This module introduces students to the general concepts of statistics and data analysis and the role of data-generated insight for sports performance, participation and business functions. It will provide the students with the appropriate tools to generate, summarise, visualise and analyse sports-related datasets and report the results in an appropriate format. It provides the students with the ability to apply appropriate statistical techniques to data sets gathered during project work and also to comment on, and rate techniques used in existing studies.

1. Explain and critique the theory, growth and application of data-based intelligence in sports performance, sports participation and sports business
2. Ethically apply appropriate skills and techniques in the areas of data set generation, data mining, dataset evaluation and classification for participation, performance and other sports related data.
3. Use appropriate techniques to visualise sports participation, performance and business data.
4. Describe and justify the selection and application of appropriate statistical techniques for the analysis of sports related data.
5. Use appropriate software to automate the mining, analysis and visualisation of sports related data.

This module aims to introduce basic concepts, principles, methods and techniques of data analytics and AI for sport. It will develop skills and techniques for practical applications of data analytics using AI and machine learning through engagement in pattern discovery with data. The importance of pattern discovery with applications for data analytics will be explored. Data mining processes including data cleaning, preparation, and exploration algorithms will be introduced along with machine learning algorithms for clustering, classification, regression, and prediction.

1. Explain the concept of ‘big data’ and critically analyse data strategy and procedures in the context of a human-centred, ethical and inclusive approach to data
2. Critically evaluate the quality and potential limitations of sports data sets and identify strategies to clean and structure datasets appropriately
3. Manage data incorporating data architecture, cloud computing, databasing, and data mining
4. Apply and evaluate data mining techniques and models for knowledge discovery in sport related datasets
5. Apply machine learning algorithms and appraise the potential benefits and challenges of their use within sporting contexts

Digital Transformation for Sport is about leveraging digital technology to revolutionise the sports industry. The integration of digital technologies into all areas of sports, fundamentally changes how sports organisations operate and deliver value to stakeholders, including fans, athletes, and sponsors, and by making sports more accessible, engaging, and efficient. This module is an introduction to key concepts of digital transformation in sport in terms of people, processes and technology. It will equip students with the knowledge and skills to audit the different phases of digital transformation in a sporting context, identify potential opportunities for and barriers to digital change.

1. Critically assess the digital and technological landscape in sport and physical activity at global and local levels.
2. Critically evaluate how digital technologies can be applied within defined scenarios.
3. Apply digital transformation principles and processes to solve complex problems and/or opportunities.
4. Assess the ethical, legal and sustainability considerations of digital transformation.
5. Develop and communicate a strategic digital transformation plan within a defined scenario.

In this module, students will develop the expertise required to lead digital change within sporting organisations. With input from industry leaders and peers, students will focus on developing realistic, feasible and sustainable digital and change management strategies within the sports industry.

1. Assess digital transformation skills and competencies of oneself and others.
2. Analyse the relationship between organisation culture, sustainable development goals and digital transformation.
3. Critically evaluate digital transformation and change management frameworks.
4. Develop and communicate leadership in a strategic digital transformation plan within a defined scenario.

Digital innovation is the process of utilising digital technologies and strategies to create new or improved products, services, processes, and business models. This module will challenge students to become design thinkers and who come up with innovations for sport that can rewire organisational products, services, processes, and business models. This module enables the learner to develop functioning knowledge by participating and reflecting on the process of defining, designing, developing, implementing and presenting an innovative prototype as part of a team and contextualised to an agreed scenario. Students will be equiped with the skills to advocate for human centred product development and undertake effective project management.

1. Effectively organise and manage a project using appropriate techniques and skills.
2. Evaluate and apply digital innovation frameworks.
3. Collaborate, ideate and co-create a product/service/process/business model prototype within an agreed defined scenario.
4. Professionally communicate and demonstrate the prototype to stakeholders.
5. Take ownership of their role in the development of an innovation prototype as part of a team.

Research methodology is an integral part of any Masters course. The aim of this module is to ensure that students will be fully competent to devise, run and present research in a professional manner. This module will be part of a number of different Masters programmes in the Department of Sport, Exercise and Nutrition. The module will introduce students to both qualitative and quantitative approaches to research enquiry.

1. Systematically review and evaluate current literature, using appropriate tools and techniques.

2. Identify, analyse and evaluate appropriate research methods for research project proposal development.

3. Demonstrate the synthesis and integration of knowledge.

4. Draft a research proposal appropriate to their career stage and aligned with their research interests.

5. Create an appropriate data management structure.

6. Communicate research in various formats including written and oral presentation methods.

This module will equip students with a comprehensive understanding of digital marketing technologies and their application to promote and generate revenue streams in sporting organisations. Students will learn how digital technology is driving customer engagement across numerous channels/platforms and providing excellent customer experience is a prerequisite for organisations.

