{"id":"https://openalex.org/W7168265633","doi":"https://doi.org/10.48550/arxiv.2607.11548","title":"Training-Free Off-Screen Player Imputation for Broadcast-Based Spatial Football Analytics","display_name":"Training-Free Off-Screen Player Imputation for Broadcast-Based Spatial Football Analytics","publication_year":2026,"publication_date":"2026-07-13","ids":{"openalex":"https://openalex.org/W7168265633","doi":"https://doi.org/10.48550/arxiv.2607.11548"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.11548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11548","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,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.11548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140592178","display_name":"Seongjin Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Choi, Seongjin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5140592178"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.6536999940872192,"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":0.6536999940872192,"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/T10813","display_name":"Sport Psychology and Performance","score":0.07289999723434448,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12677","display_name":"Sports Dynamics and Biomechanics","score":0.05909999832510948,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.6326000094413757},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.6247000098228455},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.516700029373169},{"id":"https://openalex.org/keywords/geolocation","display_name":"Geolocation","score":0.4339999854564667},{"id":"https://openalex.org/keywords/football","display_name":"Football","score":0.3517000079154968},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.3506999909877777},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.3140999972820282}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6550999879837036},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.6326000094413757},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.6247000098228455},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.516700029373169},{"id":"https://openalex.org/C22041718","wikidata":"https://www.wikidata.org/wiki/Q638949","display_name":"Geolocation","level":2,"score":0.4339999854564667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3709000051021576},{"id":"https://openalex.org/C2778444522","wikidata":"https://www.wikidata.org/wiki/Q1081491","display_name":"Football","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.31299999356269836},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3012000024318695},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2590000033378601},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.11548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11548","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,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.11548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11548","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,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8006666302680969}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spatial":[0],"football":[1],"metrics":[2],"such":[3],"as":[4],"pitch":[5],"control":[6],"assume":[7],"access":[8],"to":[9,54,92,168,181],"the":[10,17,26,41,73,106,124,143,153,171,193,196,248],"positions":[11],"of":[12,22,34,102,114,170,195,208,213],"all":[13,185],"22":[14],"players,":[15],"yet":[16],"most":[18],"widely":[19],"available":[20],"source":[21],"positional":[23],"data":[24,58],"--":[25,30,72,87,192,201],"broadcast":[27,51,245],"main":[28],"camera":[29],"shows":[31],"only":[32,121],"10-16":[33],"them":[35],"at":[36,174],"any":[37],"moment.":[38],"We":[39,109],"quantify":[40],"resulting":[42],"distortion":[43],"with":[44],"an":[45],"open,":[46],"reproducible":[47],"benchmark:":[48],"a":[49,78,97,112,223,229],"simulated":[50],"viewport":[52,176],"applied":[53],"open":[55],"full-pitch":[56],"tracking":[57],"(Metrica":[59],"Sports;":[60],"three":[61,107,186],"matches,":[62],"one":[63],"held":[64],"out":[65],"from":[66,123,178],"method":[67],"development).":[68],"Ignoring":[69],"off-screen":[70],"players":[71],"visible-only":[74],"baseline":[75],"implied":[76],"whenever":[77],"video-based":[79],"game-state-reconstruction":[80],"(GSR)":[81],"pipeline":[82],"adds":[83],"no":[84],"imputation":[85,117,227],"layer":[86],"inflates":[88],"hidden-zone":[89,159],"pitch-control":[90],"error":[91,101,160,167],"25.1-26.9":[93],"percentage":[94],"points":[95,104,239],"and":[96,164,237],"mean":[98],"absolute":[99],"control-share":[100,166],"11.1-13.4":[103],"across":[105],"matches.":[108,187],"then":[110],"evaluate":[111],"ladder":[113],"training-free,":[115],"online":[116],"baselines":[118],"that":[119,218],"use":[120],"observations":[122,215],"match":[125],"being":[126],"analysed.":[127],"The":[128],"best":[129],"overall":[130],"on":[131,240],"these":[132],"decision-relevant":[133],"metrics,":[134],"role-anchored":[135],"centroid":[136,145],"voting":[137],"(each":[138],"visible":[139],"player":[140],"votes":[141],"for":[142],"full-team":[144],"by":[146,235],"subtracting":[147],"its":[148],"running":[149],"role":[150],"offset,":[151],"attenuating":[152],"viewport-induced":[154],"subset":[155],"bias),":[156],"roughly":[157],"halves":[158],"(to":[161],"12.2-13.8":[162],"points)":[163],"cuts":[165],"28-48%":[169],"ignore":[172],"policy":[173],"every":[175],"width":[177],"36":[179],"m":[180,183],"60":[182],"in":[184,251],"For":[188],"occlusions":[189],"&lt;=9.6":[190],"s":[191],"regime":[194],"closest":[197],"learned":[198],"prior":[199],"work":[200],"it":[202],"reaches":[203],"binwise":[204],"median":[205],"position":[206],"errors":[207],"3.3-8.9":[209],"m;":[210],"but":[211],"50-57%":[212],"hidden-player":[214],"lie":[216],"beyond":[217],"regime.":[219],"Integrated":[220],"end-to-end":[221],"into":[222],"broadcast-video":[224],"GSR":[225],"pipeline,":[226],"moves":[228],"downstream":[230],"possession-quality":[231],"score":[232],"(Space-Creation":[233],"Index)":[234],"15.6":[236],"17.2":[238],"two":[241],"real":[242],"World":[243],"Cup":[244],"windows,":[246],"flipping":[247],"verdict":[249],"class":[250],"one.":[252]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-15T00:00:00"}
