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  Sports Science: Fully Funded Swansea University and Scarlets Rugby PhD Scholarship: In-game statistics associated with match outcome in professional Rugby Union

   School of Engineering and Applied Sciences

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  Prof L Kilduff  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Funding provider: Swansea University and Scarlets Rugby

Subject areas: Engineering, sport science, data science, physics, mathematics

Project start date: 

  • 1 July 2024 (Enrolment open from mid-June) 


Aligned programme of study: PhD in Sports Science

Mode of study: Full-time

Project description:

The aim of this PhD project is to investigate whether match key performance indicators (KPIs) are effective at predicting match outcome at the elite rugby union level in the URC. 

The candidate will review current key performance indicators and analyse their influence on match outcome. The candidate will build and refine machine learning techniques to find latent patterns or parameters in the data to statistically predict match outcome and league position. Initially, these models will be based on legacy data from our project partner, Scarlets Rugby. This dataset comprises individual athlete, team, strategy, and wellness information from 5 prior seasons. The models will be verified/refined on the legacy data test efficacy and then applied to the current URC season 24-25. 

The candidate will be embedded in a professional rugby environment and will be expected to adhere to strict non-interference rules. They will be responsible for collecting multi-channel data from a range of micro-technology devices that assess performance and monitor training load and ultimately will oversee data quality, provenance and curation within a standardised database. 

Available resources/facilities: A-STEM labs (biomechanics and exercise physiology)/Scarlets load monitoring and performance analysis equipment


Candidates must hold an undergraduate degree at 2.1 level in a STEM discipline. If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency. 

Experience in MATLAB, PYTHON and GPS Data Collection are desirable.

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations

Engineering (12) Mathematics (25) Physics (29) Sport & Exercise Science (33)

Funding Notes

This scholarship covers the full cost of UK tuition fees and an annual stipend at UKRI rate (currently £18,622 for 2023/24).
Additional research expenses will also be available.

Where will I study?