1. Design and implement Digital and Social Media Marketing strategies.
2. Evaluate the role of digital technology in Customer Experience
3. Critically assess Marketing technology platforms
4. Evaluate the role of emerging technology in marketing
5. Critically assess the importance of relationship management in sports marketing

In this module, students will explore the impact advanced computing, networks, mobile applications, the Internet of Things (IoT), artificial intelligence, immersive experiences (augmented reality (AR) and virtual reality (VR)) and Web 3 are having on sports business, performance, and participation. Students will gain the knowledge and skills to critique and evaluate new technological solutions in sporting contexts such as smart stadia, ticketing, performance measurement and participation monitoring. Students will also critique and evaluate the validity and accuracy of new technologies against existing, more established methods.

1. Identify and describe recent technological advances in sport, and applications in sports business, performance and participation.
2. Critically evaluate the functionality and applicability of a range of emerging technologies, including an evaluation of the advantages and disadvantages of these technologies from the point of view of the end user and/or analyst.
3. Evaluate the validity and accuracy of new technologies against more established methods, through reviewing published literature and appropriate statistical testing.
4. Examine future trends in digital innovations and technologies in sport, understanding how continued advances will impact on sports business, performance and participation.

Learning design is the deliberate crafting of experiences designed to support learning. In elite sport, the role of technology and data in providing feedback to athletes is now a multi-billion euro industry, built on the assumption that learning occurs with this feedback. Applied performance analysts use sports technology to generate, curate and translate data which ideally leads to better decision-making for players, coaches and sports executives. Despite this growth in the use of technology for sports feedback, few practitioners are trained to design environments which optimise learning or try and measure if learning and knowledge translation is happening. Thus there is often little understanding of the return on investment for this technology. This module introduces students to the principles of learning design in performance sport and the digital tools which support the planning, delivery and evaluation of performance feedback. Students will design and critically evaluate learning interventions and strategies for performance sport.

1. Critically evaluate learning environments in sporting ecosystems and how these can be assessed.
2. Critically asses theories and frameworks for learning design and evaluation and understand how they apply in performance sport environments.
3. Design, implement and evaluate learning interventions appropriate to organisational context.
4. Use digital tools to create appropriate aims, storyboards and materials to support learning interventions in sporting contexts.
5. Design a learning strategy based on an environmental assessment of a sports performance environment.

Sports organisations are spending significant amounts of money on technology and digital platforms which they assume are making an impact on performance. As with technology in all domains, the most critical element for success and impact is in how it is deployed and this usually lies with the professionals involved.

This module aims to provide students with an advanced knowledge and understanding of the systems and processes which optimise value co-creation in professional practice in sport. Students are supported to undertake personal and peer reflection on their professional practice, and to design and implement professional development plans.

1. Critically analyse the professional behaviours which add value to a performance ecosystem.
2. Use reflective practice to critically assess personal and professional development.
3. Conduct appropriate environmental assessments (to include a technology audit), individual and group needs analysis within the performance ecosystem.
4. Effectively select and use the tools and strategies for self and service management, appropriate to the level of experience and expertise.

This module will equip students with an advanced knowledge of programming and scripting skills needed for the effective use of data analytics libraries and software. Students will learn how to select efficient data structures for numerical programming and to use these appropriately to transform data into useful and actionable information in the sports sector.

1. Understand the fundamentals of data architecture and programming for complex sports systems and the strengths and limitations with real-world examples.
2. Develop competence in handling and processing of data and identifying the opportunities and challenges of incorporating data analytics to improve the development and testing of complex sports systems.
3. Critically assess the methodological challenges and gain understanding of the principles of database management including data ingestion, storage, processing, and sharing.
4. Apply data analytics, including traditional statistics and machine learning techniques, to implement relevant workflow for data visualisation, analysis, and communication. Undertake data wrangling and exploratory data analysis with appropriate libraries and software.

Technologies like Virtual, Augmented and Mixed Reality form a suite of available media to develop applications for immersive experiences. Along with wearable devices and the Internet of Things, there are a significant number of pathways available to develop applications for data visualisation and connected sport solutions for players, fans and coaches.

This module will focus on these technologies and the necessary programming to give students the practical insights into developing applications tailored for enhancing the sporting experience, analysing performance metrics and facilitating informed decision-making in sports for the various stakeholders. The technologies and often the data to be displayed provide a practical opportunity to deploy AI and machine-learning based solutions in this space.

Throughout the module, the students will be motivated to use a computational thinking approach to decompose the challenges identified and to adopt a digital mindset in the development of the appropriate solutions.

1. Critically evaluate the range of technologies available to build connected, immersive applications in a sporting context.
2. Analyse and provide examples of appropriate use of technology in applications to enhance the engagement of players, fans and coaches.
3. Develop practical applications using immersive, connected or wearable technology within the sports landscape.
4. Critically evaluate the impact of these immersive, connected technologies on the sports industry and its stakeholders.