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Start   >  Master's & postgraduate courses  >  Education  >  Postgraduate course in Sports Analytics
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  • discount

    Are you UPC Alumni? 15% discount if you enroll before July 1

  • discount

    10% discount if you enrol before 1 July

Presentation

Edition
4th Edition
Credits
15 ECTS (120 teaching hours)
Delivery
Face-to-face
Language of instruction
English
Fee
€4,500 €4,050(10% discount if you enrol before 1 July)
Payment of enrolment fee options

The enrolment fee can be paid:
- In a single payment to be paid within the deadline specified in the letter of admission to the programme.
- In two instalments:

  • 60% of the amount payable, to be paid within the deadline specified in the letter of admission to the programme.
  • Remaining 40% to be paid up to 60 days at the latest after the starting date of the programme.
Notes 0,7% campaign

Registration open until the beginning of the course or until end of vacancies.
Start date
Classes start: 22/10/2024
Classes end: 07/02/2025
Programme ends : 21/03/2025
Timetable
Tuesday: 6:00 pm to 9:00 pm
Thursday: 6:00 pm to 9:00 pm
Friday: 6:00 pm to 9:00 pm
Taught at
Facultat d'Informàtica de Barcelona (FIB)
C/ Jordi Girona, 1-3
Barcelona
Why this postgraduate course?
The importance of data in today's society is beyond any doubt, not only in fields strictly related to business, but also in the world of professional sport. Sports associations and institutions and private companies in the sector have a large amount of data, which require mechanisms for collection, storage and analysis to obtain the valuable information that an organisation needs.

Data management and analysis enables a differential value based on this information to be extracted, managed and generated. Today, sports analytics is a new area experiencing constant growth, and is fundamental for decision-making and team management.

The postgraduate course in Sports Analytics provides a unique opportunity to combine advanced data analysis and passion for sport. The training is carried out in partnership with Futbol Club Barcelona, one of world's leading clubs and a pioneer in data analysis in sport. This partnership means students can work with top-level data, event data and tracking data, and on solving applied problems. In addition, students will be able to obtain a real and privileged view of the application of sports analytics in a leading club in the field.

The postgraduate course provides a comprehensive and broad-based perspective of a data ecosystem applied to the sports field, with an in-depth look at data management and data analytics. The training provides an overview of all the components and tasks currently involved in the application of sports analytics.

After completing the postgraduate course, participants will be able to work professionally in football clubs and in other sports or in private companies, as well as in the field of consultancy and research for sports associations and companies.

Aims
  • Understand the paradigm of open data and be aware of the problems of data management and analysis in sports.
  • Practice using the main data management and analysis tools that are currently being applied to sport data analysis (event data and tracking data).
  • Identify the statistical or machine learning models that are most suitable for a given problem.
  • Be able to perform pre-processing of data.
  • Be able to evaluate the success rate of the proposed models.
  • Obtain specific knowledge about data management and analysis for decision-making.
Who is it for?
  • Graduates in computer science or equivalent qualifications, statistics, mathematics, physics or engineering.
  • Computer professionals, primarily developers, architects, data analysts and systems administrators, interested in data management and analytics applied to the sports sector.
Those interested must have technical training in centralised databases, programming and statistics.

Training Content

List of subjects
3 ECTS 24h
Sport Analytics
  • Introduction to sports analytics.
  • Introduction to game analysis.
  • Football methodology. Barça DNA.
  • Sports analytics in other sports.
  • Advanced data analysis in football.
  • Physical performance data.
  • Artificial intelligence applied to basketball.
4.5 ECTS 36h
Data Management
  • Introduction: big data, cloud computing and services engineering (XaaS).
  • Data management on cloud databases (NoSQL).
  • Distributed data processing and analysis.
  • The most commonly used unstructured and semi-structured data models.
  • Streams management.
  • Geospatial and trajectory data management.
  • Data integration and quality.
  • Visualisation.
4.5 ECTS 36h
Data Analysis
  • Introduction: basic statistics.
  • Statistical inference, sampling and validation of the method.
  • Statistical modelling and calibration of models.
  • Knowledge discovery in databases.
  • Principal component analysis.
  • Clustering methods.
  • Decision trees.
  • Classification methods: discriminant analysis y Support Vector Machine (SVM).
  • Neuronal networks.
  • Convolutional neural networks.
3 ECTS 24h
Final Project
The objective of this module is to put into practice the concepts explained in the 3 previous modules based on a case of use.
The UPC School reserves the right to modify the contents of the programme, which may vary in order to better accommodate the course objectives.
Degree
Postgraduate qualification issued by the Universitat Politècnica de Catalunya. Issued by virtue of the provisions of art. 7.1 of Organic Law 2/2023 of 22 March, concerning the University System, and art. 36 of Royal Decree 822/2021 of 28 September, which establishes the organisation of university education and the procedure for ensuring its quality. A prior official university qualification is necessary to obtain it. Otherwise, the student will receive a certificate of completion of the course issued by the Fundació Politècnica de Catalunya. Lifelong learning studies at the Universitat Politècnica de Catalunya are approved by the University's Governing Council on an annual basis. (See details appearing on the certificate).

