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Enhancing the Use of Data in Professional Rugby Union via Advanced Data Science Techniques - fully funded PhD by Bath Rugby and Leeds Beckett University


Project Description

With the ever-growing collection of data in professional sport, appropriate collection, management and analysis strategies are paramount to ensure that correct inferences are made (Casals and Finch, 2017). This is particularly important for big data sets of repeated measures that require sophisticated statistical modelling, the interpretation of responses to an intervention, and assessing individual changes in measures of training load and fatigue, and performance metrics (Robertson et al., 2017, Sweeting et al., 2017, Voisin et al., 2019). Furthermore, the presentation of such data is important to accurately disseminate findings to performance staff and athletes (Perin et al., 2018, Thornton et al., 2019). Bath Rugby and Leeds Beckett are looking to recruit a highly motivated individual with a passion for data science, and a desire to advance the area of data management and interpretation in professional sport. The candidate will have a strong grounding in model building, statistical inference and research methods, data visualization, and a desire to apply this knowledge in applied practice. Previous experience working in sport is not required.

The purpose of this PhD is to explore the use of different data collection, management and analysis methods within a professional rugby union club, in order to improve the rigor of data collection, management and interpretation. Furthermore, the PhD will investigate the effect of data presentation methods on support staff and player interpretation and engagement. The PhD student will use the findings from their research to guide performance staff, strategically embedding these methods in practice within the constraints of the day-day schedules, to ensure that scientific rigor is upheld and best practice applied.

The successful candidate will join the research department at Bath Rugby which consists of a number of practitioners and PhD students working in the areas of sports science and performance. They will be involved in the management, analysis and presentation of data collected at the club, although the specific day-to-day activities will depend on the successful candidate’s strengths and areas of interest. Candidates should be innovative, creative and ambitious, while also being well organised and highly motivated. Positions will require some flexibility in working hours in line the Bath Rugby schedule, although the PhD programme of research and candidate’s academic development will remain a priority. The start date for the PhD is 1st October, although there is opportunity to start beforehand employed as a research assistant.

Applicants are encouraged to discuss their proposals and the project with the Project Lead Dr. Gregory Roe and

Funding Notes

The PhD studentship will have an advanced bursary of £23,009 per annum (pro-rata into 12 monthly payments) plus UK/EU Fees paid initially for a period of four years.

Overseas applicants must refer to the UKBA regulations on studying in the UK and contact our Graduate School before submitting. The Graduate School: For all enquiries regarding the application process, please contact or telephone: +44 (0)113 812 5385.

References

CASALS, M. & FINCH, C. F. 2017. Sports Biostatistician: a critical member of all sports science and medicine teams for injury prevention. Inj Prev, 23, 423-427.

PERIN, C., VUILLEMOT, R., STOLPER, C. D., STASKO, J. T., WOOD, J. & CARPENDALE, S. 2018. State of the Art of Sports Data Visualization. Computer Graphics Forum, 37, 663-686.

ROBERTSON, S., BARTLETT, J. D. & GASTIN, P. B. 2017. Red, Amber, or Green? Athlete Monitoring in Team Sport: The Need for Decision-Support Systems. Int J Sports Physiol Perform, 12, S273-s279.

SWEETING, A. J., AUGHEY, R. J., CORMACK, S. J. & MORGAN, S. 2017. Discovering frequently recurring movement sequences in team-sport athlete spatiotemporal data. J Sports Sci, 35, 2439-2445.

THORNTON, H. R., DELANEY, J. A., DUTHIE, G. M. & DASCOMBE, B. J. 2019. Developing Athlete Monitoring Systems in Team-Sports: Data Analysis and Visualization. Int J Sports Physiol Perform, 1-26.

VOISIN, S., JACQUES, M., LUCIA, A., BISHOP, D. J. & EYNON, N. 2019. Statistical Considerations for Exercise Protocols Aimed at Measuring Trainability. Exerc Sport Sci Rev, 47, 37-45.

How good is research at Leeds Beckett University in Sport and Exercise Sciences, Leisure and Tourism?

FTE Category A staff submitted: 48.60

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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