{"id":"W4401797669","doi":"10.1016/j.serev.2024.100039","title":"Professionals do play Minimax: Revisiting the Nash equilibrium in Major League Baseball","year":2024,"lang":"en","type":"article","venue":"Sports Economics Review","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; National Bank of Canada","funders":"","keywords":"League; Minimax; Nash equilibrium; Mathematical economics; Best response; Economics; Computer science; Physics","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003247456,0.000300071,0.000880811,0.0002336581,0.00008878371,0.000217802,0.0004416742,0.0001118164,0.005428147],"category_scores_gemma":[0.00006477464,0.0002514525,0.000329509,0.0003904998,0.0000627709,0.0004214549,0.0001438544,0.000396043,0.0008234383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001624497,"about_ca_system_score_gemma":0.0001154402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008408813,"about_ca_topic_score_gemma":0.00002982133,"domain_scores_codex":[0.9969487,0.00001635202,0.001775878,0.0007347721,0.00005023056,0.0004741065],"domain_scores_gemma":[0.9985733,0.00009913245,0.0005102233,0.0006875571,0.00002498442,0.0001048156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002320806,0.0001270073,0.1060603,0.01088835,0.0002431754,0.0002678578,0.0007069958,0.0007655706,0.000003703723,0.7525222,0.0519533,0.07643826],"study_design_scores_gemma":[0.0001514448,0.00001225481,0.008082655,0.004996458,0.0000271434,0.0000344482,0.00003636732,0.006630751,0.000004958232,0.004194588,0.9753881,0.0004407955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1864072,0.7173873,0.0000375447,0.01367006,0.002013124,0.001221629,0.0002419252,0.00008194354,0.07893927],"genre_scores_gemma":[0.7370544,0.2485192,0.0001449552,0.004363556,0.000896656,0.0001290062,0.0001020628,0.00009368115,0.008696465],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9234349,"threshold_uncertainty_score":0.9999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02960258246208538,"score_gpt":0.2675315699810368,"score_spread":0.2379289875189514,"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."}}