Composition Partnership

1. Università degli Studi di Napoli Federico II, Italy (Coordinator and Host Institution)
2. Instituto Politécnico de Viana do Castelo, Portugal  (Co-host Institution)
3. IE University, Spain (sending institution)
4. International school for social and business studies, Slovenia (sending institution)
5. Technische Universität Dortmund, Germany (sending institution)
6. Technische Universität München, Germany(sending institution)
7. Athens University of Economics and Business, Greece (sending institution)

Topic of the program

This course offers an in-depth exploration of sports analytics, focusing on the application of data science and machine learning techniques to sports data. The programme aims to provide analytical skills to create, manage and interrogate large datasets applicable to or derived from the sports industry. Participants will learn to analyse and interpret complex data structures, develop predictive models and understand team and player performance, strategy and the business of sport. In addition a set of programming tools will facilitate the implementation of models and enable participants to analyse decision-making processes.

This course provides the analytical requirements of a sports management programme. It is aimed at all students interested in data science as well as sports analysts and stakeholders. 

At the end of the BIP, participants will be able to: 
-Improve their ability to build empirical models and implement them through specification, estimation and simulation using the R package.
- Gain an understanding of basic statistical concepts and their applications in the world of sport.
- Develop proficiency in data collection, cleaning, and analysis.
- Obtain a broad overview of the methods used in the acquisition, processing, analysis, visualisation and implementation of sports data.
- Understand the role of analytics in sports decision-making

Schedule description

a. Description of the physical component

The course consists of one week in presence (8 September - 13 September 2025) organised as described below.

Face-to-face: 6 days

-----------------------------------------------------------------------------

September 8, 2025

• Full day
  
  Lecture: Social Network Analysis: introduction with sport example
  
  Main topics: Introduction to Network Analysis, Graph Theory and Visualization, Descriptive and Inferential Methods, Software Tools: R Packages and Pajek, Applications of Network Analysis in Sports.

-----------------------------------------------------------------------------

September 9, 2025

• Morning
  
  Lecture: Modeling and Prediction of Match Outcomes
  
  Main topics: Modeling and Predicting Match Outcomes, Generalized Linear Models (GLMs), Regression and Classification Trees (CARTs), Random Forests for Sports Analytics, Applications to Football, Handball, and Tennis.
   
• Evening
  
  Laboratory lectures – supervised tutorial

-----------------------------------------------------------------------------

September 10, 2025

• Morning
  
  Lecture: Methods for dimension reduction and clustering in Sport Analytics
  
  Main topics: Clustering mixed type nominal/ordinal/interval data, Joint dimension reduction and clustering. Supervised and unsupervised learning.
   
• Evening
  
  Laboratory lectures – supervised tutorial, individual and team work

-----------------------------------------------------------------------------

September 11, 2025

• Morning
  
  Lecture: Latent variable models in sport surveys analytics
  
  Main topics: Latent variables, Classical Test Theory, Item Response Theory, IRT models for polytomous items
   
• Evening
  
  Lecture: Double Poisson Models
  
  Main topics: Game strategy and tactics analysis, Player performance evaluation, Team dynamics and performance metrics, Internal and external load quantification for Load Management

-----------------------------------------------------------------------------

September 12, 2025

• Morning
  
  Lecture: Injury Analytics
  
  Main topic: Sports injury prevention, Risk injury modelling.
   
• Evening
  
  Summary, feedback, alternative methods, wrap-up

-----------------------------------------------------------------------------

September 13, 2025

Group Workshop & Collaborative Activities

• Informal group work and reflection sessions; Peer exchange on project outcomes and learning experiences; Cross-cultural interaction and networking activities; Social engagement and farewell gathering

These activities are designed to foster team collaboration, consolidate the learning outcomes of the in-person week, and strengthen intercultural exchange among participants.

b. Description of the virtual component 

The course includes 4 virtual sessions (Live virtual sessions) organised as follows:

-----------------------------------------------------------------------------

September 3, 2025
 

• 10:00 - Welcome and introductions by the academic partners to greet the students.
   
• 10:20 - “Transforming Coaching: Data Science for Practical Applications to Sports Performance Analysis.” 
  Sotirios Drikos, Assistant Professor, Didactics and Theory of Training in Volleyball, National and Kapodistrian University of Athens, School of Physical Education and Sport Science
   
• 11:20 - “Performance analysis in sports: Physical assessment and monitoring.”
  Rui Miguel Silva, Professor Adjunto Convidado, Instituto Politécnico de Viana do Castelo, Portugal

-----------------------------------------------------------------------------

September 4, 2025 - Quarto dashboards

• 10:00 - Main topics: Introduction to Quarto for Reporting and Visualization. Building Interactive Dashboards with Quarto. Integrating R Code and Output into Dashboards. Customizing Layouts and Themes. Exporting and Sharing Dashboards for Sports Analytics.

-----------------------------------------------------------------------------

October 10, 2025 - The Quarto authoring tool

• 10:00 - Main topics: Introduction to the Quarto Authoring Tool. Multilingual Computation: R, Python, Julia, Observable JavaScript (hints). Output Formats: HTML, MS Word, and PDF. Types of Quarto Reports: Embedded Code, External Code, Parametric Reports.

-----------------------------------------------------------------------------

October 20, 2025

• 9:30 - Welcome address by institutional representatives
   
• 9:45 - Introduction: Maria Iannario, BIP coordinator
   
• 9:50 - "Advanced regression to handle varying dispersion when modeling anxiety in volleyball"
  Moritz Berger, Group Leader, Central Institute of Mental Health, Mannheim
   
• 10:30 - Presentation of results from BIP participants
   
• 11:30 - "Introduction to Basketball Analytics: How to Start with Data-Driven Decisions"
  Christos Marmarinos, Basketball Coach / Sacramento Kings Int’l Scout
   
• 12:40 - "Sports, Data, and Society: A Statistical Perspective"
  Michele Gallo and Lucio Palazzo, University of Naples L'Orientale
   
• 13:10 - Concluding remarks: Maria Iannario

Practical information

- Level of students: Master and PhD students

- Number of ECTS: 3 

- Main language of instruction/training: English

- Venue of Activities (City, Institution): Naples, Department of Political Sciences, University of Naples Federico II (Statistics Laboratory and G4 room)

Open Badge has been associated with our program, providing a digital recognition of the skills and achievements gained through participation.
Further details at: https://bestr.it/badge/show/4685?ln=en
https://bestr.it/project/show/229?ln=en 

Course information, main materials used by BIP Faculty and professionals will be available at: https://indico.unina.it/e/bip25

In addition, a tutor will be available for each participant during the training period (weekly online mentorship from Sport Analytics experts) and a dedicated programme manager provided by BIP Faculty will be available virtually. These figures will act as support in the learning and skills development phase.