Data Mining and Machine Learning in High-Performance Sport: Performance Analysis of On-Field and Video Assistant Referees in European Soccer Leagues

This book explores the application of data mining and machine learning techniques in studying the activity pattern, decision-making skills, misconducts, and actions resulting in the intervention of VAR in European soccer leagues referees. The game of soccer at the elite level is characterised by intense competitions, a high level of intensity, technical, and tactical skills coupled with a long duration of play. Referees are required to officiate the game and deliver correct and indisputable decisions throughout the duration of play. The increase in the spatial and temporal task demands of the game necessitates that the referees must respond and cope with the physiological and psychological loads inherent in the game. The referees are also required to deliver an accurate decision and uphold the rules and regulations of the game during a match. These demands and attributes make the work of referees highly complex. The increasing pace and complexity of the game resulted in the introduction of the Video Assistant Referee (VAR) to assist and improve the decision-making of on-field referees. Despite the integration of VAR into the current refereeing system, the performances of the referees are yet to be error-free. Machine learning coupled with data mining techniques has shown to be vital in providing insights from a large dataset which could be used to draw important inferences that can aid decision-making for diagnostics purposes and overall performance improvement.

A total of 6232 matches from 5 consecutive seasons officiated across the English Premier League, Spanish LaLiga, Italian Serie A as well as the German Bundesliga was studied. It is envisioned that the findings in this book could be useful in recognising the activity pattern of top-class referees, that is non-trivial for the stakeholders in devising strategies to further enhance the performances of referees as well as empower talent identification experts with pertinent information for mapping out future high-performance referees.​

Dr Rabiu Muazu Musa holds a Ph.D. degree in Sports Science from Universiti Sultan Zainal Abidin (UniSZA), Malaysia. He obtained his M.Sc. in Sports Science from UniSZA and his B.Sc. in Physical and Health Education at Bayero University Kano, Nigeria. His research activity focused on the development of multivariate and machine learning models for athletic performance. His research interests include sports performance analysis, health promotion, sport and exercise science, talent identification, test, and measurement as well as machine learning in sports. He obtained several research grants both as principal and co-investigator. He is an active reviewer to many reputable journals and currently serving as an academic editor for PLOSONE as well as the executive guest editor for the Open Sports Science Journal and SN Applied Sciences. He authored many publications in myriad journals, conference proceedings, books as well as chapters in books. He is currently a senior lecturer at the Centre for Fundamental and Continuing Education, Universiti Malaysia Terengganu.

Dr Anwar P.P. Abdul Majeed graduated with a first-class honours B.Eng. in Mechanical Engineering from Universiti Teknologi MARA (UiTM), Malaysia. He obtained an M.Sc. in Nuclear Engineering from Imperial College London, United Kingdom. He then received his Ph.D. in Rehabilitation Robotics from the Universiti Malaysia Pahang (UMP). He is currently serving as an associate professor at the School of Robotics, XJTLU. Prior to joining XJTLU, he was a senior lecturer (assistant professor) and was the head of Programme (Bachelor of Manufacturing Engineering Technology (Industrial Automation)) at the Faculty of Manufacturing and Mechatronics Engineering Technology, UMP. He is also currently serving as an adjunct lecturer at UCSI University, Malaysia. Dr Anwar is also a visiting research fellow at EUREKA Robotics Centre, Cardiff Metropolitan University, UK. Dr Anwar is a chartered engineer, registered with the Institution of Mechanical Engineers (IMechE), UK, a member of the Institution of Engineering and Technology (IET), UK, as well as a senior member of the Institute of Electrical and Electronics Engineers (IEEE). His research interest includes rehabilitation robotics, computational mechanics, applied mechanics, sports engineering, renewable and nuclear energy, sports performance analysis as well as machine learning. He has authored over 60 papers in different journals, conference proceedings as well as books. He serves as a reviewer in a number of prolific journals such as IEEE Access, Frontiers in Bioengineering and Biotechnology, SN Applied Sciences, PeerJ Computer Science, Applied Computing and Informatics amongst others. He has also served as a guest editor for SN Applied Sciences, MDPI, Frontiers as well as an editor for several Springer book series. He is currently serving as an academic editor for PLOS ONE, a review editor for Frontiers in Robotics and AI, and a section editor for Mekatronika (UMP Press). Dr Anwar is also a member of the Young Scientists Network of the Academy of Sciences Malaysia (YSN-ASM). With regards to learned/civil society activities, he is an active member of the IET Malaysia Local Network as well as acting as a liaison officer for the Imperial College Alumni Association Malaysia.

Assoc. Prof. Dr. Mohamad Razali Abdullah obtained his Bachelor of Physical Education in 1989 from Universiti Putra Malaysia (UPM). He obtained his M.Sc. in Sport and Exercise Science from the University of Wales Institute, Cardiff, in 1998, and in 2007, he received his Ph.D. in Sports Science from UPM. His research interests include motor control, sports biomechanics, motor performance, and machine learning in sports. He is currently an associate professor at East Coast Environmental Research Institute Universiti Sultan Zainal Abidin, Terengganu, Malaysia

Assoc. Prof Dr Garry Kuan is an associate professor of the Exercise and Sports Science Programme, School of Health Sciences, Universiti Sains Malaysia, and a research fellow at the Brunel University, London, United Kingdom. He completed his Ph.D. in Sport Psychology at Victoria University, Melbourne, Australia. Presently, Garry is the secretary-general of the Asian-South Pacific Association of Sport Psychology (ASPASP), the secretary-general of the Malaysian Sport Psychology Association (MASPA), the executive board member of the Asian Council of Sports Science (ACESS), and the scientific committee of the World Exercise Medicine. He is the recipient of the 2021 International Society of Sport Psychology (ISSP) Developing Scholar Award, the 2021 Ten Outstanding Young Malaysian, the 2021 Asia Outstanding Academician of the year, the 2020 IFPEFSSA International Eminent Educator Award, A-CIPA Young Researcher Award at the 27th International Congress of Applied Psychology, International Scholars Award at the ICSEMIS pre-Olympic conference, and the Atsushi Fujita Research Scholarship at the 6th ASPASP conference. His research interest includes sport psychology, neuroscience, health promotion, test and measurements, and music. During his social time, he plays the first violin professionally and teaches communities to play various musical instruments.

Dr. Mohd Azraai Mohd Razman graduated his first degree from the University of Sheffield, UK, in Mechatronics Engineering. He then obtained his M.Eng. from Universiti Malaysia Pahang (UMP) in Mechatronics Engineering as well. He then completed his Ph.D. at UMP specifically in the application of machine learning in aquaculture. His research interest includes optimisation techniques, control systems, signal processing, instrumentation in aquaculture, sports engineering as well as machine learning. He is currently serving as a guest editor for SN Applied Sciences in a number of topical collections. He has also edited a number of volume in Springer's LNEE and AISC series. He is currently serving as the editor-in-chief for MEKATRONIKA: Journal of Mechatronics and Intelligent Manufacturing under UMP Press.