Short Course On
Basketball Data Science
L
Location: Virtual
7-9 May 2025
Course Lecturers
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Marica Manisera (University of Brescia)
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Paola Zuccolotto (University of Brescia)
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Christos Marmarinos
Course Lecturers
Christos Marmarinos (AUEB Sports Analytics, Sacramento Kings) ()
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Basketball performance indexes and metrics for player evaluation.
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Epilogue: Closing comment on the course content and material
and their practical application (from the manager's perspective)
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During the course, Dr Marmarinos will give the perspective from
the manager's perspective
Marica Manisera and Paola Zuccolotto (University of Brescia)
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Data science in basketball
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Basketball data
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Introduction to the R package BasketballAnalyzeR
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Discovering Patterns in data
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Finding groups in data
Program: TBA
Bibliography
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Oliver D. (2003). Basketball on paper: Rules and Tools for Performance. Potomac Books; 1st edition
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Zuccolotto P. and Manisera M. (2020). Basketball Data Science with applications in R. Chapman and Hall.
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Marco Sandri, Paola Zuccolotto, Marica Manisera (2020), BasketballAnalyzeR: Analysis and Visualization of Basketball Data. R package version 0.5.0. https://CRAN.R-project.org/package=BasketballAnalyzeR
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Marco Sandri, The R package BasketballAnalyzeR, in: Zuccolotto P. and Manisera M., Basketball Data Science, 2020, Chapter 6.
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Paola Zuccolotto, Marica Manisera, Marco Sandri (2021), Alley‐oop! Basketball analytics in R, Significance, 26-31 https://doi.org/10.1111/1740-9713.01507
All participants must bring their own laptops fully charged with R and the R package BasketballAnalyzeR already installed.
How to install it: https://bdsports.unibs.it/basketballanalyzer/
For any problem, please write to basketball.analyzer.help@gmail.com
All course participants will receive a certificate of attendance if they attend in both four-hour sessions.
Contact
