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# Clustering NBA Players Based on Offensive and Defense Skillset

Preferred citation (DataCite format):

  Raj, Ashwin (2021).
  Clustering NBA Players Based on Offensive and Defense Skillset.
  University of Arizona Research Data Repository.
  Figure. https://doi.org/10.25422/azu.data.14515278


Corresponding Author:
  Ashwin Raj, Mathematics, ashwinr136@email.arizona.edu


License:
  CC BY 4.0


DOI:
  https://doi.org/10.25422/azu.data.14515278



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## Summary

This visualization, titled "Clustering NBA Players Based on Offensive and
Defense Skillset" was submitted by Ashwin Raj to the University of Arizona
Libraries 2021 Data Visualization Challenge. It received the third place win
within the undergraduate classification.

Submitted Abstract:
This project uses 2019 NBA Player data from basketball-reference to cluster
NBA players into roles based on their offensive and defensive skillsets. Using
3-pointers made as the offensive metric and steals as the defensive metric,
and then standardizing these metrics per 36 minutes, players were clustered as
Low-Impact, Bench Defense, Bench Offense, Shooters, Two-Way, and Elite. Teams
can use this data about their players to determine rotations, offensive &
defensive strategy, and even potential trades. The cluster analysis was done
using K-Means with k=6, and the interactive plot was created using GGPlot and
Plotly.



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## Additional Notes

This item is part of the University of Arizona Libraries 2021 Data Visualization Challenge, which is available here:
https://doi.org/10.25422/azu.data.c.5405493