A scalable framework for NBA player and team comparisons using player tracking data

@article{Bruce2016ASF,
  title={A scalable framework for NBA player and team comparisons using player tracking data},
  author={Scott Bruce},
  journal={Journal of Systems Architecture},
  year={2016},
  volume={2},
  pages={107-119}
}
  • Scott Bruce
  • Published 2016
  • Computer Science, Mathematics
  • Journal of Systems Architecture
The release of NBA player tracking data greatly enhances the granularity and dimensionality of basketball statistics used to evaluate and compare player performance. However, the high dimensionality of this new data source can be troublesome as it demands more computational resources and reduces the ability to easily interpret findings. Therefore, we must find a way to reduce the dimensionality of the data while retaining the ability to differentiate and compare player performance. In this… Expand
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