{"id":"https://openalex.org/W2809797215","doi":"https://doi.org/10.1007/s10994-018-5741-1","title":"Modeling outcomes of soccer matches","display_name":"Modeling outcomes of soccer matches","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2809797215","doi":"https://doi.org/10.1007/s10994-018-5741-1","mag":"2809797215"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-018-5741-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-018-5741-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-018-5741-1.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-018-5741-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011713793","display_name":"Alkeos Tsokos","orcid":"https://orcid.org/0000-0002-6628-0506"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Alkeos Tsokos","raw_affiliation_strings":["University College London, London, UK","Univ College London, London, UK"],"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"Univ College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037695885","display_name":"Santhosh Narayanan","orcid":"https://orcid.org/0000-0003-2175-5499"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Santhosh Narayanan","raw_affiliation_strings":["University of Warwick, Coventry, UK"],"affiliations":[{"raw_affiliation_string":"University of Warwick, Coventry, UK","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010748074","display_name":"Ioannis Kosmidis","orcid":"https://orcid.org/0000-0003-1556-0302"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]},{"id":"https://openalex.org/I4210128584","display_name":"The Alan Turing Institute","ror":"https://ror.org/035dkdb55","country_code":"GB","type":"facility","lineage":["https://openalex.org/I4210128584"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ioannis Kosmidis","raw_affiliation_strings":["The Alan Turing Institute, London, UK","University of Warwick, Coventry, UK"],"affiliations":[{"raw_affiliation_string":"The Alan Turing Institute, London, UK","institution_ids":["https://openalex.org/I4210128584"]},{"raw_affiliation_string":"University of Warwick, Coventry, UK","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023729638","display_name":"Gianluca Baio","orcid":"https://orcid.org/0000-0003-4314-2570"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gianluca Baio","raw_affiliation_strings":["University College London, London, UK","Univ College London, London, UK"],"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"Univ College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039600886","display_name":"Mihai Cucuringu","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210128584","display_name":"The Alan Turing Institute","ror":"https://ror.org/035dkdb55","country_code":"GB","type":"facility","lineage":["https://openalex.org/I4210128584"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mihai Cucuringu","raw_affiliation_strings":["The Alan Turing Institute, London, UK","University of Oxford, Oxford, UK"],"affiliations":[{"raw_affiliation_string":"The Alan Turing Institute, London, UK","institution_ids":["https://openalex.org/I4210128584"]},{"raw_affiliation_string":"University of Oxford, Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047343749","display_name":"Gavin A. Whitaker","orcid":null},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gavin Whitaker","raw_affiliation_strings":["University College London, London, UK","Univ College London, London, UK"],"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"Univ College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076492850","display_name":"Franz J. Kir\u00e1ly","orcid":"https://orcid.org/0000-0002-9254-793X"},"institutions":[{"id":"https://openalex.org/I4210128584","display_name":"The Alan Turing Institute","ror":"https://ror.org/035dkdb55","country_code":"GB","type":"facility","lineage":["https://openalex.org/I4210128584"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Franz Kir\u00e1ly","raw_affiliation_strings":["The Alan Turing Institute, London, UK","University College London, London, UK"],"affiliations":[{"raw_affiliation_string":"The Alan Turing Institute, London, UK","institution_ids":["https://openalex.org/I4210128584"]},{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5011713793"],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.2449,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.87447781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"108","issue":"1","first_page":"77","last_page":"95"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9467999935150146,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.916700005531311,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/poisson-distribution","display_name":"Poisson distribution","score":0.7778794765472412},{"id":"https://openalex.org/keywords/laplaces-method","display_name":"Laplace's method","score":0.6466435194015503},{"id":"https://openalex.org/keywords/generalized-linear-model","display_name":"Generalized linear model","score":0.607579231262207},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5934249758720398},{"id":"https://openalex.org/keywords/poisson-regression","display_name":"Poisson regression","score":0.5055222511291504},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4939122796058655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.491479754447937},{"id":"https://openalex.org/keywords/multilevel-model","display_name":"Multilevel model","score":0.4903724193572998},{"id":"https://openalex.org/keywords/log-linear-model","display_name":"Log-linear model","score":0.4801018536090851},{"id":"https://openalex.org/keywords/laplace-transform","display_name":"Laplace transform","score":0.4674471318721771},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.4664914608001709},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.4650854468345642},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4503617584705353},{"id":"https://openalex.org/keywords/hierarchical-generalized-linear-model","display_name":"Hierarchical generalized linear model","score":0.4393775761127472},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4364076256752014},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.42118769884109497},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38835203647613525},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3122379183769226},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21441596746444702}],"concepts":[{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.7778794765472412},{"id":"https://openalex.org/C22243797","wikidata":"https://www.wikidata.org/wiki/Q2058297","display_name":"Laplace's method","level":3,"score":0.6466435194015503},{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.607579231262207},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5934249758720398},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.5055222511291504},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4939122796058655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.491479754447937},{"id":"https://openalex.org/C53059260","wikidata":"https://www.wikidata.org/wiki/Q374758","display_name":"Multilevel