A KD Framework in Football Data Analytics: A Value Co-creation Framework for the Use of Knowledge Discovery Technologies in the Football Industry A doctoral thesis submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University By Khaled Shaban Department of Computer Science Loughborough University Supervisors Doctor Christian W Dawson And Doctor Shaheen Fatima February 2019 © by Khaled Shaban 2019 ACKNOWLEDGEMENT To Allah, God, thank you for helping me with strength, willingness, efforts and patience during my studies. To my mother, father, wife, kids, friends, and family for all their prayers, support and help. To my country and sponsors for allowing me to have this opportunity, experience, trusting me, and supporting me. To my supervisor Doctor Christian W Dawson for his continuous support and valuable feedback. To the Sport authorities, football federations, coaches and individuals who supported me. To Loughborough University for offering me the best research and study experience. To my Friends, I can not name them all, the ones who aid and helped me reaching the expertise individuals needed for the success of my research. To everyone that supported me during my research studies by any means. I would like to specially thank, My mother, Shadyah, for her prayers and continuous support, and I wish my success returns just part of her kindness and love that surrounded me. My lovely soulmate, Doctor Abeer Almakky for her support, advice and courage in my life. My father Professor Ghazy Almakky for his advice, courage and support during my studies. His words and wisdom were always there to support me. To my brothers and sisters, especially Ibrahim. I would like to thank my greatest boys, Mr Rayan and Mr Omar for allowing me the time to work on my thesis, and hopefully compensating them for the time and effort focusing on my studies away from them. Thank you all very much. I ABSTRACT Investment in sport technologies are expected to grow by 40.1% during 2016-2022 reaching approximately $3.97 billion by 2022. As well the recent changes in technology regulations by The Federation Internationale de Football Association (FIFA) since the 2018 World Cup created promising football technologies. This research questions addressing the issue of what is the value of such technologies for professional football teams? and what are the benefits of these technologies? This is achieved by developing a framework for understanding the value co-creation process from the knowledge discovery systems in the football industry. The framework aids in mapping the resources, pinpointing the outputs, identifying the competencies leading into capabilities, and finally in realisation of the value of the final outcomes in that journey. On another words, different teams have different resources that allow them to achieve certain outputs. These outputs enable the coaching team to achieve and maintain certain abilities. By changes in practice the will improve the team ability and enhance their analytical capabilities. Therefore, that will allow and aid the coaching team to gain new outcomes such as improving training strategies, transferring players, and informative match strategies. Additionally, improved understanding of the value co-creation process from the knowledge discovery systems in the football industry answering, why are some teams better able to gain value from investment in knowledge discovery technologies than other teams in the football industry. The framework has been developed in three phases in which semi-structured interviews where used in the first and second phases for developing and validating the framework respectively. The third and final phases is verifying the framework by developing a knowledge discovery maturity model as an online assessment’s tool in operationalising the research findings. The main contributions of this research are the adaptation and customisation of Melville et al. (2004) to develop a value co-creation process form knowledge discovery resources. Moreover, applying Agile (APM, 2015) artefacts and techniques and tools in improving the value co-creation process between coaches and data analysts. That’s aided in developing the value co- creation knowledge discovery framework in football analytics. Additionally, the development of a key performance indicators balanced scorecard and its adaptation as a in understanding the relationships between the key performance indicators (i.e. physical, psychological, technical and tactical performance indicators). Finally, the development II of the knowledge discovery maturity model in football analytics which was used in understanding and pinpointing areas of strength and weakness in the utilisation of the various football resources used in football analytics (human resources, technological resources, value co-creation resources and analytical models used). III GLOSSARY Term Details Definition (as defined by this research) A systematic iterative procedure intended to enable the development of models and KD Knowledge Discovery frameworks that can be used to study specific phenomena. KD resources used in the KD framework Knowledge Discovery (i.e. technological resources, human KDR Resources resources, value co-creation resources and their sub-models. Are used to measure players performance Key Performance KPI actions based on the related events or Indicators actions during a match or training. A multi-phases assessment model to reflect MM Maturity Model on current practices. The KDMMFDA developed in this research Knowledge Discovery KDMMFDA to assess the coaching team FDA strength Maturity Model and weakness. CT Case Team - Football Data FDA - Analytics PA Performance Analysis - Knowledge Discovery KDV - Value are a technique for the development of the User stores - features required to meet the specific goals of users A method used to improve communication Sprint - and gathering requirements. It a technique for maintaining the iterative need between the questions, research and Retrospective - result so that level or collaboration is achieved as will leading enhancing maturity level in the collaboration process over time. The mechanisms that a team manager utilises to select and recruit players in Transfer - fulfilment of the aim of achieving his Strategy overall objectives. The process of using a match model to understand the strength, weaknesses, Match - opportunities and threats (SWOT) of strategy opponents in the match environment, in order to help the team winning the match. Tactical Are metrics that are intended to measure the - KPIs ability of players to position themselves IV effectively in such a way the probability of passing, possessing, scoring and intercepting are improved. It is the ability to control the ball for the Technical - sake of accomplishing the required tasks KPI effectively and efficiently. Are those physiological and fitness measures for the players’ abilities. Some of them are traits that cannot be changed, such Physical - as the height and ambidexterity while KPIs others can be improved by training such as speed, high/moderate intensity running and recovery rate. Referees to the ability to play in the Psychological standard performance under different - KPIs psychological pressures, which can be called “resilience indicator”. Are equations or estimations used to Predictive - estimate the probability of scoring in a models variety of different situations. Is defined in this research as the Context- identification and measurement of the based players’ KPIs in different training and modelling match context Is a statistical method for the comparison Comparative between players or teams utilising different modelling KPIs. Is a technique used to identify the Synergetic correlation in a player performance with modelling others in the team V Table of Case Studies Wave One – Developing the framework Code Team / Bodies Role W1TD Football National Teams Technical Director & Expert (Coach, Player in Different Leagues) W1FC2 Football Club - 1st Team Coach W1DA3 Football Club - 1st Team Analysts W1DA4 Football Club 1st Team Analysts W1FC5 Football Club - Olympic Head Coach Team W1DA6 Football Club - Olympic Analyst Team W1FC7 National Olympic Team Coach W1FC8 Football Club - 1st Team Coach W1FC9 Football National Teams Assistant Coach W1DA10 Football Club 1st Team UK Analysts W1BM11 Football Organisation - UK Performance Analysis Team Member W1BM12 Football Organisation - UK Performance Analysis Team Member W1BM13 Football Organisation - KSA Technical Committee W1RS14 Rugby Club Director of Performance Analysis W1PSC15 Sports Data Consultancy Data/Video Analysts W1BM16 Football Organisation - KSA Technical Committee W1PSC17 Sports Data Specialists - UK Representative - Sports Data Specialist W1PSC18 Sports Data Specialists - Representative - Sports Data International Specialist W1PSC19 Sports Consultancy - KSA Manager – Football Data Specialist W1PSC20 Sports Consultancy - KSA Representative - Football Data Specialist W1PSC21 Sports Data Specialists Live Scouting Administration VI Wave Two – Validating the framework Code Team / Bodies Role W2TD1 Football National Team Director – Former Player – Former Teams Coach W2EM2 Football Federation Executive Manager of the Technical Committee W2TCM3 Football Federation Technical Committee Member – Professional coach W2FC4 Football Federation - Professional Coach – Academy Director – Football Club Academy Former National Team Coach W2FC5 Football Federation - Professional