Sport Performance Analysis MSc

This module aims to allow you to gain a systematic understanding of performance analysis of sport. This is achieved through critically engaging you in appropriate processes and developing a comprehensive understanding of relevant techniques used in the discipline. It also aims to develop your research skills so you are able to disseminate complex information to both coaches and athletes with the aim of providing greater insight to performance. You'll critically evaluate current research in the discipline in order to evaluate methodologies, design, interpret and synthesise sport performance data and literature.

This module aims to equip you with the relevant knowledge and skills to undertake appropriate research in their subject areas. You'll learn searching strategies to identify relevant literature, how to critically appraise literature and relevant research methods topics such as research design, selecting and using suitable statistical tests appropriate to the subject area. This module will be delivered predominantly through shared and subject-specific online video tutorials allowing you to access a wide variety of resources which will prepare you for undertaking their dissertations. This innovative approach allows you to develop their research methods skills at your own pace with relevant step-by-step videos produced, allowing you to revisit the content at any time.

This module aims to develop your ability to apply and see the application of knowledge gained from other modules in relation to a real work scenario. You'll be required to adopt a reflective and critical approach to your working practice and to promote a problem-solving approach in a work environment.

This module aims to support you to undertake research, with a focus appropriate to your programme and area of practice and building upon the research proposal formulated in SES4030. To create a peer learning community for you to critically support each other in the research process. To provide guidance, additional to that provided by your supervisors, on matters of ethical application, research methods, data collection, analysis and writing-up.

This module aims to develop your data analysis and visualisation skills. The ability to manage data and check for errors in datasets is an important and sought-after skill in performance analysis. You'll learn to visualise data in a variety of software packages such as spreadsheets and business intelligence software. You'll be able to analyse and interpret data using predictive based statistics like regression and determine important variables using techniques like dimension reduction (principal component analysis) and assess relationships (correlations).

You will gain knowledge and understanding through attending live research led-teaching and practice-led learning, engaging with pre-recorded content and key concept videos, seminars, workshops, problem solving tasks, small group discussions & presentations, student and teacher led learning sessions and finally, via student placements. 

Through these methods you will develop your digital literacy. An understanding of the subject is assessed in both summative and formative methods. You will be encouraged to participate in curriculum design and lead student communities via co-leadership opportunities throughout the academic year via group learning, student forums, programme voice groups and an ability to co-design your research methods and dissertation assessments.

We are regularly reviewing and updating our programmes to ensure you have the best learning experience. We are taking what we have learnt during the pandemic and enhancing our teaching methods with new and innovative ways of learning.

Your timetable will be built around on campus sessions using our professional facilities, with online sessions for some activities where we know being virtual will add value. We’ll use technology to enhance all of your learning and give you access to online resources to use in your own time.

The table below gives you an idea of what learning looks like across a typical week. Some weeks are different due to how we schedule classes and arrange on campus sessions.

This information is likely to change slightly as our plans evolve. You'll receive full information on your teaching before you start your course.

Learning structure: typical hourly breakdown:

Definitions of terms

Live in-person on campus learning – This will focus on active and experiential sessions that are both:

• Led by your tutors including seminars, lab sessions and demonstrations We'll schedule all of this for you
• Student-led by you and other students, like small group work and presentations.

Tutor set learning activities – This covers activities which will be set for you by your tutor, but which you will undertake in your own time. Examples of this include watching online materials, participating in an online discussion forum, completing a virtual laboratory or reading specific texts. You may be doing this by yourself of with your course mates depending on your course and assignments. Outside of these hours, you’ll also be expected to do further independent study where you’ll be expected to learn, prepare, revise and reflect in your own time.

Your knowledge, understanding and skills is assessed via a range of assessment methods, such as: presentations, practical assessments, and coursework.