model","level":2,"score":0.4903724193572998},{"id":"https://openalex.org/C70519679","wikidata":"https://www.wikidata.org/wiki/Q6666755","display_name":"Log-linear model","level":3,"score":0.4801018536090851},{"id":"https://openalex.org/C97937538","wikidata":"https://www.wikidata.org/wiki/Q199691","display_name":"Laplace transform","level":2,"score":0.4674471318721771},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.4664914608001709},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.4650854468345642},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4503617584705353},{"id":"https://openalex.org/C142967376","wikidata":"https://www.wikidata.org/wiki/Q5753099","display_name":"Hierarchical generalized linear model","level":3,"score":0.4393775761127472},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4364076256752014},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.42118769884109497},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38835203647613525},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3122379183769226},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21441596746444702},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1007/s10994-018-5741-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-018-5741-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-018-5741-1.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1807.01623","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1807.01623","pdf_url":"https://arxiv.org/pdf/1807.01623","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},{"id":"mag:2809797215","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1807.01623.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10056079","is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10056079/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   Machine Learning , 108  (1)   pp. 77-95.   (2019)      ","raw_type":"Article"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:31f86927-f29e-404d-a29f-eb52468d49e1","is_oa":true,"landing_page_url":"https://ora.ox.ac.uk/objects/uuid:31f86927-f29e-404d-a29f-eb52468d49e1","pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"},{"id":"doi:10.48550/arxiv.1807.01623","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1807.01623","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s10994-018-5741-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-018-5741-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-018-5741-1.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1223493200","display_name":null,"funder_award_id":"EP/N510129/1.","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1309768829","display_name":null,"funder_award_id":"EP/N510129/1.","funder_id":"https://openalex.org/F4320313467","funder_display_name":"Alan Turing Institute"},{"id":"https://openalex.org/G1633672591","display_name":null,"funder_award_id":"N510129","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3855435662","display_name":null,"funder_award_id":"N510129","funder_id":"https://openalex.org/F4320313467","funder_display_name":"Alan Turing Institute"},{"id":"https://openalex.org/G4072067573","display_name":null,"funder_award_id":"EP/N510129/1","funder_id":"https://openalex.org/F4320313467","funder_display_name":"Alan Turing Institute"},{"id":"https://openalex.org/G444630160","display_name":null,"funder_award_id":"EP/N510129/","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4500485203","display_name":"The Alan Turing Institute","funder_award_id":"EP/N510129/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G6290867921","display_name":null,"funder_award_id":"EPSRC grant EP/N510129/1","funder_id":"https://openalex.org/F4320313467","funder_display_name":"Alan Turing Institute"}],"funders":[{"id":"https://openalex.org/F4320313467","display_name":"Alan Turing Institute","ror":"https://ror.org/035dkdb55"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2809797215.pdf","grobid_xml":"https://content.openalex.org/works/W2809797215.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W606561187","https://openalex.org/W1588819017","https://openalex.org/W1975926620","https://openalex.org/W1986797382","https://openalex.org/W1987164822","https://openalex.org/W1990381576","https://openalex.org/W2000359198","https://openalex.org/W2006935644","https://openalex.org/W2022838594","https://openalex.org/W2025720061","https://openalex.org/W2098649057","https://openalex.org/W2103562949","https://openalex.org/W2107328434","https://openalex.org/W2109802089","https://openalex.org/W2121088269","https://openalex.org/W2124181495","https://openalex.org/W2136744117","https://openalex.org/W2140308441","https://openalex.org/W2143075842","https://openalex.org/W2143703915","https://openalex.org/W2144898279","https://openalex.org/W2172229041","https://openalex.org/W2963929357","https://openalex.org/W4298870098","https://openalex.org/W4298876635","https://openalex.org/W7001961671","https://openalex.org/W7045577039"],"related_works":["https://openalex.org/W2964225582","https://openalex.org/W2121088269","https://openalex.org/W2310103076","https://openalex.org/W1995644805","https://openalex.org/W2765209148","https://openalex.org/W1914577290","https://openalex.org/W3035254432","https://openalex.org/W3164899769","https://openalex.org/W2890809978","https://openalex.org/W2588943917","https://openalex.org/W3033042206","https://openalex.org/W3105153193","https://openalex.org/W2766115568","https://openalex.org/W3210111469","https://openalex.org/W2099303649","https://openalex.org/W3046239586","https://openalex.org/W3049770224","https://openalex.org/W3098804274","https://openalex.org/W2771579906","https://openalex.org/W1759606585"],"abstract_inverted_index":{"We":[0],"compare":[1],"various":[2,74,105],"extensions":[3,35,107],"of":[4,16,23,32,47,53,56,72,94,101,111,125],"the":[5,21,33,40,50,54,57,73,95,104,109,115],"Bradley\u2013Terry":[6,34,106],"model":[7,13,61,119],"and":[8,108],"a":[9,80],"hierarchical":[10,58,116],"Poisson":[11,59,117],"log-linear":[12,60,118],"in":[14,19,123],"terms":[15,124],"their":[17],"performance":[18,71],"predicting":[20],"outcome":[22],"soccer":[24],"matches":[25],"(win,":[26],"draw,":[27],"or":[28,42],"loss).":[29],"The":[30,69,98],"parameters":[31,55],"are":[36,62],"estimated":[37],"by":[38],"maximizing":[39],"log-likelihood,":[41],"an":[43],"appropriately":[44],"penalized":[45],"version":[46],"it,":[48],"while":[49],"posterior":[51],"densities":[52],"approximated":[63],"using":[64,79,114],"integrated":[65],"nested":[66],"Laplace":[67],"approximations.":[68],"prediction":[70],"modeling":[75,100,110],"approaches":[76],"is":[77,88],"assessed":[78],"novel,":[81],"context-specific":[82],"framework":[83],"for":[84],"temporal":[85],"validation":[86],"that":[87],"found":[89],"to":[90],"deliver":[91],"accurate":[92],"estimates":[93],"test":[96],"error.":[97],"direct":[99],"outcomes":[102],"via":[103],"match":[112],"scores":[113],"demonstrate":[120],"similar":[121],"behavior":[122],"predictive":[126],"performance.":[127]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
