{"id":"https://openalex.org/W2614666418","doi":"https://doi.org/10.1080/01605682.2018.1457485","title":"Comparing probabilistic predictive models applied to football","display_name":"Comparing probabilistic predictive models applied to football","publication_year":2018,"publication_date":"2018-04-25","ids":{"openalex":"https://openalex.org/W2614666418","doi":"https://doi.org/10.1080/01605682.2018.1457485","mag":"2614666418"},"language":"en","primary_location":{"id":"doi:10.1080/01605682.2018.1457485","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01605682.2018.1457485","pdf_url":null,"source":{"id":"https://openalex.org/S169988927","display_name":"Journal of the Operational Research Society","issn_l":"0160-5682","issn":["0160-5682","1476-9360"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319703","host_organization_name":"Palgrave Macmillan","host_organization_lineage":["https://openalex.org/P4310319703","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Palgrave Macmillan","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Operational Research Society","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1705.04356","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Marcio Alves Diniz","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Marcio Alves Diniz","raw_affiliation_strings":["Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rafael Izbicki","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rafael Izbicki","raw_affiliation_strings":["Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Danilo Lopes","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Danilo Lopes","raw_affiliation_strings":["Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"last","author":{"id":null,"display_name":"Luis Ernesto Salasar","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luis Ernesto Salasar","raw_affiliation_strings":["Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Statistics Department, Universidade Federal de Sao Carlos, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I177909021"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177909021"],"apc_list":null,"apc_paid":null,"fwci":1.5108,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87187587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"70","issue":"5","first_page":"770","last_page":"782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9398999810218811,"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":0.9398999810218811,"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":0.006000000052154064,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.00430000014603138,"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/goodness-of-fit","display_name":"Goodness of fit","score":0.7605000138282776},{"id":"https://openalex.org/keywords/championship","display_name":"Championship","score":0.7231000065803528},{"id":"https://openalex.org/keywords/football","display_name":"Football","score":0.6589999794960022},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5676000118255615},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5156999826431274},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.40139999985694885},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.3840999901294708},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.37770000100135803}],"concepts":[{"id":"https://openalex.org/C132480984","wikidata":"https://www.wikidata.org/wiki/Q2034239","display_name":"Goodness of fit","level":2,"score":0.7605000138282776},{"id":"https://openalex.org/C2779501167","wikidata":"https://www.wikidata.org/wiki/Q1079023","display_name":"Championship","level":2,"score":0.7231000065803528},{"id":"https://openalex.org/C2778444522","wikidata":"https://www.wikidata.org/wiki/Q1081491","display_name":"Football","level":2,"score":0.6589999794960022},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5676000118255615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5631999969482422},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5156999826431274},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41449999809265137},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4101000130176544},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3531000018119812},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.3492000102996826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2985000014305115},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.27889999747276306},{"id":"https://openalex.org/C20685875","wikidata":"https://www.wikidata.org/wiki/Q7239678","display_name":"Predictive validity","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/01605682.2018.1457485","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01605682.2018.1457485","pdf_url":null,"source":{"id":"https://openalex.org/S169988927","display_name":"Journal of the Operational Research Society","issn_l":"0160-5682","issn":["0160-5682","1476-9360"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319703","host_organization_name":"Palgrave Macmillan","host_organization_lineage":["https://openalex.org/P4310319703","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Palgrave Macmillan","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Operational Research Society","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1705.04356","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.04356","pdf_url":"https://arxiv.org/pdf/1705.04356","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,"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:RePEc:taf:tjorxx:v:70:y:2019:i:5:p:770-782","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/01605682.2018.1457485","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1705.04356","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.04356","pdf_url":"https://arxiv.org/pdf/1705.04356","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,"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1555310745","https://openalex.org/W1659054115","https://openalex.org/W1975926620","https://openalex.org/W1979541963","https://openalex.org/W1980493388","https://openalex.org/W1982045290","https://openalex.org/W1982166547","https://openalex.org/W1985830514","https://openalex.org/W1989661440","https://openalex.org/W1992532557","https://openalex.org/W2000066155","https://openalex.org/W2008974608","https://openalex.org/W2022838594","https://openalex.org/W2023943903","https://openalex.org/W2027254536","https://openalex.org/W2035378550","https://openalex.org/W2043462999","https://openalex.org/W2044878422","https://openalex.org/W2063440457","https://openalex.org/W2070039057","https://openalex.org/W2072183731","https://openalex.org/W2073241381","https://openalex.org/W2087204158","https://openalex.org/W2113003261","https://openalex.org/W2129099765","https://openalex.org/W2133157284","https://openalex.org/W2136744117","https://openalex.org/W2167732681","https://openalex.org/W2172229041","https://openalex.org/W2256334485","https://openalex.org/W2323273068","https://openalex.org/W2480455979","https://openalex.org/W2763110165","https://openalex.org/W4232632925","https://openalex.org/W4298876635"],"related_works":[],"abstract_inverted_index":{"We":[0,61],"propose":[1],"two":[2],"Bayesian":[3],"multinomial-Dirichlet":[4,73],"models":[5,21,28,74],"to":[6,18],"predict":[7],"the":[8,27,30,37,41,46,53],"final":[9],"outcome":[10],"of":[11,33,36,40,55,66,92],"football":[12,43],"(soccer)":[13],"matches":[14,35],"and":[15,45,57,88],"compare":[16],"them":[17],"three":[19,49],"well-known":[20],"regarding":[22],"their":[23],"predictive":[24],"power.":[25],"All":[26],"predicted":[29],"full-time":[31],"results":[32,70],"1710":[34],"first":[38],"division":[39],"Brazilian":[42],"championship":[44],"comparison":[47],"used":[48],"proper":[50],"scoring":[51],"rules,":[52],"proportion":[54],"errors":[56],"a":[58,64],"calibration":[59],"assessment.":[60],"also":[62,85],"provide":[63],"goodness":[65,91],"fit":[67],"measure.":[68],"Our":[69],"show":[71],"that":[72],"are":[75,84],"not":[76],"only":[77],"competitive":[78],"with":[79],"standard":[80],"approaches,":[81],"but":[82],"they":[83],"well":[86],"calibrated":[87],"present":[89],"reasonable":[90],"fit.":[93]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2017-05-26T00:00:00"}