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Short Course On

Basketball Data Science​

 

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Location: AUEB Postgraduate Building, 

47A Evelpidon & 33, Lefkados Street

• 20/5/2024 14.00 Room 601 (6th floor) 

• 21/5/2024 14.00 Room 701 (7th floor) 

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TODAY 20/5 you can register at the desk for the

short course on Basketball Data Science

at the AUEB Postgraduate Building,

47A Evelpidon & 33, Lefkados Street (6th floor) 

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20-21 May 2024

Course Lecturers

• Marica Manisera (University of Brescia)

• Paola Zuccolotto (University of Brescia)

• Christos Marmarinos (Ph.D., International Scout of Sacramento Kings)​

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Location: Athens University of Economics and Building,

Postgraduate Building, 47A Evelpidon & 33, Lefkados Street, Athina 113 62 

Total Length of the course: 8 hours in two days (4 hours per day)

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Course Lecturers 

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Christos Marmarinos (AUEB Sports Analytics, Sacramento Kings) ()

• Basketball performance indexes and metrics for player evaluation. 

• Epilogue: Closing comment on the course content and material

       and their practical application (from the manager's perspective)

• During the course, Dr Marmarinos will give the perspective from

        the manager's perspective 

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Marica Manisera and Paola Zuccolotto (University of Brescia)

• Data science in basketball

• Basketball data

• Introduction to the R package BasketballAnalyzeR

• Discovering Patterns in data

• Finding groups in data

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Temporary Program

• DAY 1 (20 May 2024)​: 14.00-18.00 (Room 601, 6th floor) 

  • 1st hour: Introduction to Basketball performance indices and metrics ​(by C. Marmarinos)

  • 1-3 hours: Basketball Data Science Part A incl. a lab session in R (by P. Zuccolotto and M. Manisera)

• DAY 2 (21 May 2024)​: 14.00-18.00 (Room 701, 7th floor) 

  • 1-3 hours: Basketball Data Science Part A incl. a lab session in R (by P. Zuccolotto and M. Manisera)

  • 4th hour: Concluding remarks about the course and the practical use of the course content from the manager's perspective. 

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Bibliography

• Oliver D. (2003). Basketball on paper:  Rules and Tools for Performance. Potomac Books; 1st edition 

• Zuccolotto P. and Manisera M. (2020). Basketball Data Science with applications in R. Chapman and Hall. 

• 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

• Marco Sandri, The R package BasketballAnalyzeR, in: Zuccolotto P. and Manisera M., Basketball Data Science, 2020,  Chapter 6.

• Paola Zuccolotto, Marica Manisera, Marco Sandri (2021), Alley‐oop! Basketball analytics in R, Significance, 26-31 https://doi.org/10.1111/1740-9713.01507

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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

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All course participants will receive a certificate of attendance if they attend in both four-hour sessions. 

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The live participation will be limited to 80 participants. 

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Contact

groupsportsanalytics@gmail.com