{"id":"https://openalex.org/W3184870026","doi":"https://doi.org/10.1109/access.2021.3117911","title":"Measurement Space Partitioning for Estimation and Prediction","display_name":"Measurement Space Partitioning for Estimation and Prediction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3184870026","doi":"https://doi.org/10.1109/access.2021.3117911","mag":"3184870026"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3117911","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3117911","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558850.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558850.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020643599","display_name":"Glenn Healey","orcid":"https://orcid.org/0000-0003-2428-0046"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Glenn Healey","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA","[Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA]"],"raw_orcid":"https://orcid.org/0000-0003-2428-0046","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA","institution_ids":[]},{"raw_affiliation_string":"[Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA]","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078515949","display_name":"Shiyuan Zhao","orcid":"https://orcid.org/0000-0003-1114-7297"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiyuan Zhao","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA","[Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA]"],"raw_orcid":"https://orcid.org/0000-0003-1114-7297","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA","institution_ids":[]},{"raw_affiliation_string":"[Department of Electrical Engineering and Computer Science, University of California at Irvine, Irvine, CA, USA]","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204250578"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0661969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"137419","last_page":"137429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12677","display_name":"Sports Dynamics and Biomechanics","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12677","display_name":"Sports Dynamics and Biomechanics","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9962999820709229,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.954800009727478,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ball","display_name":"Ball (mathematics)","score":0.7227919101715088},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.5884037017822266},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5255469083786011},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.43166467547416687},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4251422882080078},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41281378269195557},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3834354281425476},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33480626344680786},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.33063623309135437},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23330166935920715},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23219674825668335},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13311457633972168}],"concepts":[{"id":"https://openalex.org/C122041747","wikidata":"https://www.wikidata.org/wiki/Q838611","display_name":"Ball (mathematics)","level":2,"score":0.7227919101715088},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5884037017822266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5255469083786011},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43166467547416687},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4251422882080078},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41281378269195557},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3834354281425476},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33480626344680786},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33063623309135437},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23330166935920715},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23219674825668335},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13311457633972168}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3117911","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3117911","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558850.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"mag:3184870026","is_oa":false,"landing_page_url":"https://vixra.org/pdf/2107.0131v1.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S2883122597","display_name":"viXra","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"viXra","raw_type":null},{"id":"pmh:oai:doaj.org/article:9ae946973a2f47da8b3e036a5bc8da35","is_oa":true,"landing_page_url":"https://doaj.org/article/9ae946973a2f47da8b3e036a5bc8da35","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 137419-137429 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3117911","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3117911","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558850.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3184870026.pdf","grobid_xml":"https://content.openalex.org/works/W3184870026.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1901616594","https://openalex.org/W1991769471","https://openalex.org/W2149023664","https://openalex.org/W2159306398","https://openalex.org/W2502759836","https://openalex.org/W2765448013","https://openalex.org/W2789931190","https://openalex.org/W2893038382","https://openalex.org/W2962819866","https://openalex.org/W2963944577","https://openalex.org/W2991007140","https://openalex.org/W3089838435","https://openalex.org/W3114747184","https://openalex.org/W4205365020","https://openalex.org/W6620371665","https://openalex.org/W6634927326","https://openalex.org/W6635777585","https://openalex.org/W6703141430","https://openalex.org/W6797530555"],"related_works":["https://openalex.org/W3202796892","https://openalex.org/W2609007592","https://openalex.org/W2616242671","https://openalex.org/W2752569217","https://openalex.org/W2019530605","https://openalex.org/W2783726161","https://openalex.org/W2801921992","https://openalex.org/W3193689914","https://openalex.org/W2599811448","https://openalex.org/W2891191070","https://openalex.org/W2518203214","https://openalex.org/W2256731029","https://openalex.org/W2901214699","https://openalex.org/W154563054","https://openalex.org/W2561310410","https://openalex.org/W3087224734","https://openalex.org/W1707892877","https://openalex.org/W2962697208","https://openalex.org/W2922013626","https://openalex.org/W2031071434"],"abstract_inverted_index":{"An":[0],"important":[1],"and":[2,128,163],"challenging":[3],"problem":[4,18],"in":[5],"the":[6,12,44,98,114,117,125,137,157,171,174],"evaluation":[7],"of":[8,14,34,47,97,106,116,124,132,159,173],"baseball":[9],"players":[10],"is":[11,58,85,101,110],"quantification":[13],"batted-ball":[15,62,93,99],"talent.":[16,94],"This":[17,56,83],"has":[19],"traditionally":[20],"been":[21],"addressed":[22],"using":[23,74,150],"linear":[24],"regression":[25,75],"or":[26],"machine":[27],"learning":[28],"methods.":[29,152],"We":[30,119],"use":[31,129,158],"large":[32],"sets":[33],"trajectory":[35],"measurements":[36],"acquired":[37],"by":[38,73,103],"in-game":[39],"sensors":[40],"to":[41,60,79,87,112,134],"show":[42,135,165],"that":[43,77,109,136,142,166],"predictive":[45],"value":[46],"a":[48,66,88,104,130],"batted":[49,80],"ball":[50,81],"depends":[51],"on":[52],"its":[53],"physical":[54],"properties.":[55,82],"knowledge":[57],"exploited":[59],"estimate":[61],"distributions":[63,72,100],"defined":[64,102],"over":[65],"multidimensional":[67],"measurement":[68,107],"space":[69,108],"from":[70],"observed":[71],"parameters":[76],"adapt":[78],"process":[84,168],"central":[86],"new":[89,126,138,154],"method":[90,139],"for":[91],"estimating":[92],"The":[95,153],"domain":[96],"partition":[105],"selected":[111],"optimize":[113],"accuracy":[115,172],"estimates.":[118],"present":[120],"examples":[121],"illustrating":[122],"facets":[123],"approach":[127],"set":[131],"experiments":[133],"generates":[140],"estimates":[141],"are":[143],"significantly":[144],"more":[145],"accurate":[146],"than":[147],"those":[148],"generated":[149],"current":[151],"methodology":[155],"supports":[156],"fine-grained":[160],"contextual":[161],"adjustments":[162],"we":[164],"this":[167],"further":[169],"improves":[170],"technique.":[175]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}