Master’s Degree in Sports Science and Data Intelligence in High-Performance
Learn to transform physical performance data into decisions for training planning, workload monitoring, injury prevention and performance improvement. Master Big Data, Artificial Intelligence and sports technology to optimise physical preparation in professional football.
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Training sports AI professionals
In the Sports Data Campus ecosystem
Master's degrees certified by UCAM
With our certified diplomas
Big Data and Artificial Intelligence for Physical Preparation in Football
The Master’s Degree in Sports Science and Data Intelligence in High-Performance integrates Big Data, Artificial Intelligence and sports technology to analyse physical performance, optimise workload monitoring, prevent injuries and improve decision-making in training and competition.
Practical applications covered in the programme include:
- Physical performance analysis using data and advanced metrics.
- Workload monitoring and quantification using GPS, wearable devices and sports technology.
- Injury prevention through continuous performance analysis.
- Creation of dashboards with Power BI and Tableau to support decision-making.
- Performance evaluation before, during and after competition.
IN COLLABORATION WITH:
Who Is the Master’s Degree in Sports Science and Data Intelligence in High-Performance For?
The Master’s Degree in Sports Science and Data Intelligence in High-Performance is designed for fitness coaches, coaches, performance analysts, rehabilitation specialists, physiotherapists and sports professionals seeking to apply data, Artificial Intelligence and sports technology to physical performance monitoring.
It is also suitable for graduates in Sports and Exercise Science, Physiotherapy, Engineering, Data Science and related fields who want to specialise in physical preparation, training monitoring and injury prevention in football.
The programme develops skills in performance analysis, workload monitoring, data visualisation, player tracking and decision-making within clubs, academies and sports organisations.
IINS Recognition · March 2026
The Institute for Spanish Sports Quality grants this extraordinary distinction to Sports Data Campus, in recognition of its leadership, impact, and outstanding contribution to the strategic development of the sports ecosystem, and certifies that the institution meets the requirements and standards established for the sports quality seal.
At Sports Data Campus, we sign the best instructors for you
Career Opportunities
Graduates of the Master’s Degree in Sports Science and Data Intelligence in High-Performance will be prepared to work in professional clubs, academies, high-performance centres and sports technology companies in roles such as:
Physical Performance Analyst
Analyses training and competition data to optimise performance, monitor workloads and reduce injury risk.
Data-Driven Strength and Conditioning Coach
Designs, plans and adapts training programmes using objective data and sports technology.
Sports Data Scientist
Develops predictive models to assess physical performance, prevent injuries and support decision-making.
Sports Technology and Wearables Specialist
Manages GPS systems, sensors, monitoring platforms and wearable devices to track athlete performance.
Sports Performance Consultant
Advises clubs, academies and sports organisations on implementing data-driven performance strategies.
Injury Prevention Specialist
Analyses risk indicators and designs prevention protocols supported by data and performance metrics.
Sports Science Researcher
Participates in research projects involving physical preparation, performance analysis and emerging sports technologies.
Sports Data Analysis Specialist
Designs dashboards, reports and analytical models to support decision-making within performance departments.
ACCESS TO THE INTERNATIONAL PROGRAM IN
SCHOLARSHIPS
Access the international scholarship programme for the Master’s Degree in Sports Science and Data Intelligence in High-Performance and discover the available funding options to specialise in data analytics and Artificial Intelligence applied to professional sport.
Why Study the Master’s Degree in Sports Science and Data Intelligence in High-Performance?
This programme prepares you to apply data analytics, Artificial Intelligence and sports technology to training planning, workload monitoring, injury prevention and physical performance improvement. You will learn to interpret data and transform it into informed decisions within professional clubs, academies and performance departments.
Por que fazer o nosso Mestrado?
Realizar um mestrado no Sports Data Campus permitir-te-á formar-te com especialistas do setor, adquirir ferramentas avançadas para gerir e analisar dados aplicados ao desporto, e destacar-te num mercado em constante evolução que exige profissionais altamente capacitados
UNIQUE EDUCATION
Exclusive, industry-focused content
LEADING CAMPUS
A global community focused on Big Data and sports
OVER 3,100 STUDENTS
Professionals trained across major leagues and sports
REAL PARTNERSHIPS
Over 100 professional clubs and teams
CONTINUOUS SUPPORT
We are always available to support you
NETWORKING
Discover opportunities within our professional community
OFFICIAL CERTIFICATION
Master’s degree certified by UCAM
TOP FACULTY
Masterclasses and exclusive events with industry experts
SCHOLARSHIPS
Discover our scholarship and study support programme
PROFESSIONAL PORTFOLIO
Build a portfolio through your final project and practical work
What we offer you
THE PROGRAM
A TRAINING PROGRAM THAT WILL REVOLUTIONIZE THE WORLD OF PHYSICAL PREPARATION IN FOOTBALL. HERE IT IS:
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MODULE 1. INTRODUCTION TO BIG DATA (3 ECTS)
