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R code, data and functionsSupplementary materials for reproducing the case studies presented throughout the book. The zip file contains datasets (Table 1.11), R scripts (Table 1.12), additional functions (Tables 1.13-1.14). An overall overview of supplementary materials is in Table 1.15. See sections 1.2 and 1.3 for details. Functions in the file additional_functions.R Code tested on both Windows and macOS, using R version 4.5.2 and RStudio version 2025.09.2+418, and on Ubuntu Linux 25.10 (64-bit, kernel 6.17) using R version 4.5.1 and RStudio version 2025.09.2+418. |
1 Getting Started: Overview and Supporting Materials
I – Analyzing and comparing game splits
2 Beyond individual skills
3 Drilling down on clutch splits: measuring performance
when it matters most
4 The race to the finish: exploring the relationship between season
segments and final rankings
II – Decoding motion
5 Understanding players’ spatial dynamics
6 Athletic motion kinematics analysis
7 Tracking and analyzing ball trajectories
III – Spatial performance analysis
8 Basketball performance maps based on court segmentation
9 Scoring probability maps via machine learning algorithms
Athens, Greece (5 May, 2026 4:30 p.m. – Athens University of Economics and Business)
Event scheduled at the AUEB Sport Analytics Workshop, organised by Ioannis Ntzoufras and Dimitris Karlis
Madrid, Spain (8 September, 2026 5:00 p.m. – Salón de Actos, Quintana Aulario – Laboratorio de Ciencia de Datos)
organised by Isaac Martín de Diego and Emilio López Cano (Rey Juan Carlos University)
Barcelona, Spain (9 September, 2026 5:00 p.m. – Sala Assumpció, Gran Via de les Corts Catalanes, 585 – Universitat de Barcelona & Federació Catalana de Basquetbol)
Organised by Daniel Fernández Martínez, Jordi Cortés and Martí Casals (Universitat Politècnica de Catalunya)
Valencia, Spain (24 September, 2026 1:00 p.m. – Universitat de València)
Organised by Gabriel Calvo Bayarri (Universitat de València)
