2026-09-19T13:46:09Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1228802021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
Peko Hosoi.
Poler, Colin(Colin M.)
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2019-11-12T17:41:12Z
2019-11-12T17:41:12Z
2018
2018
https://hdl.handle.net/1721.1/122880
1126661787
Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018
Cataloged from PDF version of thesis.
Includes bibliographical references (page [25]).
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.
by Colin Poler.
S.B.
S.B. Massachusetts Institute of Technology, Department of Mechanical Engineering
25 unnumbered pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Classifying teams in the NBA with player behavioral data
Classifying teams in the National Basketball Association with player behavioral data
Thesis
application/pdf
2019-11-12T17:41:11Z
Publication
Bachelor
MechE
unknown
unknown
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<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.</Abstract>
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