1. Introduction to Big Data.
2. Application of Big Data in sports.
3. Theoretical introduction to data processing.
4. Theoretical introduction to data storage.
5. Theoretical introduction to data analysis.
6. Theoretical introduction to data visualization.
MODULE 2. THE ROLE OF THE “SPORTS SCIENTIST” AND THE “HEAD OF PERFORMANCE” (6 ECTS)
2. The role of the Head of Performance within a club’s organizational structure.
3. Performance department models: structures and resources.
4. Technological tools and data flows in physical performance.
5. Key indicators: load, fatigue, recovery, and readiness.
6. Coordination between departments: analysis, coaching staff, and medical services.
7. Visualization and reporting: dashboards, presentations, and technical meetings.
8. Real cases: how performance departments operate in professional clubs.
9. Soft skills of the performance leader: communication, leadership, and change management.
10. Challenges and the future of the Sports Scientist in modern football.
MODULE 3. DATA-PROVIDING TECHNOLOGIES IN PHYSICAL PREPARATION (5 ECTS)
2. Introduction to load quantification using these technologies.
3. Metrics and indicators of physical performance.
4. Metrics and indicators for injury-related processes.
5. Understanding and using the data obtained.
6. Practical case: assessment of physical performance.
7. Practical case: injury rehabilitation.
8. Practical case: minimizing injury incidence.
MODULE 4. BASIC DATA PROCESSING: DATABASES IN EXCEL (3 ECTS)
2. Basic concepts of databases.
3. Data management: Power Query.
4. Advanced database concepts: Pivot Tables and Dashboards.
5. Charts and data visualization.
6. Use cases in football.
MODULE 5. ADVANCED DATA PROCESSING AND VISUALIZATION: ETL TOOLS, TABLEAU, POWER BI (6 ECTS)
2. Types of physical and conditional data.
3. ETL – Pentaho Data Integration.
4. Tableau.
5. Microsoft Power BI.
MODULE 6. ADVANCED ANALYTICS OF TECHNICAL-TACTICAL ASPECTS WITH TABLEAU (4 ECTS)
- Introduction to Tableau Public.
- Elements of Tableau Public.
- Main data providers and sources: MediaCoach, Wyscout, Scout7, and StatsBomb.
- Own analysis: enhancing the game model and team positioning within its competitive environment.
- Justification of own analysis from a micro perspective.
- Opponent analysis: from data to video.
- Goalkeeper analysis.
- Designing an operational strategy.
- Application to training.
MODULE 7. ADVANCED ANALYTICS IN STRENGTH TRAINING APPLIED TO FOOTBALL (3 ECTS)
1. Isoinertial strength assessment through execution velocity and data analysis.
2. Strength assessment with inertial devices through execution velocity and data analysis.
3. Monitoring strength training and fatigue control through execution velocity.
4. Isokinetic strength assessment and data analysis.
5. Strength assessment using hand dynamometers, strain gauges, or load cells and data analysis.
6. Assessment of jumping ability and isometric tests of the posterior chain using force platforms: data analysis.
7. Calculation of the strength–velocity profile through jumps and sprints.
8. Strength assessment: recording, data analysis, and injury prevention.
MODULE 8. ADVANCED ANALYTICS IN INJURY REHABILITATION (3 ECTS)
2. Intrinsic and extrinsic risk factors in different pathologies.
3. Injury mechanisms in different pathologies.
4. Pre- and post-injury assessments.
5. Progression criteria in the different phases of injury rehabilitation.
6. Load quantification using GPS devices during the rehabilitation process.
7. Practical examples of different injuries.
MODULE 9. “DATA-DRIVEN DECISION” IN PERFORMANCE OPTIMIZATION IN FOOTBALL (6 ECTS)
2. Metrics and performance indicators in football.
3. Process of load quantification.
4. “Worst-case scenario.”
