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Middlesex University Research Repository An open access repository of Middlesex University research http://eprints.mdx.ac.uk Parmar, Nimai (2017) Determining, scoring and presenting successful performance in professional rugby league. PhD thesis, Middlesex University. [Thesis] Final accepted version (with author’s formatting) This version is available at: https://eprints.mdx.ac.uk/23235/ Copyright: Middlesex University Research Repository makes the University’s research available electronically. Copyright and moral rights to this work are retained by the author and/or other copyright owners unless otherwise stated. The work is supplied on the understanding that any use for commercial gain is strictly forbidden. A copy may be downloaded for personal, non-commercial, research or study without prior permission and without charge. 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See also repository copyright: re-use policy: http://eprints.mdx.ac.uk/policies.html#copy DETERMINING, SCORING AND PRESENTING SUCCESSFUL PERFORMANCE IN PROFESSIONAL RUGBY LEAGUE A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY NIMAI CHANDRA PARMAR LONDON SPORT INSTITUTE FACULTY OF SCIENCE & TECHNOLOGY MIDDLESEX UNIVERSITY SEPTEMBER 2017 ABSTRACT Performance indicators allow for the objective quantification of performance (Vogelbein, Nopp & Hokelmann, 2014). However, limited PI research for professional rugby league exists, with just one paper published (Woods, Sinclair and Robertson, 2017) although this was conducted on teams from the Australian elite competition, the NRL, with no similar attempts for Europe’s Super League competition. Therefore, this thesis aimed to identify robust indicators of success for professional rugby league teams in super league, which would subsequently allow performances to be scored and assessed graphically through performance profiles. Data from all 27 rounds of the 2012, 2013 and 2014 European Super League seasons were collected by Opta, amounting to 567 matches. Data for 45 action variables was extracted from spreadsheets using Visual Basic for Applications in Microsoft Excel (Excel, v2013, Microsoft Inc., Redmond, USA). To enable clear comparisons between winning and losing teams, draws (n=22) were excluded. Study 1 assessed twenty-four relative variables (home value minus away) using backwards logistic (match outcome) and linear (points difference) regression models alongside exhaustive Chi-Square Automatic Interaction Detection (CHAID) decision trees to identify performance indicators (PIs) and key performance indicators (KPIs). However, some variables which were thought to be important (as identified by previous literature) were removed from the analysis as they did not contribute to the model’s predictive ability as much as others thus calling into question the appropriateness of stepwise methods. Furthermore, unusual results were evident which lead to the conclusion that a suitable dimension reduction technique could be more appropriate to analyse large datasets with multiple variables that could be related to each other. I Study 2 utilised principal component analysis to reduce 45 action variables into 10 orthogonal principle components. These components were analysed using backwards and enter methods in logistic and linear regression models alongside CHAID decision trees. This method provided a relevant guide on how teams could improve their performance by improving a collection of variables as opposed to traditional methods which described individual variables. Furthermore, the use of stepwise methods was argued to be less appropriate for sporting performances as some principal components that could relate to success may be removed. Results from both regression models indicated large variations on confidence intervals for beta coefficients and odds ratios, suggesting that the variation of a set of values are more representative of the data analysed, when assessing multiple teams. Therefore, idiographic assessments of performances were suggested to provide relevant information for practitioners, which can be lost through traditional nomothetic approaches, as evidenced in this study. Study 3 utilised the principle component scores to create idiographic performance profiles, according to match venue and match closeness. In addition, a case study was produced assessing two teams’ previous performances, prior to an upcoming game, providing a practical example of how practitioners could utilise this information in their respective environments. Although large variations were evident on profiles, it was suggested that team performances may never stabilise due to the unpredictability of complex sports involving multiple players like rugby league. However it was clear that idiographic profiles provided meaningful and informative assessments of performance which were arguably more relevant for practitioners compared to traditional nomothetic methods. II Overall, this thesis facilitated a greater understanding of how rugby league teams perform in Super League, through the use of practical and relevant methodologies that can be utilised by practitioners and coaches who are constantly striving to improve sporting performance. Future research must consider the ‘theory- practice’ gap identified by McKenzie and Cushion (2013) in order to provide simple and relevant answers that practitioners require, which seems to be a principle that has remained elusive thus far. III ACKNOWLEDGEMENTS I would like to dedicate this PhD to my late Father. I was only able to take on this challenge through his financial support and backing. He had picked up extra hours to cover my tuition fees up until I was awarded a fully funded studentship in 2013. Sadly, he suddenly passed away a year later in 2014. He was a very kind and loving father and selflessly supported our family. His selfless dedication to supporting me embark on this journey has certainly carried me through every challenging moment since. I would like to express appreciation and gratitude to my Mother. She has been my source of inspiration and strength, setting the standard for myself and my brothers, having excelled academically as an Advanced Skills Teacher, Head Teacher and finally now an Education Consultant. She was awarded a Fellowship in Religious Education through Oxford University, despite raising three children and enduring many personal adversities, she has managed to have a successful career. She has guided us through many fun and tough challenges and the completion of this PhD would not have been possible without her continued emotional and financial support. I would like to express sincere gratitude to my director of studies Professor Nic James for his kindness and commitment given to developing my research skills and teaching. I met Nic seven years ago, in 2010 at Middlesex University after he had come into one of my Lectures and offered 5 students the chance to travel to Hungary to participate in a two-week EU funded intensive programme in performance analysis of sport. I was lucky enough to achieve top grades on that course, and embarked on a research dissertation upon my return. My passion for performance analysis was ignited! Nic encouraged me to enrol on a PhD and I was awarded a fully funded IV studentship a year later. On reflection, it was Nic’s continuous encouragement, guidance and support that enabled all of these achievements. I therefore offer my heartfelt and sincere appreciation to him. Meeting him has been life changing and I hope that I can transfer the research skills and knowledge gained, to my teaching and research output in the future and help students I encounter to achieve their best. I would also like to thank Dr. Rhonda Cohen, Head of the London Sport Institute at Middlesex University for her constant guidance and support. Despite an extremely busy workload she has always made time to see how my research was going and to offer words of encouragement through challenging times. She has also supported me to gain considerable teaching experience at Middlesex which has been a rewarding and fulfilling challenge. I know I would not have been able to submit this Thesis without her support and encouragement. Finally, I would like to thank Opta for providing me access to their rugby league data and my supervisors Dr. Andrew Greenhalgh and Professor Mike Hughes for their help and contribution towards the completion of this thesis. Mike is known as the ‘godfather of performance analysis’, after a long and successful academic career, founding the International Society of Performance Analysis