{"id":"W4403523974","doi":"10.2139/ssrn.4992342","title":"Predicting the Outcome of a Soccer Match Using Machine Learning Models","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Langara College","funders":"","keywords":"Outcome (game theory); Artificial intelligence; Computer science; Machine learning; Psychology; Mathematics; Mathematical economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001584506,0.0007593998,0.001025179,0.00142693,0.0003767379,0.001638575,0.0009258303,0.001627077,0.00506319],"category_scores_gemma":[0.006891191,0.0003807405,0.0006027725,0.001080792,0.0004361849,0.0009520148,0.0007467213,0.001606668,0.001486553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006062805,"about_ca_system_score_gemma":0.000689811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008439519,"about_ca_topic_score_gemma":0.008859602,"domain_scores_codex":[0.999553,0.0001074946,0.00002916008,0.0001253908,0.00006308226,0.0001218173],"domain_scores_gemma":[0.9965424,0.002177385,0.0004933077,0.0001218138,0.0002734514,0.0003915877],"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":[0.001930722,0.001718078,0.3718669,0.000111008,0.0003043566,0.0003144243,0.00007123504,0.5568841,0.00151375,0.00269829,0.004968248,0.05761892],"study_design_scores_gemma":[0.00002494967,0.0001384933,0.02294207,0.00001186083,0.00002280556,0.00002113976,0.00004138203,0.9733247,0.0003315553,0.002959737,0.0001701403,0.00001115468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668022,0.0003200645,0.02782793,0.001056229,0.000132526,0.00005389342,0.001430127,0.0001613518,0.002215679],"genre_scores_gemma":[0.9945545,0.000129847,0.001903562,0.00004669453,0.00007269323,0.00002219176,0.001571894,0.00001097845,0.00168762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008439519,"threshold_uncertainty_score":0.01693803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06163686192083424,"score_gpt":0.2612038954079925,"score_spread":0.1995670334871583,"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."}}