Breaking the Surface: A Data-Driven Investigation for Swimming Strategies and Outcomes

Performance analysis, defined as an objective analysis of actual sports performance without involving self-reports or a laboratory setting [1], is an essential approach to form further experimental study questions. In swimming, a major form of performance analysis is the race analysis, which is performed based on both/either the video data recorded in competition sites and/or official race outcomes [2]. Although there have been many studies focusing on swimming race analysis, there are many questions remain unanswered, such as:

• Are swimmers generally achieving good performance in Olympic years?
• Can the next Olympic records be predicted from past competition results?
• Is there a common peak performance age for swimmers?
• How do top-elite swimmers develop their performances across their international careers?
• How have swimmers changed their race strategies over the last decades?

One of the reasons for the lack of studies addressing these questions might be that, commonly, researchers only focus on narrowed-down data, such as data extracted from a single competition, finalists only, or specific events/strokes. Answering broader research questions would require a wider focus on data, while this would potentially require a great amount of time in data collection and analysis. One potential solution for this issue is the usage of publicly available data. For example, the World Aquatics website (https://www.worldaquatics.com/) provides many datasets, including major swimming competition results, as well as the record histories of all international swimmers. Exploring these datasets would be an excellent starting point for investigating competitive swimming evolution and predicting the future of swimming performance, which would give useful insights into many practical areas, such as long-term training planning, swimming career planning, and talent development.

This PhD project aims to explore these questions, linking to different events and gender, using mass data extracted from public resources and advanced statistics (e.g. multiple/logistic regression models) as well as machine-learning approaches (e.g. time-series forecasting models). There is a further possibility of extending the questions to a national level (Great Britain/Scotland) and to youth and development ages, utilising the resources of the Scottish Institute of Sport.

Supervision

The successful candidate will be supervised by Tomohiro Gonjo, Fergus Guppy and Marta Vallejo.

Funding

This is a full scholarship which will cover tuition fees (Home and Oversees) and provide an annual stipend (paid in line with UKRI recommended rates, £20,780 in 2025-25) for 42 months. Thereafter, candidates will be expected to pay a continuing affiliation fee (currently £130) whilst they complete writing up their thesis.

Eligibility

This project is available to ALL students, whether home, EU or overseas.

Essential requirements:

• First or upper second-class Honours degree (or equivalent) in Sport & Exercise Sciences, Computer Sciences, Mathematics, or any other relevant discipline.
• Excellent personal, oral, and written communication skills.

Desirable qualities:

• MSc in a relevant discipline
• Experience in conducting research in a relevant area.

How to Apply

To apply you must complete our online application form.

Please select PhD Life Sciences as the programme and include the full project title, reference number (EGIS2025-TG) and supervisor name on your application form. Ensure that all fields marked as ‘required’ are complete.

Once have entered your personal details, click submit. You will be asked to upload your supporting documents. You must complete the section marked project proposal; provide a supporting statement (1-2 A4 pages) documenting your reasons for applying to this particular project, outlining your suitability and how you would approach the project. You must also upload your CV, a copy of your degree certificate and relevant transcripts and an academic reference in the relevant section of the application form.

You must also provide proof of your ability in the English language (if English is not your mother tongue). We require an IELTS certificate showing an overall score of at least 6.5 with no component scoring less than 6.0, or a TOEFL certificate with an overall score of at least 85, including reading 20, listening 19, speaking 20 and writing 21. Alternatively, if you have received an English-taught Bachelors or Masters degree from one of the countries listed on the UK Government Guidance under ‘Who does not need to prove their knowledge of English’, and it was obtained less than five years from your intended start date, you should provide evidence of your award that clearly states it was delivered and assessed in English language.

Please contact Dr Tomohiro Gonjo (T.Gonjo@hw.ac.uk) for further information or an informal discussion.

Please contact egis-pgr-apps@hw.ac.uk for technical support with your application.

Timeline

The closing date for applications is 4 July 2025. Applicants should ideally be available to start in September 2025 and no later than January 2026.

References