Learning methodology

The teaching methodology of the programme facilitates the student's learning and the achievement of the necessary competences.



Learning tools
Participatory lectures
A presentation of the conceptual foundations of the content to be taught, promoting interaction with the students to guide them in their learning of the different contents and the development of the established competences.
Solving exercises
Solutions are worked on by practising routines, applying formulas and algorithms, and procedures are followed for transforming the available information and interpreting the results.
Case studies
Real or hypothetical situations are presented in which the students, in a completely participatory and practical way, examine the situation, consider the various hypotheses and share their own conclusions.
Tutorship
Students are given technical support in the preparation of the final project, according to their specialisation and the subject matter of the project.
Assessment criteria
Attendance
At least 80% attendance of teaching hours is required.
Level of participation
The student's active contribution to the various activities offered by the teaching team is assessed.
Solving exercises, questionnaires or exams
Individual tests aimed at assessing the degree of learning and the acquisition of competences.
Completion and presentation of the final project
Individual or group projects in which the contents taught in the programme are applied. The project can be based on real cases and include the identification of a problem, the design of the solution, its implementation or a business plan. The project will be presented and defended in public.
Work placements & employment service
Students can access job offers in their field of specialisation on the My_Tech_Space virtual campus. Applications made from this site will be treated confidentially. Hundreds of offers of the UPC School of Professional & Executive Development employment service appear annually. The offers range from formal contracts to work placement agreements.
Virtual campus
The students on this postgraduate course will have access to the My_ Tech_Space virtual campus - an effective platform for work and communication between the course's students, lecturers, directors and coordinators. My_Tech_Space provides the documentation for each training session before it starts, and enables students to work as a team, consult lecturers, check notes, etc.

Teaching team

Academic management
  • Abelló Gamazo, Alberto
    info
    View profile in futur.upc / View profile in Linkedin
    Holds a doctorate in Computer Science from the Polytechnic University of Catalonia (UPC). A lecturer in the Department of Service and Information System Engineering at the UPC. He teaches at both bachelor's degree level and on the Master's degree course in Innovation and Research in Informatics (MIRI), specialising in Data Science. He is the UPC coordinator of the Erasmus Mundus doctorate in Information Technologies for Business Intelligence - Doctoral College (IT4BI-DC).

    Furthermore, he has worked as a consultant with SAP, HP and the OMS, Fundació Probitas,  among others.
  • Madrero Pardo, Pau
    info
    View profile in Linkedin
    Graduate in Computer Science from the Universitat Politècnica de Catalunya (UPC). Master's degree in Innovation and Research in Informatics (MIRI) from the UPC majored in Data Science. Currently working as the Head of Sports Analytics at FC Barcelona, providing support in the field of data analysis to different teams within the club. He has been working in the club since 2019. He previously collaborated with a research team at the Universitat de Barcelona (UB) that participated in the Gaia project from the European Space Agency (ESA) to collect a three-dimensional map of the Milky Way.
Teaching staff
  • Abelló Gamazo, Alberto
    info
    View profile in futur.upc / View profile in Linkedin
    Holds a doctorate in Computer Science from the Polytechnic University of Catalonia (UPC). A lecturer in the Department of Service and Information System Engineering at the UPC. He teaches at both bachelor's degree level and on the Master's degree course in Innovation and Research in Informatics (MIRI), specialising in Data Science. He is the UPC coordinator of the Erasmus Mundus doctorate in Information Technologies for Business Intelligence - Doctoral College (IT4BI-DC).

