MPhil/PhD studentship in developing a player-value rating system in elite football utilising machine learning and artificial intelligence

Investing in excellence: studentship opportunities

The University of Derby has an opportunity for a full-time postgraduate research studentship in Data Science area of research in the College of Science and Engineering (SE).

The successful applicant will receive a maintenance stipend (based on the minimum stipend defined by UKRI, currently £18,622 for the academic year 2023/24) and home MPhil/PhD tuition fees (£4,712 - subject to amendment) only up to the target submission date.

Please note: this opportunity is only open to home/UK students due to CAS and visa processing restrictions related to the start date.

The intended intake period is March 2024, or the next available intake. 

The successful applicant will be expected to complete their MPhil/PhD within 3 years on the MPhil/PhD route, contribute to the College REF submission and get involved in the wider research activities of the College. 

Applicants will become part of a friendly and welcoming team and will be supported and managed by their supervisors. 

The vacancy details are as follows: 

Purpose/objectives 

To semantic model and annotate the football data recently collected through advanced IoT technology, including ball contact types (eg passes, tackles, and shots), outcome (eg successful/unsuccessful), player pitch location, and outcome rating (eg added expected goal value). The model then can be used by cutting-edge machine-learning algorithms.

Investigate the potential of deep-learning-based reinforcement learning and ChatGPT functions to develop a novel and interactive AI system capable of understanding complex football data, including player positional requirements, signature types (eg attacking/defensive contributions), and starting line-up combinations during in-game performances, thereby aiding in complex decision-making processes.

We will evaluate the effectiveness of our developed system by testing it in a simulation of our football club partners' environment with financial data, helping to make complex decisions such as rating and analysing player performance, suggesting training and game strategies, selecting line-ups, and assisting with player transfers.

Project description 

We are looking for a student to start a PhD programme with experience and a background in machine learning, computer programming (eg Python) and big-data analytics. 

This PhD project aims to create a new and innovative AI system that can understand complex football data using machine-learning algorithms, deep-learning-based reinforcement learning, and ChatGPT functions. To achieve this, the project will model and annotate advanced IoT technology-enabled collected football in-game data from our football club industry partners.

The AI system will be designed to assist with complex decision-making processes, such as rating and analysing player performance, suggesting training and game strategies, selecting line-ups, and helping with player transfers. To evaluate the effectiveness of the system, it will be tested in a simulation environment using financial data.

The project takes an interdisciplinary approach, bringing together sports performance analysis, business, economics, and data science. This approach has great potential to support decision-making within the UK football economy and lead to greater market efficiency.

The project also addresses the challenges associated with understanding and evaluating player performance data in relation to team performance and financial sustainability, making a significant economic contribution to the UK national economy, particularly in professional football.

Potential project impact 

This study has the potential to enhance our understanding of how data science, specifically machine learning and AI, can be used to inform complex decision-making in sport and business. In the realm of business, sustainability, and governance, the study's findings could be leveraged to improve and transform player trading strategies for professional football clubs.

Principal accountabilities and responsibilities

• Carry out research towards the timely completion of a doctoral degree
• Work on site and off site, as appropriately, in the University Data Science Research Centre
• Organise and attend regular supervision meetings
• Provide regular progress updates and research outcomes to the supervision team and Postgraduate Research School (PGR)
• Communicate regularly and in a professional manner with research partners and key stakeholders
• Contribute to the wider University of Derby research student culture
• Engage in relevant training and CPD opportunities to facilitate the successful completion of doctoral studies
• Actively participate in theoretical and/or empirical research in the big-data analytics and machine learning area with sport performance datasets
• Be prepared to learn and apply cutting-edge technologies to solve research problems
• Work towards publishing results in the high-standard and related international research journals and conferences
• Present findings at internal and external conferences, workshops and seminars
• Comply with the regulations governing the degree programme as laid out by the PGR department
• To comply with the Code of Practice for Research Candidature and Supervision

To apply 

Please review our entry requirements before submitting your application and check out the 'Getting Started' section below.

For this studentship, the ideal candidate should be able to demonstrate the following required specific skills, knowledge, experience and qualities: 

• Strong mathematical and statistical background: Understanding most of linear algebra, probability theory, calculus, and optimisation techniques is essential for machine learning applications
• Proficiency in programming languages: Experience with programming languages such as Python or R is highly recommended; experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras is also desirable
• Knowledge of machine-learning techniques: Familiarity with supervised and unsupervised learning methods such as classification, regression, clustering, dimensionality reduction, reinforcement learning, and Natural Language Processing is necessary
• Communication and collaboration skills: The ability to communicate effectively and work collaboratively with interdisciplinary teams, including coaches, athletes, and researchers, is essential to ensure the successful development and implementation of the project
• Creativity and critical thinking: The ability to think creatively and critically to solve complex problems and develop novel approaches to tackle challenges is important for success in this field
• Academic writing and research dissemination: The ability to produce academic work to a high written standard and to present to a variety of audiences.
• Desire: An interest in the application of data science to sports performance environments and a desire to develop a high-quality academic publication profile

It is desirable that the candidate has an MSc in data science, computer science, statistics, mathematics, physics or a related STEM discipline.

Completed applications should be submitted via our online application system quoting funding reference: CoSE_PGRS_PlayerValue_MAR23

Closing dates for applications: Wednesday 3 January 2024.*

*(Please note, we encourage applicants to apply as soon as possible as we reserve the right to close before 3 January 2024 if a high volume of applications is received.)  

Interviews: 22-26 January 2024. 

If you have not been invited for an interview by the interview date, please assume your application has been unsuccessful.  

For other enquiries which are subject-specific please contact:

• Director of Studies: Dr Hong Qing Yu (Harry) (H.Yu@derby.ac.uk)
• First Supervisor: Dr Ryan Groom (R.Groom@derby.ac.uk) 
• Second Supervisor: Dr Scott Nicholls (S.Nicholls@derby.ac.uk) 

Find out more about our research degrees.

Apply for this SE studentship post

Getting started

Before you begin your application, make sure you have:

Studentship funding reference code

This is provided on the individual studentship advert and must be specified in your application. 

Personal statement

A 500-word personal statement outlining your suitability for the studentship project. This is a mandatory requirement and you must upload it into your application. You should include your reasons for applying for the studentship, your experience in the field, how you feel you would benefit from studying and relevant information about your previous studies.

Your CV

A CV outlining your academic and professional experience.

Qualifications

Your qualification details including grades and dates taken. You will have the opportunity to upload scanned copies of your qualification certificates and transcripts in the application. If you have no formal qualifications, you can also state this in your application.

Passport/birth certificate

A scanned copy of your passport or full birth certificate. This will help us verify your application to study with us. International applicants can provide a copy of their passport only for visa assessment purposes, and their current visa if residing within the UK.

Academic references

Two signed academic references. This is optional at application stage but highly encouraged. If successful in your application, two academic references will be a mandatory requirement of admission. The references should be in written format, signed and dated from either a supervisor or tutor from your most recent studies.

For international applicants

The University of Derby has a network of international agents and representatives in different regions. For postgraduate research degree applications, depending on your country of origin, you may need to apply through an agent. You can contact any of our agents and apply to study with us through them.

Some agents may charge for provision of services so please check this directly with the agent. Please be aware that, if you apply directly to the University without going through an agent, we may contact you and you will be required to re-apply through an agent or representative before your application can be considered.