Mark is the course lead and lecturer on the BSc Sport Performance Analysis degree and is currently completing his PhD at the University College Dublin where he is an active member of the Natural Computing Research & Applications Group, having previously completed a BSc (Hons) in Applied Sports Science at Loughborough University.
Prior to joining the University, Mark was a senior data scientist at EY and also held the role of Research & Innovation Lead at STATSports Group where he developed novel applications of wearable technology to enhance player tracking and analysis, having also conducted research to establish new methodologies, models and algorithms to support training load management and performance in team sports. During his time at STATSports Mark also accumulated significant applied experience working with a wide range of professional sporting teams and organisations across the world. This notably included providing sport science support to the Irish U20, French and South African senior men’s rugby teams. As well as the Arsenal senior men’s and USA U20 soccer teams.
Mark has a strong background in computer science and his research interests include; the application of machine learning, deep learning and artificial intelligence to plan, manage and support team sport training, the development of decision support systems and the application of operational research to the effective management of sports performance, the use of data mining and mathematical modelling techniques to uncover spatio-temporal patterns in team sport movement and performance, the application of wearable technology to assess athlete readiness and fatigue, the development of new modelling approaches to complement and enhance our understanding of the athlete training performance relationship.
Currently, Mark provides sport science and analytics consultancy to professional clubs and international sports teams specialising in athlete monitoring, performance analysis and data analytics.
A current list of Mark’s publications can be found at https://www.researchgate.net/profile/Mark_Connor5