{"id":"W3178479706","doi":"10.1177/15270025211022733","title":"Financial Returns in Major League Soccer","year":2021,"lang":"en","type":"article","venue":"Journal of Sports Economics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"League; Revenue; Quality (philosophy); Demographics; Stadium; Business; Marketing; Revenue sharing; Team sport; Novelty; Economics; Advertising; Finance; Psychology; Athletes","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001617712,0.0003174549,0.000310511,0.001441134,0.0004326773,0.002535513,0.0004723292,0.0007061222,0.005976164],"category_scores_gemma":[0.01419608,0.0001583405,0.0004091743,0.001040309,0.0007342737,0.001203889,0.001198746,0.001517547,0.001239858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001681121,"about_ca_system_score_gemma":0.0009731372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.035387,"about_ca_topic_score_gemma":0.02966693,"domain_scores_codex":[0.9991608,0.000178473,0.00004774442,0.00009608761,0.0002023656,0.0003145226],"domain_scores_gemma":[0.9846745,0.004787998,0.006086273,0.0002908357,0.001380213,0.002780285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003212484,0.0002861073,0.971155,0.00003422091,0.00008431619,0.0003218844,0.0001797307,0.002675132,0.0001376829,0.003711847,0.004794539,0.01629833],"study_design_scores_gemma":[0.0000227883,0.0002193845,0.9881518,0.00003864494,0.00004068405,0.0001667438,0.0011217,0.005143608,0.0002032101,0.002065352,0.002803331,0.00002266184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989125,0.001153849,0.0002550394,0.001740829,0.00002656391,0.00001218992,0.0008140599,0.00002145658,0.006850955],"genre_scores_gemma":[0.997127,0.0002531203,0.00002557666,0.00008833472,0.00003891284,0.000004429196,0.0006682735,0.00000365496,0.00179071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.035387,"threshold_uncertainty_score":0.07036209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975317782556067,"score_gpt":0.2055916900922092,"score_spread":0.1858385122666485,"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."}}