Master in Sport Analytics
The Master in Sports Analytics is your gateway to becoming a top match or data analyst in the sports industry. With a strong emphasis on practical learning and a comprehensive approach to performance analysis, this program will equip you with the skills to turn data into strategic insights. You will master AI-driven tools while developing a deep understanding of game dynamics and talent identification across various sports.
During this 9-month master’s program, you will explore the fundamentals of working with big data and learn how to extract the most valuable insights from data. We will guide you through data collection processes, the different ways to analyze them, and the key parameters that can enhance team and player performance. Alongside data analysis and artificial intelligence, you will also gain a deeper understanding of game dynamics and the essential steps to identifying top talent.
Private degree issued by Universidad Europea de Madrid
Classes in English | Villaviciosa de Odón | Start: 10 nov. 2025 | Faculty of Medicine, Health and Sport | Escuela Universitaria Real Madrid Universidad Europea |
Live the Real Madrid Experience
We present a brief summary of the most relevant milestones of the 2023-24 academic year, a year full of learning and unforgettable experiences.
Facilities

Join the AI in sports industry programme
AISports: artificial intelligence in sports
Be part of the AISports: Artificial Intelligence in Sports program. Train to lead the industry through innovation and artificial intelligence. Leadership is embedded in the DNA of our school, driven by a relentless pursuit of success and a passion for constant improvement.
Get ready to apply Artificial Intelligence in the sports industry. You’ll have the opportunity to learn from international experts in AI applied to sports through live online classes, access exclusive content, and develop your Final Master’s Project (TFM) centered on AI.
Study Plan
Module 1 - Introduction to the sports ecosystem (3 ECTS)
- Comprehensive overview of professional sports club structures and organizations.
- Key departments, roles, and processes in modern sports management.
- The transversal role of data: its impact on decision-making across sporting, medical, financial, and communication domains.
- Embracing a data-driven culture within sports organizations.
- Real-world examples of data-centric structures in various sports.
Module 2 - Fundamentals of sports analytics (6 ECTS)
- Historical evolution of sports analytics: from observational analysis to machine learning.
- Core statistical principles and their application in sports.
- Types of sports data (tracking, eventing, biometric, GPS, etc.).
- Introduction to ETL processes and the data lifecycle in sports.
- Case studies on data-informed decision-making across club departments.
Module 3 - Management and architecture of sports databases (6 ECTS)
- Foundations of relational (SQL) and non-relational (NoSQL) database design and management.
- Structuring databases to efficiently store and query sports data.
- Practical introduction to SQL tailored to sports databases.
- Integrating data from multiple sources and providers (tracking, scouting, external platforms).
- Data privacy and security protocols in athlete data management.
Module 4 - Programming for sports analytics: R, Python & advanced visualization tools (12 ECTS)
- Hands-on introduction to R and Python for sports data analysis and modeling.
- Data cleaning, transformation, and analysis using tidyverse and pandas.
- Building predictive and descriptive models with scikit-learn and caret.
- Advanced data visualization: dashboards with ggplot2, plotly, seaborn, and interactive libraries.
- Essentials of Tableau and Power BI for rapid reporting and executive dashboards.
- Automating visual reports and creating custom outputs for clubs and federations.
Module 5 - Computer vision & artificial intelligence in sport (6 ECTS)
- Core principles of computer vision applied to video and tracking analysis.
- Event, pose, and behavior pattern detection in sports imagery.
- Building deep learning models using TensorFlow and PyTorch.
- Real-world applications of AI in scouting, tactics, and physical performance.
- Case studies in football, basketball, tennis, and other disciplines.
Module 6 - Tactical intelligence: game analysis and sports performance (6 ECTS)
- Foundations of tactical and performance analysis in team sports.
- Designing and interpreting advanced individual and team metrics.
- Identifying game patterns and tactical trends using data.
- Role- and style-specific KPIs for performance evaluation.
- Creating tactical reports and presentations for coaching staff.
