Sports acoustics: Impact sound in cricket, golf, baseball and tennis

This project examines how impact sounds in cricket, golf, baseball, and tennis reveal the physics and performance quality of each strike. Through acoustic analysis, physics-based models, and machine learning, it aims to reveal the information hidden in these acoustic signals. Cricket players instantly recognise a “sweetly struck” shot by sound, and golfers can interpret impact sounds signalling a perfect strike. Athletes use acoustic hints to judge shot quality and ball speed even before visual confirmation. This project investigates exactly what those sounds convey about impact mechanics and ball trajectory. You will integrate advanced sound data analysis with physics-based modelling and machine learning, validating acoustic models against tracking measurements from controlled experiments and in-game data. The project offers direct collaboration with Hawk-Eye Innovations, providing industrial placement opportunities with world-leading sports vision and tracking systems. You will also enrol in taught modules on acoustics, dynamics, vibration, and machine learning, plus access bespoke technical training linked to your research. This research aims to quantify high-fidelity performance data hidden in ball-equipment impact sounds for cricket, baseball, golf, and tennis. Outcome indicators will bridge elite-level tracking information and low-cost coaching tools accessible at grassroots level. Unlocking the science of impact sounds will empower athletes and coaches by providing objective, real-time feedback on shot quality beyond visual observation. The interdisciplinary approach and industrial partnership ensure innovative advancements at the intersection of sports engineering, data science, and acoustics.

You must have a UK 2:1 honours degree, or international equivalent, in engineering, physics, maths, computer science, or related scientific discipline. Demonstrate initiative in problem-solving, curiosity, passion for science, and teamwork ability.

Apply now by choosing research programme type, 2026/27, Faculty of Engineering and Physical Sciences; select full- or part-time; search PhD Engineering & the Environment (7175); add supervisor name in section 2. Submit CV, 2 academic references, degree transcripts, certificates, and English qualification if applicable.