5. Acute-to-chronic ratio.
6. Relationship between physical parameters and the game.
7. Performance evaluation and conditional development in youth football.
8. Post-session use case.
9. Microcycle use case.
10. Post-match use case.
MODULE 10. INTRODUCTION TO PYTHON AND DATA ANALYSIS FOR PHYSICAL PREPARATION (6 ECTS)
- Introduction to Python for Data Science
- Language fundamentals and development environments (Colab, Jupyter Notebook)
- First scripts: variables, basic structures, and functions
- Statistical Fundamentals Applied to Performance
- Types of variables and descriptive statistical measures
- Hypothesis testing applied to sports
- Effect size and relationships between variables
- Data Cycle in Sports Environments
- Phases of data analysis: from collection to presentation
- Practical application in real cases in sports and physical preparation
- Acquisition of Real Data
- Reading sports files (CSV, Excel)
- Basic use of APIs and other automated data sources
- Data Preparation and Cleaning
- Detection and handling of outliers and missing values
- Common transformations: normalization, encoding, scaling
- Automation of Analysis Processes
- Creation of complete workflows: data input – analysis – output
- Applied example: calculation of a player’s physical profile
- Visualization and Presentation of Results
- Creating graphs with Python (Matplotlib, Seaborn)
- Automatic generation of reports for the coaching staff (PDF, HTML)
MODULE 11. APPLICATIONS OF MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE IN SPORTS PERFORMANCE (6 ECTS)
-
Introduction to Machine Learning
- What is Machine Learning and why is it relevant in sports?
- Differences between supervised, unsupervised, and reinforcement learning
- Lifecycle of an ML model: training, validation, deployment
-
Types of Models and Use Cases in Physical Preparation
- Classification: detecting physical states (fatigue, risk)
- Regression: predicting performance metrics (distance, power)
- Clustering: segmenting players by physiological or technical profiles
- Applied cases: automatic thresholds, load anomalies, error detection in data
-
Generative Artificial Intelligence and AI Assistants
- What is generative AI and how it differs from other types of AI
- Applications in sports: automatic report generation, narrative dashboards
- Personalized virtual assistants (chatbots with natural language + data)
- Practical example: creating a generative AI assistant to prepare weekly load reports
-
Model Implementation and Automation
- Basic integration in physical analysis workflows (input – model – output)
- Basic production concepts: APIs, automation with scripts
- Monitoring models in use: detecting failures or changes in data
-
Hands-on Practice with Python and Accessible Tools
- Key libraries: Scikit-learn, Pandas, Streamlit, LangChain, OpenAI
- Creating functional prototypes without advanced programming
- Model documentation and collaboration with technical teams
MODULE 12. MASTER’S FINAL PROJECT (12 ECTS)
2. Data Collection
3. Data Cleaning
4. Machine Learning Analytical Model
5. Visualization
6. Conclusions
7. References
You will work with these providers of football data, tools, and video analytics platforms
ACADEMIC DIRECTION
David Sáez
CEO of Sports Data Campus, Big Data International Campus at ENIIT (Innova IT Business School)
He is the CEO of Sports Data Campus (Big Data International Campus). He holds a Master’s in Project Management, a Master’s in Sales and Marketing Management, and is an expert in Leadership and a Master’s in Internet Application Development. He is also the CEO of ENIIT (Innova IT Business School). He has over 20 years of experience leading e-learning projects for top-tier companies, both nationally and internationally. He is an expert in educational technology, e-learning, new methodologies, and the production and management of postgraduate courses and LMS platforms.
Cristóbal Fuentes
Head of Performance at Elche F.C
He holds a degree in Physical Activity and Sport Sciences from the University of Granada. He also holds a Master’s degree in Injury Prevention and Rehabilitation endorsed by the Spanish Olympic Committee (COE) and the Royal Spanish Football Federation (RFEF), as well as a Master’s degree in Teacher Training. In addition, he is a UEFA PRO licensed coach and holds an Advanced Certificate in Tensiomyography. His expertise lies in physical performance analysis through the use of EPTS (GPS) technology.
His professional career has been developed across different structures and competitive levels in both domestic and international football, from youth development stages to the professional game. He has worked with clubs including Lucena CF, Granada CF, Córdoba CF, Cultural y Deportiva Leonesa, AD Alcorcón, CD Tenerife, Real Oviedo, SC Internacional, Charlotte FC and Malmö FF in Sweden. He currently works at Elche C.F. He also brings experience in international tournaments, further strengthening his perspective on performance in high-demand environments.
He combines his professional career in football with his role as Academic Director at Sports Data Campus.