- Real-world examples of tactical analysis in clubs and national teams.
Module 7 - Strategic decision-making: data-driven scouting and sporting direction (6 ECTS)
- Essentials of modern scouting: data scouting, visual scouting, and hybrid models.
- Designing player profiles and tactical fit models.
- Talent evaluation through predictive modeling and scenario simulation.
- Squad building and market planning based on data insights.
- Tools for medium- and long-term decision-making in sports departments.
- Successful case studies in data-driven sports management.
Module 8 - Data in sports business management & data storytelling (6 ECTS)
- Business models in the sports industry: traditional and emerging revenue streams (ticketing, media rights, sponsorship, hospitality, digital commerce).
- Executive visualization and narrative for senior management: financial KPIs and executive dashboards.
- Data storytelling for executive leadership and marketing.
- Analytics of social media, digital platforms, and OTT services.
- Conversion funnels and data-driven activation strategies.
- Final workshop: Executive report on digital business.
Module 9 - Final Master's Project (6 ECTS)
- Group development of a project applied to a real-world case.
- Methodological supervision and mentoring by academic staff.
- Final evaluation and presentation.
Module 10 - Professional internship (3 ECTS)
Number of places for incoming students
20.
Graduate profile
This master's qualifies you to manage and lead professional sports analysis and data management projects. You will be able to work in roles such as:
- Sport Scientist, carrying out scientific analyses to optimise sports performance.
- Sport Data Scientist, managing large volumes of data to extract key information for decision-making.
- Data Scout, using data analysis to identify patterns and trends to discover talent.
- Scout, specialising in scouting for players and analysing the opposition for competitive teams.
- Match analyst, breaking down tactics, strategies and statistics to support coaching staff and improve team performance.
Employability
Career opportunities for sports analytics graduates
In sports departments
- Match analyst.
- Sports data scientist.
- Sports data engineer.
- Tactical analyst.
- Data scout.
- Data-driven sporting director.
- Performance analyst.
- Head of analysis department.
In management or transversal roles
- Sports data strategist.
- Business intelligence manager (sports sector).
- Sports marketing data analyst.
- Communication & data specialist.
- Visualization & reporting expert in sports.
- Consultant for digital transformation in sports organizations.
In emerging areas
- AI solutions developer for sports.
- Computer vision specialist for performance.
- Product owner in sports tech companies.
- Fan engagement & digital strategy specialist.
Admissions
Start your future at Universidad Europea
You can become a student at Universidad Europea in three easy steps.
1
Admission exams
Start your admission process by calling +34 911128850 or request information and our advisors will contact you.
2
Place reservation
Once you have been admitted, secure your place by paying the reservation fee.
3
Enrollment
Submit the required documents to formalise your enrollment.
Scholarships and financial aid
We want to help you. If you want to study at the Universidad Europea, you will have at your disposal a wide selection of own and official scholarships.
Credit recognition and transfers
You don’t have to stick with something you don’t like. That’s why we’ve designed specific plans for credit recognition and transfers.
Request your online credit recognition review, transfer your academic file and start studying at Universidad Europea.
Requirementes for admissions
For the access to the Master's Degree/University Specialist/University Expert it is necessary to meet one of the following requirements:
- To be in possession of a University Degree.
- If applicable, accredit professional experience of at least 6 months that is directly related to the field of the degree.
- If applicable, accredit professional internships of CFGS that are directly related to the scope of the degree.
Access profile
This Master aimed at professionals in the sports industry who want to build a career in the field of match and data analysis, such as:
- Graduates with a degree in physical activity and sports sciences
- Graduates with degrees such as engineering, mathematics, big data or other fields related to the area of knowledge.
- Coaches and members of coaching teams who want to understand match play better and to develop the skills needed to enable them to improve team and player performance.
- Former players who wish to transfer their skills and experience into the field of match analysis.
- Professionals working with new technologies with a passion for sport, who wish to use their knowledge to help develop this sector.