    Furthermore, he has worked as a consultant with SAP, HP and the OMS, Fundació Probitas,  among others.
  • Aluja Banet, Tomàs
    info
    View profile in futur.upc
    Professor at the Polytechnic University of Catalonia (UPC). He is the author of 60 articles published in scientific journals or as chapters of a book. Research topics addressed: Multivariate analysis, data mining models, models for estimating intangibles and design of learning analytics systems. Member of scientific committees of international conferences (including Computational Statistics, COMPSTAT, and PLS). He has participated in various European and Spanish research projects in the field of systems based on statistical meta-data, data fusion and modeling of intangibles, and has been a statistical consultant for La Caixa, Kantar Media, Idescat and the City Council of Barcelona among others.
  • Arasa Salomon, Jordi
    info

    Diploma in Physical Education Teaching from the University of Barcelona (UB) and Football Coach from the Catalan Football Federation (FCF). He started working with FC Barcelona in 2007 as a football coach and analyst in formative stages. Technical Director of the BARÇA Academy projects in India (2012-2015) and Vancouver (2015-2017). He currently serves as Technical Director of the BARÇA Academy projects in the Asia Pacific and Middle East region.
  • Arbués-Sangüesa, Adrià
    info
    View profile in Linkedin
    Audiovisual systems engineer (2011-2015), who obtained a PhD in applied Computer Vision in Sports at the Department of Information and Communication Technologies of Universitat Pompeu Fabra (2017-2021). Currently working as a data scientist in the basketball division of Zelus Analytics, where he provides NBA teams with predictive models and new metrics. Former basketball coach in the youth teams of Futbol Club Barcelona.
  • Belanche Muñoz, Luis Antonio
    info
    View profile in futur.upc
    Graduated in Computer Science and holds a doctorate in Artificial Intelligence from the Universitat Politècnica de Catalunya (UPC). He is a professor in the Computer Science Department of the UPC with more than thirty years of teaching experience. He has supervised or tutored more than one hundred theses and student projects. He currently teaches on the bachelor’s degree in Data Science and Engineering, the master's degree in Innovation and Research in Informatics (MIRI), the master's degree in Advanced Mathematics and Mathematical Engineering (MAMME), the master's degree in Artificial Intelligence (AI) and the master's degree in Data Science at the Barcelona School of Informatics (FIB). He has authored more than one hundred and thirty publications in international journals and conferences, and has participated in fifteen research projects. He was recently head of studies at the Barcelona School of Informatics (FIB).
  • Gutierrez Pérez, Marc
    info
    View profile in Linkedin
    Graduate in Physics and Master's Degree in Modelling for Science and Engineering from the Autonomous University of Barcelona (UAB). Previously, member of the Sport Science department of F.C. Barcelona as a data scientist, his main role was the development of mathematical models to obtain qualitative and quantitative information on sports performance. Currently, PhD student at the Polytechnic University of Catalonia (UPC), where he is developing his thesis on Deep Learning and Computer Vison applied to Sport Science.
  • Jovanovic, Petar
    info
    View profile in futur.upc
    PhD in Computer Science from the Polythecnic University of Catalonia (UPC) and Université Libre de Bruxelles. MSc in Computer Science from the UPC. BSc in Software Engineering from University of Belgrade. His research is in the area of Business Intelligence, big data Management systems and distributed databases.
  • Madrero Pardo, Pau
    info
    View profile in Linkedin
    Graduate in Computer Science from the Universitat Politècnica de Catalunya (UPC). Master's degree in Innovation and Research in Informatics (MIRI) from the UPC majored in Data Science. Currently working as the Head of Sports Analytics at FC Barcelona, providing support in the field of data analysis to different teams within the club. He has been working in the club since 2019. He previously collaborated with a research team at the Universitat de Barcelona (UB) that participated in the Gaia project from the European Space Agency (ESA) to collect a three-dimensional map of the Milky Way.
  • Martín Buldú, Javier
    info
    View profile in Linkedin
    Industrial Engineer and PhD in Applied Physics from the Polytechnic University of Catalonia. Professor at the Rey Juan Carlos University, he is the Coordinator of the Complex Systems Group. In 2011, he founded the Biological Networks Laboratory of the Biomedical Technology Center (Madrid, Spain). He is an expert in the analysis of complex systems and their applications. In recent years, he has specialized in the analysis of football data understood as a complex system. He collaborates with La Liga and several football clubs.
  • Nadal Francesch, Sergi
    info
    View profile in futur.upc / View profile in Linkedin
    The holder of a doctoral degree in computer science from the Universitat Politècnica de Catalunya (UPC) and the Université Libre de Bruxelles (ULB). He is currently a lecturer in the Department of Service and Information System Engineering at the UPC, where he teaches in the Faculty of Computer Science on the bachelor's degree in Computer Engineering, the bachelor's degree in Artificial Intelligence and the master's degree in Data Science. His research interests are in the field of data and information management, as well as data lifecycle automation, an area in which he has published numerous papers and led technology transfer projects.
  • Reche Royo, Xavi
    info
    View profile in Linkedin
    Sport Science Bsc at Universitat de Barcelona (UB). Msc in Sport Performance at Universitat de Barcelona (UB). Bsc Applied Data Science at Universitat Oberta de Catalunya (UOC) in course. Sport Scientist at FC Barcelona (2014-2022). He is currently an endurance sports coach at R3ndurance and university lecturer in different degrees and master's degrees related to sports training.
  • Ric Diez, Ángel
    info

