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Enhancing the application and utility of microtechnology for training and monitoring in Rugby League

Project Description

Leeds Rhinos Rugby League sponsored Research Bursaries in collaboration with Leeds Beckett University
Full-time Sponsored Postgraduate Research Student Bursaries start date – February 2020
Leeds Beckett University and Leeds Rhinos Rugby League club are looking to recruit two highly motivated individuals to join the embedded research team at Leeds Rhinos Rugby League club.
Data are routinely collected via microtechnology during training and match play. Typically, velocity and time derived variables are aggregated (e.g., total distance, average speed, high speed running distance, accelerations) from training or match activities to be used for player monitoring and evaluation. While useful, typically the analysis techniques fail to consider more advanced application of the data, including its time series nature (Athanasopoulos et al., 2017 []), the multicollinearity between variables (Weaving et al., 2019 [], Weaving et al., 2017 []), the potential for evaluating movement sequences (Sweeting et al., 2017 []), or spatial positioning between players (Gonçalves et al., 2017 []).

The successful candidate will work alongside Dr Dan Weaving (Lead Sports Scientist - Leeds Rhinos / Lecturer in Sports Performance - Leeds Beckett University) at Leeds Rhinos to provide Sports Science support to the first team. The practical commitment will not exceed 15 hours per week, allowing the candidate to undertake innovative research, whilst developing an awareness of the practical constraints in rugby league. The successful candidate should have excellent data analytical skills to undertake this project.

Funding Notes

The PhD studentship will have a bursary of £15,009 per annum (pro-rata into 12 monthly payments) plus UK/EU Fees paid initially for a period of three years.

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)

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