Free open Job in Wales Adopting Data Driven Modelling and Prediction Approaches to Support Strategies for Successful Game Outcomes in Rugby at Swansea University

Swansea University is a UK top 30 institution for research excellence (Research Excellence Framework 2014), and has been named Welsh University of the Year 2017 by The Times and Sunday Times Good University Guide.

*This scholarships is part funded by the Welsh Government’s European Social Fund (ESF) convergence programme for West Wales and the Valleys.*

MSc by Research for UK or EU applicants in the field of Computer Science / Visual and Interactive Computing

This work in with Ospreys Rugby will consider the design of Key performance indicators (features) and a Bayesian-based machine learning models to predict the outcomes of a rugby match. The approach will focus on the ability for the above data-driven features and models to inform coaches and players on areas that are mostly likely to influence game outcomes therefore help shape training, selection and strategies in Rugby Matches. This research will empower Ospreys Rugby and the wider community (through it is community initiatives) to further the adoption of data driven techniques to enhance performance and gain competitive margins.

The work has four main research objectives:

1) The design and quantifiable validation of in-game context-sensitive data driven descriptive statistics.

2) To build a predicative model with some transparency of feature impact on outcomes.

3) This work will adopt and investigate the relative usefulness of continuous outcome metrics to train supervised probabilistic predication of scores.

4) The work will assess the usefulness of the features and predictive models trained using various outcome metrics in empowering the team to investigate and make data-driven changes to training, selection and in-game strategies.

Scholarships are collaborative awards with external partners including SME’s and micro companies, as well as public and third sector organisations. The scholarship provides 1 year funding with a 3 month period to complete the thesis. The achievement of a postgraduate skills development award, PSDA, is compulsory for each KESS II scholar and is based on a 30 credit award.


Academic requirements:

Candidates should have a 2.1 or above in their undergraduate degree Computer Science or a related subject.

Residency criteria:

Candidates should be eligible for UK/EU Fees.

Funding Details

The studentship covers the full cost of UK/EU tuition fees, plus a stipend. The bursary will be limited to a maximum of £11,472 p.a. dependent upon the applicant’s financial circumstances.

There will also be additional funds available for research expenses.