{"id":"https://openalex.org/W4390900820","doi":"https://doi.org/10.1145/3635638.3635646","title":"Predictive Analysis of NBA Game Outcomes through Machine Learning","display_name":"Predictive Analysis of NBA Game Outcomes through Machine Learning","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4390900820","doi":"https://doi.org/10.1145/3635638.3635646"},"language":"en","primary_location":{"id":"doi:10.1145/3635638.3635646","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3635638.3635646","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3635638.3635646","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Machine Learning and Machine Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3635638.3635646","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006163055","display_name":"J. Wang","orcid":"https://orcid.org/0009-0005-5773-3816"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junwen Wang","raw_affiliation_strings":["Department of Physics, University of California, Santa Barbara, The U.S"],"raw_orcid":"https://orcid.org/0009-0005-5773-3816","affiliations":[{"raw_affiliation_string":"Department of Physics, University of California, Santa Barbara, The U.S","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006163055"],"corresponding_institution_ids":["https://openalex.org/I154570441"],"apc_list":null,"apc_paid":null,"fwci":15.3876,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.99061986,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"46","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9639000296592712,"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/T10942","display_name":"Sports, Gender, and Society","score":0.9154999852180481,"subfield":{"id":"https://openalex.org/subfields/3318","display_name":"Gender Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7684859037399292},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7259570360183716},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6926062107086182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6444877982139587},{"id":"https://openalex.org/keywords/predictive-analytics","display_name":"Predictive analytics","score":0.6382002234458923},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5388761162757874},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5344376564025879},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5005819797515869},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5002238750457764},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.49765828251838684},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.48167622089385986},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.47227346897125244},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43773454427719116}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684859037399292},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7259570360183716},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6926062107086182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6444877982139587},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.6382002234458923},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5388761162757874},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5344376564025879},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5005819797515869},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5002238750457764},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.49765828251838684},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.48167622089385986},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.47227346897125244},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43773454427719116},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3635638.3635646","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3635638.3635646","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3635638.3635646","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Machine Learning and Machine Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3635638.3635646","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3635638.3635646","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3635638.3635646","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Machine Learning and Machine Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390900820.pdf"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1985594121","https://openalex.org/W2046106671","https://openalex.org/W2057997183","https://openalex.org/W2138697424","https://openalex.org/W2582555581","https://openalex.org/W2908448204","https://openalex.org/W2940689695","https://openalex.org/W2980669472","https://openalex.org/W3134998352","https://openalex.org/W3204732847","https://openalex.org/W4206558754"],"related_works":["https://openalex.org/W3189884647","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W2809858895","https://openalex.org/W4313289487","https://openalex.org/W2570647323","https://openalex.org/W2206805568","https://openalex.org/W2076942471"],"abstract_inverted_index":{"This":[0],"study":[1,80,92],"delved":[2],"into":[3,38,155],"the":[4,15,39,63,73,94,104,108,115,130,148,163],"realm":[5],"of":[6,17,65,78,97,110,165],"sports":[7,88,136],"analytics,":[8],"employing":[9],"machine":[10],"learning":[11],"techniques":[12],"to":[13,86],"predict":[14],"outcomes":[16],"NBA":[18],"games":[19],"based":[20],"on":[21],"player":[22],"performance":[23,96],"and":[24,32,55,99,107,126,162],"team":[25],"statistics.":[26],"Through":[27],"meticulous":[28],"data":[29,124],"collection,":[30],"filtering,":[31],"model":[33,127],"comparison,":[34],"we":[35,142],"gained":[36],"insights":[37],"factors":[40],"that":[41],"significantly":[42],"impact":[43],"game":[44,105],"results.":[45],"Logistic":[46],"Regression,":[47],"Support":[48],"Vector":[49],"Machines,":[50],"Deep":[51],"Neural":[52],"Networks":[53],"(DNN)":[54],"Random":[56,100],"Forest":[57,101],"models":[58],"were":[59],"rigorously":[60],"evaluated,":[61],"showcasing":[62],"power":[64],"advanced":[66],"algorithms":[67],"in":[68,102,114,120],"uncovering":[69],"intricate":[70],"patterns":[71,167],"within":[72],"data.":[74],"The":[75,91],"structured":[76],"methodology":[77],"this":[79,121,145],"provides":[81],"a":[82],"versatile":[83],"framework":[84],"applicable":[85],"various":[87],"analytics":[89],"scenarios.":[90],"shows":[93],"better":[95],"DNN":[98],"predicting":[103],"results":[106],"importance":[109],"field":[111],"goal":[112],"percentage":[113],"predicting.":[116],"Limitations":[117],"still":[118],"exist":[119],"work,":[122],"including":[123],"quality":[125],"constraints;":[128],"however,":[129],"findings":[131],"have":[132],"immediate":[133],"implications":[134],"for":[135,150,168],"professionals":[137],"seeking":[138],"actionable":[139],"insights.":[140],"As":[141],"look":[143],"ahead,":[144],"research":[146],"underscores":[147],"potential":[149],"future":[151],"advancements,":[152],"encouraging":[153],"exploration":[154],"more":[156],"sophisticated":[157],"algorithms,":[158],"deeper":[159],"feature":[160],"analysis,":[161],"integration":[164],"temporal":[166],"comprehensive":[169],"predictive":[170],"accuracy.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
