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Jupyter Notebook Python
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.ipynb_checkpoints gathering data Oct 3, 2019
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data gathering data Oct 3, 2019
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1_Introduction_to_space_occupation.ipynb notebook 3 Sep 30, 2019
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Today, technology is increasingly used in sport. Indeed, the players' statistics are more and more accurate and more and more numerous. Clubs employ people to acquire data and use it to improve performance. It is in this context that the MecaSportCo Research Application Project, conducted at the Ecole Centrale de Lyon by Gabin Rolland and Nathan Rivière, under the supervision of Wouter Bos and Romain Vuillemot.

The aim of this study is to quantify how "free" a basketball player is and how this influences his 3-points shot performance.


The dataset we use is derived from Stats company data and SportsVU technology. These are the 632 men's basketball games in the NBA between the 2013-2014 and 2016-2017 seasons. For each match we have the movement data for the ball and players taken 25 times per second and stored in the form JavaScript Object Notation (JSON). The following figure shows the general structure of the data:

Work performed


References of the project can be found in Bibliography

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