"PhD Studentship - Assessment of Gait Characteristics using Video-based Skeletal Tracking Data"

Manchester Metropolitan University

Placed On: 18th February 2026
Closes: 13th May 2026
Reference: SciEng-MW-October 2026-27-Gait Characteristics

The accuracy and precision of opto-electronic 3D motion capture systems created a global shift towards lab-based biomechanical analysis over the last 30 years. With the advent of AI and machine learning new video-based technologies are becoming increasingly available to analyse athlete’s movement in their competitive environment, marking a shift away from the laboratory. FIFA have indeed implemented this type of skeletal tracking system into their Video Assistant Referee (VAR) process by adopting Semi-Automated Offside Detection (SAOD) technology. Whilst this is a very specific application to aid referee decision-making there are many other potential applications for this type of technology and data.

The ability to capture the detailed movement of 22 players and officials around the entire pitch and over the full duration of the match takes the landscape of biomechanical analysis into a new era. Given the size of the calibrated area and unscripted movements during a football match there are a number of questions relating to the accuracy of this kinematic data, and this forms the basis of this research programme. This project has the potential to redefine the future of biomechanical analysis in sport, validating FIFA approved skeletal tracking systems.

The project forms a partnership between Manchester Met and FIFA’s Innovation Department.

Project aims and objectives

The overarching aim of this project is to develop new, scientifically valid applications of skeletal data extracted from video-based skeletal tracking for use in football.

Project Objectives

• Compare kinematic descriptors of football movement skills from FIFA approved skeletal tracking partner(s) data against recognised gold standard motion capture system(s).
• Conduct a feasibility study around the potential adoption of innovative applications based on current FIFA approved skeletal tracking data within different parts of the football ecosystem.
• Develop and evaluate a new innovative application for use with FIFA partners.

Funding

Only home students can apply. Tuition fees will be covered for the duration of the three-year award, which is £5,006 for the year 2025/26.

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.

Specific requirements of the candidate

Essential

• A first class or upper second-class (2:1) degree (or equivalent) in a sport-related discipline or computer science.
• A keen and active interest in technology for sports performance analysis.
• Competent in using biomechanical techniques or technologies to analyse movement.
• Experience and competence in analytical / programming software to code and analysis data.

How to apply

Interested applicants should contact Dr Phil Graham-Smith (p.graham-smith@mmu.ac.uk) for an informal discussion.

To apply, you will need to complete the online application form for a full-time PhD in Sports & Exercise Science.

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest.

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Expected start date: October 2026

Please quote the reference: SciEng-MW-October 2026-27-Gait Characteristics