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  The identification, classification and implementation of tactical strategies using AI and tracking data in elite football (Ref: SSEHS/ABBL)

   School of Sport, Exercise and Health Sciences

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  Dr Andrew Butterworth  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

The research project will focus on applying artificial intelligence and advanced sports analytics techniques to automate the technical and tactical analysis of the phases of play in elite football using player tracking data.

Working in collaboration with staff from the Data Science and Performance Analysis departments at Leicester City FC and staff in the School of Sport, Exercise and Health Sciences and Computer Science at Loughborough University (Dr. Andrew Butterworth, Donald Barron and Professor Baihua Li), the project aims to develop a formation and phases of play recognition tool, identify and recommend effective strategies for upcoming opponents and inform player scouting and recruitment processes.

The Doctoral Researcher will be embedded within Leicester City’s modern Seagrave Training Ground and use sports analytics techniques to develop novel solutions to applied performance questions in elite football. This will allow the successful candidate to develop skills in data analysis, working with industry-standard tracking data, and collaborating with key stakeholders in an elite sporting environment.

Entry requirements:

  • Postgraduate research degrees delivered in the School of Sport, Exercise and Health Sciences, require applicants to have a 2:1 honours degree or a master’s degree in a relevant subject (e.g. computer science, data science, performance analysis or sports analytics).
  • Demonstrable experience of coding with either Python or R, either in an educational setting or applied setting.
  • Experience of visualising data with Tableau and/or R Shiny is desirable but not essential.
  • Excellent communication skills, with the ability to write reports and present findings clearly to stakeholders of varying technical levels.
  • Pro-active and structured approach to problem-solving, good time management and organisational skills, with an ability to adhere to deadlines.
  • A commitment to continued professional development and a growth mindset.
  • Previous experience working in a professional sporting setting and knowledge of football is desirable but not essential.

English language requirements:

Applicants must meet the minimum English language requirements. Further details are available on the International website (

Funding information:

The studentship is for 3 years and provides a tax-free stipend of £19,237 per annum for the duration of the studentship plus tuition fees at the UK rate. Due to funding restrictions, this is only available to those eligible for UK fees.

All applications should be made online. Under programme name, select the School of Sport, Exercise and Health Sciences. Please also quote the advertised reference number: SSEHS/ABBL in your application.

To avoid delays in processing your application, please ensure that you submit the minimum supporting documents.

The following selection criteria will be used by academic schools to help them make a decision on your application.

As part of your supporting documents, please submit a proposal of no more than 500 words describing a study investigating how to assess phases of play in elite football using tracking data.

Please detail your research question, a brief rationale for the study, and the methods you propose to answer your research question. Please include a figure of the proposed study design. Any references are not included in the 500-word limit.

Project key terms:

data analysis, data science, sport performance, sports analytics, Premier League, football, elite sport

Email Address SSEHS:

[Email Address Removed]

Computer Science (8) Mathematics (25) Sport & Exercise Science (33)

Where will I study?

 About the Project