Alberto Méndez
Head Fitness Coach at Al-Sadd SC
He holds a degree in Physical Activity and Sports Sciences from the University of Las Palmas. He also completed a Master’s in Exercise Physiology at The University of Western Australia and holds a PhD in Sports Sciences from the University of Oviedo.
He teaches in various national and international Master’s and postgraduate programs. He is currently responsible for strength and conditioning and injury rehabilitation for the Qatar National Football Team. Previously, he led the Physiology and Physical Preparation Department at ASPIRE Academy (Qatar). As a researcher, he has published over 100 articles indexed in the JCR.
INSTRUCTORS
WORLD-CLASS FACULTY AT YOUR SERVICE
Cristóbal Fuentes
Head of Performance at Elche F.C
Luis Suárez
Head of Performance at FC Lugano
Alberto Méndez
Head Fitness Coach en Al-Sadd SC
Oliver Gonzalo Skok
External Advisor for Professional Footballers and Clubs
Hani Al Haddad
Head of performance at Al-Qadsiah de Arabia Saudi
Pepe Lázaro
Head of Performance at Al Qadsiah F.C.
Jose Antonio Romero Caballero
Consultor Stratebi
Pablo Sanzol
Sports Technical Secretary at Deportivo Alavés
David Fombella
Big Data Consultant at StrateBI and Academic Co-Director
Javier Fernández
Senior Data Scientist at Sportian
MASTERCLASS
ANALISTAS PROFESIONALES, DIRECTORES DEPORTIVOS, ENTRENADORES, STAFF…
LUCAS BRACAMONTE
Professional Extension Director
André Silveira
International Development Officer at Sports Data Campus
ANDRÉS LÓPEZ SAGARRA
Physical Coach & Sport Scientist at Aspetar
Maurici A. López-Felip
CEO & Co-Founder of Kognia Sports Intelligence
Ismael Fernández
PhD in Physical Activity and Sports Sciences (CAFYD) and Co-founder of ThermoHuman
Asier Extebarría
Director of Business Development at Voon Sports
Víctor Escamilla
Research Departament Specialist at ThermoHuman
Andre Pawlowski
Customer Success Specialist at Catapult- Tactics and Coaching
Joshua Lee
Customer Success Specialist at Catapult
Do you want to work in professional environments?
Sports Data Campus Professional Extension
Sports Data Campus Professional Extension connects you with the job market. If you study one of our master’s programs, we help you take the next step in your career.
BECAUSE COLLABORATION IS STRENGTH
PROUD OF OUR ECOSYSTEM OF PARTNERS, WHICH KEEPS GROWING EVERY DAY
Clubs, Federations, Confederations and Sports Entities
Companies and Industry
WHAT OUR STUDENTS SAY
We are extremely proud of every student who has trained at Sports Data Campus and is now part of this great family.
Thank you all for your effort and support! 🙂
Pablo Alzamora
Han sido meses intensos, llenos de aprendizaje, desafíos y descubrimientos, donde confirmé cuánto disfruto analizar el juego, comprenderlo desde los datos y transformarlos en conocimiento útil.
Nikolaos Georgiadis
After months of hard work, I’m proud to share the final project for my MSc in Big Data Analytics in Football at Sports Data Campus and UCAM Universidad Católica San Antonio de Murcia. …
Giannis Kastritis
Special thanks to André Silveira Castanho, Lucas Bracamonte, Pablo Jiménez-Bravo Bonilla, David R. Sáez Ávila for your support and the opportunities you are giving me throughout this journey!
Mateusz Micuda
Proud to present my final project, which concludes my studies in the MSc in Data Analytics in Football at Sports Data Campus: “Dino Toppmöller’s own project — Tactical analysis of Eintracht Frankfurt in the 2024/25 season.”
Kananelo Moleko
I’m proud to share that I’ve officially completed my MSc in Data Analytics in Football, delivered by Sports Data Campus and certified by UCAM Universidad Católica San Antonio de Murcia (Spain)
Sebastien Van Renterghem
A few months ago, I took on a new challenge by starting the Master’s in “Set Pieces in Football” at Sports Data Campus. Since then, I haven’t regretted it for a single moment. Under the guidance of Austin MacPhee (Aston Villa & Portugal NT), José Rodríguez Calvo (Real Sociedad), and other (guest) lecturers, I’ve already learned so much.
