{"id":"W4405650378","doi":"10.1016/j.dajour.2024.100537","title":"A predictive analytics framework for forecasting soccer match outcomes using machine learning models","year":2024,"lang":"en","type":"article","venue":"Decision Analytics Journal","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of the Fraser Valley; Langara College","funders":"","keywords":"Predictive analytics; Analytics; Computer science; Machine learning; Artificial intelligence; Predictive modelling; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002026457,0.0003392694,0.0007811637,0.000992649,0.0005601409,0.001020086,0.000376495,0.0002387174,0.0005996977],"category_scores_gemma":[0.0006323522,0.0003093492,0.0006892933,0.0007372866,0.00005716033,0.0006261818,0.0001098695,0.001032899,0.00006089676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003160794,"about_ca_system_score_gemma":0.00009902174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004028359,"about_ca_topic_score_gemma":0.00001286079,"domain_scores_codex":[0.9971454,0.00001277275,0.001491637,0.0005325566,0.0002269585,0.0005906569],"domain_scores_gemma":[0.9979536,0.0006058055,0.0006284141,0.0003129893,0.0002310075,0.0002681833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007961044,0.00007585678,0.07129678,0.00006451293,0.0007018833,0.00009168745,0.000605363,0.7641547,0.000001720005,0.1571861,0.0008350206,0.00490683],"study_design_scores_gemma":[0.0002580473,0.00007442274,0.0003976194,0.0001763606,0.00008710219,0.00008609096,0.00008998589,0.6701255,0.000002541117,0.3198566,0.008596667,0.0002490885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0521123,0.003600512,0.9412925,0.000383327,0.001320765,0.0001659037,0.0001961832,0.00005406351,0.0008744143],"genre_scores_gemma":[0.9310603,0.001258727,0.06547237,0.0002672266,0.0006178201,0.000004780811,0.00001906572,0.00009975164,0.001199918],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.878948,"threshold_uncertainty_score":0.9999359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1793987444576868,"score_gpt":0.321133738719872,"score_spread":0.1417349942621852,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}