Classifying NBA Offensive Plays Using Neural Networks

By Kuan-Chieh Wang, Richard S. Zemel. 2016

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, methodology): “In another work by Wang and Zemel [155], an RNN has been used for classification of offensive basketball plays in NBA games.”
Identifying Basketball Plays from Sensor Data; Towards a Low-Cost Automatic Extraction of Advanced Statistics (2017, methodology): “In the paper written by Wang and Zemel [16], an algorithm to classify a closed-set of plays using Recurrent Neural Networks (RNN) is presented, with the purpose of generating detailed reports with a high-level basketball understanding.”
Applying Deep Learning to Basketball Trajectories (2016, methodology): “An attempt by Wang to use RNNs on tracking data was unsuccessful [12].”