Eduardo Francisco Guerrero Ordaz
I’m happy to share that I’ve completed my MSc in Data Analytics in Football at UCAM Universidad Católica San Antonio de Murcia and Sports Data Campus! …
Mateusz Micuda
Special thanks to my tutor Pablo Sanzol, as well as Pablo Jiménez-Bravo Bonilla and Pedro Jiménez, who were always there to support us and offered a firm, positive push when needed
Nikolaos Georgiadis
I would like to sincerely thank Sports Data Campus, Pablo Jiménez-Bravo Bonilla, PEDRO JIMÉNEZ, David R. Sáez Ávila and the rest of the staff for this unique opportunity that helped me watch both tournaments through a completely new lens, that of a football analyst.
Ben Tredinnick
I want to thank all of the tutors and speakers who helped give me the knowledge and skills in order to complete this interesting project and course.
Damián Alberto Rivitti
Esta experiencia me permitió ampliar la mirada y conectar con nuevas herramientas y métodos que pude aplicar en el Área de desarrollo del Club Atlético Independiente.
Fabio De Teyssonnière Barreto
Gratitude: Thank you to my family, friends, colleagues, and the Sports Data Campus faculty for your support and inspiration throughout this journey. Your encouragement made all the difference.
Frequently Asked Questions
VACIO
El Big Data ha abierto una puerta transversal para su óptima aplicación al deporte, en concreto, al fútbol. Por ello, es una herramienta útil para reforzar la construcción de la dirección deportiva. Es muy difícil entender uno de los estamentos más importantes de un club de fútbol sin la aplicación del dato de forma profesionalizada. En definitiva, el dato es un pilar básico que ayuda a optimizar procesos, así como a detectar talento en cualquier competición y a reducir al mínimo el factor suerte.
- Big Data y fútbol.
- Estructura, organización y planificación de una dirección deportiva de fútbol.
- Los pilares básicos de una dirección deportiva.
- El seguimiento en bruto y en neto.
- Los perfiles.
- La negociación.
- La adaptación.
- El dato y la reducción del factor suerte.
- La cantera..
Is the Master’s Degree in Sports Science and Data Intelligence in High-Performance right for me?
Yes. The programme is designed for strength and conditioning coaches, coaches, performance analysts, physiotherapists, rehabilitation specialists and sports professionals who want to use Big Data, Artificial Intelligence and sports technology to improve physical performance and prevent injuries.
Do I need previous experience or programming skills?
No. The programme follows a progressive approach, beginning with the fundamentals of data analytics before introducing the tools and technologies used in physical preparation and high-performance sport.
Contact Pedro on WhatsApp and resolve your questions about the programme.
Can I study this master’s degree without previous experience in data analytics?
Yes. Many students begin the programme without previous experience in data analytics or programming. Its methodology helps you progressively acquire the skills needed to work with physical performance data and the tools used by professional clubs and sports organisations.
What qualification will I receive after completing the programme?
After completing the programme, you will receive the qualification awarded by UCAM, as well as additional certifications linked to tools and technologies used in professional sport through the programme’s collaborating organisations.
VACIO
El Big Data ha abierto una puerta transversal para su óptima aplicación al deporte, en concreto, al fútbol. Por ello, es una herramienta útil para reforzar la construcción de la dirección deportiva. Es muy difícil entender uno de los estamentos más importantes de un club de fútbol sin la aplicación del dato de forma profesionalizada. En definitiva, el dato es un pilar básico que ayuda a optimizar procesos, así como a detectar talento en cualquier competición y a reducir al mínimo el factor suerte.
- Big Data y fútbol.
- Estructura, organización y planificación de una dirección deportiva de fútbol.
- Los pilares básicos de una dirección deportiva.
- El seguimiento en bruto y en neto.
- Los perfiles.
- La negociación.
- La adaptación.
- El dato y la reducción del factor suerte.
- La cantera..
How does the programme accommodate working professionals?
The online format allows you to combine the programme with work and other responsibilities. You can organise your studies flexibly and progress according to your availability.
Are the classes recorded?
Yes. All sessions are recorded so that you can access the content whenever you need it and continue following the programme even if you are unable to attend a live class.
Does the programme provide opportunities to connect with sports professionals?
Yes. You will learn alongside lecturers, professionals and students connected with professional clubs, academies and sports organisations, creating opportunities for networking and the exchange of knowledge and experience.
What financing options are available?
Different financing options and flexible payment plans are available. Our admissions team will provide personalised guidance to help you identify the option that best suits your circumstances.
Contact Pedro on WhatsApp to learn about the available financing options.
Take the Next Step in Your Career
Request information about our programmes and speak with the Sports Data Campus academic team. We will provide personalised guidance and answer your questions about our methodology, entry requirements, career opportunities, available programmes and admissions process.
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