{"id":"https://openalex.org/W2891630447","doi":"https://doi.org/10.48550/arxiv.1401.0942","title":"Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball","display_name":"Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball","publication_year":2014,"publication_date":"2014-01-05","ids":{"openalex":"https://openalex.org/W2891630447","doi":"https://doi.org/10.48550/arxiv.1401.0942","mag":"2891630447"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1401.0942","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1401.0942","pdf_url":"https://arxiv.org/pdf/1401.0942","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1401.0942","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Miller, Andrew","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Miller, Andrew","raw_affiliation_strings":["Harvard University","School of Engineering and Applied Sciences Harvard University Cambridge , MA 02138 , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"School of Engineering and Applied Sciences Harvard University Cambridge , MA 02138 , USA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102840195","display_name":"Luke Bornn","orcid":"https://orcid.org/0000-0003-0297-1479","observed_orcids":["https://orcid.org/0000-0003-0297-1479"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bornn, Luke","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007769527","display_name":"Ryan Prescott Adams","orcid":"https://orcid.org/0000-0002-5704-6654","observed_orcids":["https://orcid.org/0000-0002-5704-6654"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adams, Ryan","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091558863","display_name":"Kirk P. Goldsberry","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goldsberry, Kirk","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":79,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"235","last_page":"243"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10157","display_name":"Sports Performance and Training","score":0.015300000086426735,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/nba","display_name":"NBA","score":0.6909999847412109},{"id":"https://openalex.org/keywords/point-process-intensity","display_name":"point process intensity","score":0.7739999890327454},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"non-negative matrix factorization","score":0.9760000109672546},{"id":"https://openalex.org/keywords/spatial-decomposition","display_name":"spatial decomposition","score":0.42800000309944153},{"id":"https://openalex.org/keywords/shooting-accuracy","display_name":"shooting accuracy","score":0.734000027179718},{"id":"https://openalex.org/keywords/low-rank-representation","display_name":"low-rank representation","score":0.503000020980835}],"concepts":[{"id":"https://openalex.org/C103189561","wikidata":"https://www.wikidata.org/wiki/Q5372","display_name":"Basketball","level":2,"score":0.7613513469696045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7008228302001953},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6150169372558594},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.605840265750885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.601356029510498},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5505577921867371},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5386986136436462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5223023891448975},{"id":"https://openalex.org/C176856949","wikidata":"https://www.wikidata.org/wiki/Q2001676","display_name":"Offensive","level":2,"score":0.5210918188095093},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5079966187477112},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.48209574818611145},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47228819131851196},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.454163134098053},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.43722549080848694},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.43683716654777527},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20782843232154846},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.09363347291946411},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"pmh:oai:arXiv.org:1401.0942","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1401.0942","pdf_url":"https://arxiv.org/pdf/1401.0942","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1006.9093","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1006.9093","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://dash.harvard.edu/bitstream/handle/1/17491849/97209280.pdf?sequence%3D1","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.650.943","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://hips.seas.harvard.edu/files/miller-factorized-icml-2014.pdf","raw_type":"text"},{"id":"pmh:oai:dash.harvard.edu:1/17491849","doi":null,"is_oa":false,"landing_page_url":"http://nrs.harvard.edu/urn-3:HUL.InstRepos:17491849","pdf_url":null,"source":{"id":"https://openalex.org/S4306401540","display_name":"Digital Access to Scholarship at Harvard (DASH) (Harvard University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I136199984","host_organization_name":"Harvard University","host_organization_lineage":["https://openalex.org/I136199984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},{"id":"doi:10.48550/arxiv.1401.0942","doi":"https://doi.org/10.48550/arxiv.1401.0942","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1401.0942","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2891630447","doi":null,"is_oa":false,"landing_page_url":"https://dash.harvard.edu/bitstream/1/17491849/1/97209280.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","jufo-3","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research","raw_type":null},{"id":"mag:2964284633","doi":null,"is_oa":false,"landing_page_url":"http://dash.harvard.edu/bitstream/handle/1/17491849/97209280.pdf?sequence=1","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1401.0942","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1401.0942","pdf_url":"https://arxiv.org/pdf/1401.0942","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2891630447.pdf","grobid_xml":"https://content.openalex.org/works/W2891630447.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1535106372","https://openalex.org/W1555273058","https://openalex.org/W1746819321","https://openalex.org/W1880262756","https://openalex.org/W1902027874","https://openalex.org/W2131351008","https://openalex.org/W2134117233","https://openalex.org/W2135029798","https://openalex.org/W2136787567","https://openalex.org/W2144750001","https://openalex.org/W2149031002","https://openalex.org/W2154047075","https://openalex.org/W2905296953"],"related_works":["https://openalex.org/W2655360469","https://openalex.org/W7159807427","https://openalex.org/W4297818050","https://openalex.org/W7140666019","https://openalex.org/W2773856389","https://openalex.org/W4414566251","https://openalex.org/W7125801481","https://openalex.org/W3035504405","https://openalex.org/W4298859189","https://openalex.org/W4415334641"],"abstract_inverted_index":{"We":[0],"develop":[1],"a":[2,65,70,94],"machine":[3],"learning":[4],"approach":[5],"to":[6,49,113,124],"represent":[7],"and":[8,30,54,120],"analyze":[9],"the":[10,23,79,99,110],"underlying":[11],"spatial":[12,96,106,127],"structure":[13],"that":[14,37,93],"governs":[15],"shot":[16,61],"selection":[17],"among":[18],"professional":[19],"basketball":[20],"players":[21,27,53],"in":[22,32,78],"NBA.":[24,80],"Typically,":[25],"NBA":[26,103,117],"are":[28],"discussed":[29],"compared":[31],"an":[33,86],"heuristic,":[34],"imprecise":[35],"manner":[36],"relies":[38],"on":[39],"unmeasured":[40],"intuitions":[41],"about":[42],"player":[43,57,76,118],"behavior.":[44],"This":[45],"makes":[46],"it":[47],"difficult":[48],"draw":[50],"comparisons":[51],"between":[52],"make":[55],"accurate":[56],"specific":[58],"predictions.":[59],"Modeling":[60],"attempt":[62],"data":[63],"as":[64,130],"point":[66],"process,":[67],"we":[68,91],"create":[69],"low":[71],"dimensional":[72],"representation":[73],"of":[74,102,116],"offensive":[75],"types":[77],"Using":[81],"non-negative":[82],"matrix":[83],"factorization":[84],"(NMF),":[85],"unsupervised":[87],"dimensionality":[88],"reduction":[89],"technique,":[90],"show":[92],"low-rank":[95],"decomposition":[97],"summarizes":[98],"shooting":[100,131],"habits":[101],"players.":[104],"The":[105],"representations":[107],"discovered":[108],"by":[109],"algorithm":[111],"correspond":[112],"intuitive":[114],"descriptions":[115],"types,":[119],"can":[121],"be":[122],"used":[123],"model":[125],"other":[126],"effects,":[128],"such":[129],"accuracy.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":13},{"year":2014,"cited_by_count":4}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2018-09-27T00:00:00"}