An Analysis of NBA Spatio-Temporal Data
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2017
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This project examines the utility of spatio-temporal tracking data from professional basketball games by fitting models predicting whether a player will make a shot. The first part of the project involved the exploration of the data, evaluated its issues, and generated features to use as co-variates in the models. The second part fit various classification models and evaluated their predictive performance. The paper concludes with a discussion of methods to improve the models and future work.
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Robertson, Megan (2017). An Analysis of NBA Spatio-Temporal Data. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/15261.
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