    PhD in Physical Activity and Sport Sciences from the University of Lleida (UdL). Professional Master in High Performance in Team Sports. National Football Coach. Football teacher at the National Institute of Physical Education of Catalonia (INEFC). Since 2014 he has been a member of the Complex Systems and Sport Research Group. He also was a part of the sports sciences department of FC Barcelona in the area of technology, analysis and innovation, and collaborated on various knowledge generation and dissemination projects with the Barça Innovation Hub.
  • Rodriguez Campayo, Carlos
    info
    View profile in Linkedin
    Graduate in Computer Science from the Universitat Politècnica de Catalunya (UPC) and Master in Innovation and Research in Informatics (MIRI) from UPC. He works in Sports Analytics Dept. at F.C. Barcelona, where he provides key features to aid coaches in analytical tasks through computer vision and machine learning. He is currently merging event and positional data to develop algorithms from tactical concepts in football and other sports.
  • Vázquez Alcocer, Pere-Pau
    info
    View profile in futur.upc
    PhD in software from the Universitat Politècnica de Catalunya (UPC). Professor at the UPC, he, currently, teaches undergraduate and master courses at UPC. He has previous experience teaching undergraduate and master courses in other universities such as the University of Nuremberg, the University of Girona, the Universitat Oberta de Catalunya, or the University of Vic. His research area focuses on scientific data visualization and computer graphics.

Associates entities

Strategic partners
  • Barça Innovation Hub
    • Participates in the design of the contents of the programme, and ensures they are appropriate to the needs of the professional sphere.
    • Provides teachers and lecturers.
    • Disseminates the programme in the professional sphere and area of expertise.
  • Fútbol Club Barcelona
    • Participates in the design of the contents of the programme, and ensures they are appropriate to the needs of the professional sphere.
    • Disseminates the programme in the professional sphere and area of expertise.

Career opportunities

  • Sports analytics consultant.
  • Sports data analyst consultant.
  • Sports data scientist.
  • Sports data engineer.
  • Sports data architect. 
  • Digital transformation leader.
  • Decisional systems engineer.

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How to start admission
To start the enrolment process for this programme you must complete and send the form that you will find at the bottom of these lines.

Next you will receive a welcome email detailing the three steps necessary to formalize the enrolment procedure:

1. Complete and confirm your personal details.

2. Validate your curriculum vitae and attach any additional required documentation, whenever this is necessary for admission.

3. Pay €110 in concept of the registration fee for the programme. This fee will be discounted from the total enrolment fee and will only be returned when a student isn't admitted on a programme.

Once the fee has been paid and we have all your documentation, we will assess your candidacy and, if you are admitted on the course, we will send you a letter of acceptance. This document will provide you with all the necessary information to formalize the enrolment process for the programme.




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