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Sports Acoustics: Impact Sound Analysis in Cricket, Golf, Baseball and Tennis

University of Southampton School of Engineering
✓ Funded (Competition) 🎓 Acoustics 🎓 Engineering 🎓 Mechanical Engineering machine learning baseball cricket golf impact sound sports acoustics tennis physics-based modelling

Explore how the sounds of ball impacts reveal shot quality in four major sports. Analyze acoustic signals combined with physics models and machine learning to create new performance metrics. Gain experience with Hawk-Eye tracking technology and advance sports coaching tools.

AI-generated overview

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Why This Research Matters

This research unravels the acoustic signatures behind elite athletes' intuitive judgements, providing a scientific basis to a traditionally subjective experience. The project advances accessible, low-cost tools for coaching and performance analysis, potentially transforming sports training at all levels and enhancing athlete development worldwide.

Noise and vibration railway noise acoustics

Project Description

Project Overview

This project examines the physics and performance quality conveyed by impact sounds in cricket, golf, baseball, and tennis. By integrating acoustic analysis, physics-based modelling, and machine learning, the research aims to decode what the sounds of ball strikes reveal about shot quality, impact mechanics, and ball trajectory.

What You Will Do

You will conduct controlled experiments and analyze in-game data to validate acoustic models with tracking measurements. Collaboration with Hawk-Eye Innovations provides hands-on experience with leading sports tracking technology. You will study relevant taught modules in acoustics, dynamics, vibration, and machine learning, plus receive bespoke technical training.

Expected Outcomes

The project aims to develop robust, generalizable performance indicators from acoustic data that can bridge the gap between elite-level sports analytics and affordable coaching tools for grassroots sports.

Why This Matters

This research unlocks scientific understanding behind the intuitive judgments athletes make based on impact sounds. It has potential to provide accessible tools for performance evaluation, benefiting athletes, coaches, and sports technology industries globally.

Entry Requirements

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

How to Apply

Apply by choosing the Research programme for 2026/27 at the Faculty of Engineering and Physical Sciences, selecting full-time or part-time study, and searching for PhD Engineering & the Environment (7175). Include your CV, 2 academic references, degree transcripts, certificates, and English language qualification if applicable. Contact feps-pgr-apply@soton.ac.uk for queries, or G.Squicciarini@soton.ac.uk for initial conversation with project leader.

Eligibility

UK/Home
EU
International

Supervisor Profile

DG
Dr. Giacomo Squicciarini
University of Southampton, School of Engineering
1613 Citations
23 h-index
Google Scholar

Dr. Giacomo Squicciarini is a researcher specializing in acoustic engineering, vibration, and dynamics, working at the University of Southampton's School of Engineering. His research focuses on understanding sound signals in complex physical systems and applying data science techniques such as machine learning for innovative engineering solutions. He collaborates with industry leaders like Hawk-Eye Innovations, bridging academia and applied sports technology.

Key Publications

2018 82 citations
A state-of-the-art review of curve squeal noise: phenomena, mechanisms, modelling and mitigation
2019 70 citations
A model of a discretely supported railway track based on a 2.5 D finite element approach
2018 66 citations
Assessment of measurement-based methods for separating wheel and track contributions to railway rolling noise
2018 58 citations
An assessment of mode-coupling and falling-friction mechanisms in railway curve squeal through a simplified approach
2018 56 citations
Sound transmission loss properties of truss core extruded panels

Research Contributions

Studied phenomena, mechanisms, and mitigation techniques of curve squeal noise in railways.
Provides foundational understanding to reduce noise pollution and improve railway system design.
Developed finite element models to analyze railway track behavior and noise generation.
Improves predictive accuracy of railway track dynamics aiding design and maintenance.
Assessed measurement methods to separate wheel and track noise contributions.
Enables targeted noise reduction strategies enhancing urban and environmental sound quality.
Evaluated effects of mode-coupling and friction in railway curve squeal noise generation.
Supports development of engineering solutions to minimize curve squeal, improving passenger comfort.

More PhDs with Dr. Giacomo Squicciarini

Sports acoustics: Impact sound in cricket, golf, baseball and tennis
University of Southampton Dr. Giacomo Squicciarini Deadline: 31 Dec 2026

Analyse impact sounds in sports to reveal hidden performance data. Collaborate with Hawk-Eye Innovations and apply machine learning for cutting-edge sports acoustics research.

This research decodes the acoustic signatures of sports impacts to provide real-time performance feedback and democratize elite sports data…

7000+ citations · h40
Sports Acoustics Impact Sound Machine Learning Physics-Based Modelling
✓ Funded (Competition)
Added 3 months, 1 week ago View & Apply

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