Classifying teams in the NBA with player behavioral data
Name
1126661787-MIT.pdf
Size
4.62 MB
Format
Adobe PDF
Checksum (MD5)
33d86d3ab4f21fbde5bc437d28c4abc9
Author(s)
Poler, Colin(Colin M.)
Advisor(s)
Peko Hosoi.
Alternative Title
Classifying teams in the National Basketball Association with player behavioral data
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
I use SecondSpectrum play-by-play data from the 2016-2017 NBA season to assemble behavioral event data for each player. Behavioral data includes propensity to dribble/pass/shoot, and also the resulting quality of shot when players decide to shoot or make another pass. I apply a k-means clustering algorithm to cluster teams based on their starting lineup behavior data; the clusters show different team makeups within the behavioral data collected. In particular, the clustering identified pass-heavy vs dribble-heavy offenses, and good shot-decision making teams.
Description
Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018
Cataloged from PDF version of thesis.
Includes bibliographical references (page [25]).
Subjects
Mechanical Engineering.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
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