{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/factorized-point-process-intensities-a","title":"Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball","arxiv_id":"1401.0942","date":"2014-01-05","proceeding":null,"authors":["Andrew Miller","Luke Bornn","Ryan Adams","Kirk Goldsberry"],"abstract":"We develop a machine learning approach to represent and analyze the\nunderlying spatial structure that governs shot selection among professional\nbasketball players in the NBA. Typically, NBA players are discussed and\ncompared in an heuristic, imprecise manner that relies on unmeasured intuitions\nabout player behavior. This makes it difficult to draw comparisons between\nplayers and make accurate player specific predictions. Modeling shot attempt\ndata as a point process, we create a low dimensional representation of\noffensive player types in the NBA. Using non-negative matrix factorization\n(NMF), an unsupervised dimensionality reduction technique, we show that a\nlow-rank spatial decomposition summarizes the shooting habits of NBA players.\nThe spatial representations discovered by the algorithm correspond to intuitive\ndescriptions of NBA player types, and can be used to model other spatial\neffects, such as shooting accuracy.","url_abs":"http://arxiv.org/abs/1401.0942v2","url_pdf":"http://arxiv.org/pdf/1401.0942v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"factorized-point-process-intensities-a","repo_url":"https://github.com/ashleyradford/nba_shooting_analysis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"factorized-point-process-intensities-a","repo_url":"https://github.com/ashleyradford/nba_shooting_dashboard","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"dimensionality-reduction","task_name":"Dimensionality Reduction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1401.0942","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}