Sport Data Science (MSc)

About the Course

Please note this course is for September 2027 entry and will open for application soon.

To gain a competitive advantage in sport, professional teams, equipment companies, and governing bodies are increasingly investing in data-driven approaches to support evidence-based decision-making. Within sports science and human performance, data is generated across multiple domains and in many different forms. This can include: biomechanical data that captures multidimensional movement patterns, forces, and accelerations; physiological data reflecting internal responses to training and competition; performance and technical data such as match statistics, skill execution metrics, and training load; and injury data used to monitor athlete health and guide return-to-play decisions.

The ability to manage, analyse, and interpret these complex and large datasets is essential for careers across professional sport and data-driven organisations. A master’s degree in Sport Data Science enables students to combine domain-specific sports knowledge with advanced data science techniques, including programming, machine learning, and predictive modelling. Through these interdisciplinary approaches, students learn how to transform raw data into meaningful insights that can inform coaching strategies, optimise player performance, support talent identification, and reduce injury risk.

In addition, large data programming and analysis plays a growing role beyond performance analysis, contributing to areas such as recruitment strategies, tactical evaluation, and even monitoring fan engagement through enhanced sports media. By developing strong capabilities in data analysis, statistical modelling, and data visualisation, graduates gain highly transferable technical skills. These competencies are increasingly sought after not only within the sports industry but also across wider sectors such as technology, health, and business analytics.

Curriculum Overview

The programme combines core modules in programming (such as Python or R), statistics, and data management with applied, sport-specific data collection and the underlying scientific principles that inform it. Students develop practical skills using key sports science equipment and data collection technologies, including 3D motion capture systems, wearable devices, and performance monitoring tools.

A central feature of the course is its focus on the complete data lifecycle. Students engage with the full end-to-end process, beginning with how data is generated and collected in sporting environments. They then progress to data management, learning how to clean, structure, and store datasets effectively. This is followed by in-depth analysis, where statistical and machine learning techniques are applied to answer performance-related questions. Finally, students develop skills in data visualisation and communication, transforming complex results into clear, actionable insights for coaches and other stakeholders in elite sport. By working through this entire process, students gain a comprehensive understanding of how raw data is translated into meaningful, real-world decisions.

As the course progresses, students advance into more specialised topics, including machine learning, predictive modelling, and advanced data visualisation. These are delivered through sport-specific case studies, enabling students to apply their skills to areas such as performance analysis, injury prevention, and player recruitment. The programme culminates in a dissertation research project, where students independently investigate a specialised topic. This may involve collecting and analysing original data or applying advanced analytical techniques to datasets provided by external partner organisations.

By the end of the degree, graduates are proficient in data science methodologies and possess a strong understanding of how these techniques are applied to sporting contexts. Throughout the programme, students develop both personally and professionally, gaining confidence in applying analytical techniques, strengthening problem-solving and communication skills, and learning to work effectively with stakeholders. They graduate with the technical expertise, practical experience, and professional mindset required for careers in sport data analysis and the wider data science sector.

Entry Requirements

Normally a minimum of a Second-Class Honours degree in a relevant discipline awarded by a UK university, or an equivalent higher education qualification is required.

International Entry Requirements

Possess a degree from an overseas institution that is judged by the Registrar or Nominee to be equivalent to a second class honours degree from a UK University.

For students whose first language is not English there is a language requirement of IELTS 6.0 overall with 5.5 minimum of all components. In addition to this, we also accept a wide range of International Qualifications, for more information please visit our English Language Requirements page.

For additional information about country specific entry requirements visit the your country pages. 

*Part time study is not available for Non-EU International applicants

Teaching and Research

The staff who teach this course possess extensive academic and applied experience. They have published in internationally prestigious journals and have collaborated with both clinical and sporting organisations to apply data science techniques to real-world problems. This ensures that the course is focused on developing students’ employability for similar roles; rather than being taught by traditional lecturers, students are taught by practicing data scientists.

UK/Channel Island Tuition Fees

Tuition fees for Home students for 2027/28 are £10,550

Funding

We offer a number of scholarships and loans to help fund your postgraduate studies. Visit our scholarships pages for more details.

EU/Non EU International Tuition Fees

Tuition fees for EU/Non-EU International students for 2027/28 are £18,375

Please be aware that the UK’s departure from the EU may affect your tuition fees. Learn more about your fee status and which tuition fees are relevant to you.

Careers

This course specifically targets preparing students to work as data scientists in sport. In recent years, this has become an area of significant growth within elite and competitive sport. Most top-level professional clubs now employ teams of data scientists to support effective data analytics, management, and data-informed decision-making. However, the core data management and analysis skills developed on this course also equip students for a wide range of data scientist and data analyst roles beyond the sporting domain.