Emerging Trends in the Sports Industry
Code: 44834 ECTS Credits: 9| Degree | Type | Year | Semester |
|---|---|---|---|
| 4316022 Sport Management | OT | 0 | A |
Contact
- Name:
- Núria Masferrer Llabinés
- Email:
- nuria.masferrer@uab.cat
Teaching groups languages
To check the language/s of instruction, you must click on "Methodolody" section of the course guide.
External teachers
- Enric Ripoll
- Raúl Peláez
- Verónica Codina
- Víctor Jordan
Prerequisites
There are no prerequisits.
Objectives and Contextualisation
- Gain insight into the evolving landscape of the sports industry, including its legal and governance aspects, digital transformation, and the role of data science.
- Learn essential management tools, digital transition strategies, and the impact of social networks, Big Data, and AI in sports organizations.
- Explore the unique data challenges and opportunities in sports, from fan engagement and performance analysis to IoT, AI, and blockchain applications, while building practical analytics skills.
Learning Outcomes
- CA15 (Competence) Apply new technologies, especially digitisation, to decision-making, especially in (intra)entrepreneurial projects.
- CA16 (Competence) Compare and contrast different ways (traditional and new) to offer products and services in the sports market and identify the potential market.
- CA17 (Competence) Question the different possibilities of business models whilst taking into consideration the aspects related to Industry 4.0 and environmental sustainability.
- KA21 (Knowledge) Recognise new market trends in the sports industry.
- KA22 (Knowledge) Identify the main current technological solutions that can be applied to the sports industry, as well as those that will be possible in the near future.
- SA33 (Skill) Implement activities using new technologies available for existing products and services in the sports industry in order to strengthen competitiveness.
- SA34 (Skill) Come up with proposals for new business opportunities based on new trends in the sports industry.
Content
Part 1: Sports Law and Governance
Part 2: Digital Transformation
- Management tools for the digital transformation of a sports organization
- The transition in the digital transformation of an organization
- Social networks as a basic communication tool
- Data management: Big Data and Smart Data
- Future impact of digital transformation in the sports industry
Part 3: Data Science
- Data in sports vs. other industries.
- Fan engagement data and analytics.
- Performance analysis.
- The role of IoT in sports.
- Machine learning and Artificial Intelligence in sports to predict/avoid results (sports and business).
- Potential cases and uses of Blockchain in sports (sports passports of athletes, medical records, smart contracts).
- Build your own analytics.
Methodology
Online modality
In the case of the online modality, the methodology will be adjusted in order students can achieve all the learning outcomes specified in this guide and at the same time develop the skills and abilities of the subject.
To this end, the resources available in the modle classrooms will be optimized to maximize student involvement and motivation (forums, debates, simulation games, case studies, online presentations, etc ...)
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Activities
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Participatory theoretical session | 45 | 1.8 | KA21, KA22, SA33, SA34 |
| Problem solving, exercises in the ordinary classroom | 15 | 0.6 | CA15, CA16, CA17, KA21, KA22 |
| Type: Supervised | |||
| Study cases | 15 | 0.6 | CA15, CA16, CA17, KA21, KA22 |
| Supervision of group work and class discussions | 15 | 0.6 | CA15, CA16, CA17, KA21, KA22 |
| Type: Autonomous | |||
| Problem solving, exercises | 30 | 1.2 | CA15, CA16, CA17, KA21, KA22, SA33, SA34 |
| Studying hours | 90 | 3.6 | CA17, KA21, KA22, SA33, SA34 |
Assessment
Theoretical-practical tests/tasks: Submission of tasks; Presentation and defence of the exercises and works carried out (they can be individual and/or in group).
Individual theoretical and practical works: Delivery of exercises and works, as well as participation in forums and debates.
The teaching team will detail the specific activities at the beginning of the module.
Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Applied activities to be solved and submitted | 40% | 5 | 0.2 | CA15, CA16, CA17, KA21, KA22, SA33, SA34 |
| Exam | 30% | 2 | 0.08 | KA21, KA22, SA33 |
| Individual theoretical and practical activities | 30% | 8 | 0.32 | CA15, CA16, CA17, KA21, KA22, SA33, SA34 |
Bibliography
Complementary readings:
- "Sports Law and Regulation: Cases, Materials, and Problems" by Matthew J. Mitten, Timothy Davis, Rodney K. Smith, and Robert C. Berry.
- "Sports Analytics and Data Science: Winning the Game with Methods and Models" by Thomas W. Miller.
- "Sport Business Analytics: Using Data to Increase Revenue and Improve Operational Efficiency" by C. Keith Harrison and Scott Bukstein.
- "Sports Data Analytics: Using Data to Improve Performance and Win More Games" by Daniel A. Y. Fort.
Software
N/A