SE799-7-SP-CO:
Data Analytics in Sport
2025/26
Sport, Rehabilitation and Exercise Sciences (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 12 January 2026
Friday 20 March 2026
15
24 February 2025
Requisites for this module
(none)
(none)
(none)
(none)
(none)
This module explores the application of data analytics within the context of sport, providing students with the knowledge and skills to harness data for performance optimisation, strategic decision-making, and research purposes. Emphasising both theory and practice, the module covers key topics such as data collection methodologies, data cleaning and visualisation, statistical analysis, machine learning applications, and predictive modelling.
Through real-world case studies and hands-on projects, students will learn to critically evaluate data sources, interpret complex datasets, and communicate actionable insights to diverse stakeholders. By the end of this module, students will be equipped to leverage cutting-edge analytical tools and techniques to address contemporary challenges in sport science and performance.
The aims of this module are:
- To provide students with a comprehensive understanding of the principles and techniques of data analytics in the context of sport.
- To equip students with the ability to critically evaluate and apply data analytics tools and methodologies for performance analysis, strategic decision-making, and research purposes.
- To develop students’ competencies in analysing, interpreting, and presenting data-driven insights to support evidence-based practices in sport science.
By the end of this module, students will be expected to be able to:
- Critically appraise data analytics methods and their applicability to various areas of sport science, including performance analysis and injury prevention.
- Apply advanced data processing and visualisation techniques to communicate complex information effectively to both technical and non-technical audiences.
- Conduct statistical and machine learning analyses using appropriate software tools to solve practical problems in sport science.
- Generate actionable insights based on robust data analytical techniques.
Syllabus information:
- Data collection (practical session)
- Data cleaning
- Analysis of position data
- Time-motion analysis
- Collective movement
- Analysis of event data
- Passing network analysis
- Expected goals
- Web scraping
- Machine learning applications
- Supervised learning
- Unsupervised learning
- Statistics
- Dashboards
This module will be delivered via:
- One 1.5-hour seminar per week
- One 2-hour practical (IT-Lab) per week
- One practical (football pitch / astroturf) per term
- Two drop-in sessions (e.g. support classes or screenings) per term
Students are expected to undertake the reading before classes and be prepared to engage in discussion.
Students are expected to prepare and deliver a presentation at the end of the module.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
No
No
Yes
No external examiner information available for this module.
Available via Moodle
No lecture recording information available for this module.
* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.
Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can
be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements,
industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist
of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules.
The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.