport to store, analyse, consolidate and interpret data in order to communicate this information to coaches and support staff in a timely manner. Additionally, practitioners working within sport must be able to translate this data and information into practice.
This unit (SES6001) will introduce students to data analytics (e.g. finding meaningful patterns within data sets) and how it is used in sport, across a variety of different applications. Students will learn how to critically appraise technologies used to capture common data types in sport. Students will be introduced to a range of analysis techniques and will discover how to analyse data from a range of sources including athlete tracking systems (e.g. GPS), match statistics and wellbeing questionnaires.
Unit details
Location:
Online Self-Paced
Study level:
Postgraduate
Credit points:
12
Unit code:
SES6001
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Learning Outcomes
| 1. | Design, implement and evaluate methods for the analysis of data; | ||
| 2. | Devise models to identify key-performance indicators within data sets obtained from various sources; | ||
| 3. | Implement a range of analysis methods to interpret data that can be used for both short and long term practical application; | ||
| 4. | Appraise and utilise contemporary technologies in professional practice; and | ||
| 5. | Elucidate complex information based on data sets to other practitioners. |
Assessment
| Assessment type | Description | Grade |
|---|---|---|
| Exercise | Scoping the literature and framing a sports analytics problem, appraising contemporary technologies | 25% |
| Project | Analysis of a dataset, through the design of models to interpret data | 35% |
| Presentation | Multimedia presentation on insights and results from analysis of a data set | 40% |
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