I have already obtained the column metadata for the `cleandata_v2` table, which appears to be the primary table in this boxing dataset. Let me provide a comprehensive answer based on the evidence. ```json { "action": "final", "content": "# Dataset Columns: Boxing Match Records\n\nThis dataset contains **31 columns** tracking boxing match details between two fighters (designated as \"f_boxer\" for the first/featured boxer and \"s_boxer\" for the second/opponent boxer).\n\n## Column Breakdown by Category\n\n### Identity & Metadata (4 columns)\n- **_unnamed_0** (BIGINT): Row index, values 1-127\n- **X** (BIGINT): Record identifier, values 1-127\n- **_ingestion_timestamp** (TIMESTAMP): When the data was loaded into the system\n- **_batch_id** (VARCHAR): Batch processing identifier\n- **_source_file** (VARCHAR): Original CSV file path\n\n### Fighter Information - First Boxer (13 columns)\n- **f_boxer** (VARCHAR): Name of the first/featured boxer (~12 distinct fighters)\n- **f_boxer_result** (VARCHAR): Match outcome for first boxer (\"won\" or \"lost\")\n- **f_boxer_stance** (VARCHAR): Fighting stance (orthodox, southpaw, or height measurement)\n- **f_boxer_age** (BIGINT): Age at time of fight (20-39 years, 12 nulls)\n- **f_boxer_height** (BIGINT): Height in centimeters (187-206 cm)\n- **f_boxer_reach** (DOUBLE): Arm reach in centimeters (188.0-216.0 cm)\n- **f_boxer_won** (BIGINT): Career wins before this fight (0-64)\n- **f_boxer_lost** (BIGINT): Career losses before this fight (0-5)\n- **f_boxer_drawn** (BIGINT): Career draws before this fight (0-1)\n- **f_boxer_KOs** (BIGINT): Career knockouts before this fight (0-53, 12 nulls)\n- **f_boxer_ranking** (BIGINT): Fighter's ranking (1-6, where 1 is highest)\n\n### Fighter Information - Second Boxer (13 columns)\n- **s_boxer** (VARCHAR): Name of the second/opponent boxer (~93 distinct fighters)\n- **s_boxer_result** (VARCHAR): Match outcome for second boxer (\"won\" or \"lost\")\n- **s_boxer_stance** (VARCHAR): Fighting stance (10 distinct values including height measurements)\n- **s_boxer_age** (BIGINT): Age at time of fight (21-43 years, 12 nulls)\n- **s_boxer_height** (BIGINT): Height in centimeters (178-207 cm, 6 nulls)\n- **s_boxer_reach** (DOUBLE): Arm reach in centimeters (183.0-216.0 cm)\n- **s_boxer_won** (BIGINT): Career wins before this fight (2-85)\n- **s_boxer_lost** (BIGINT): Career losses before this fight (0-33)\n- **s_boxer_drawn** (BIGINT): Career draws before this fight (0-5)\n- **s_boxer_KOs** (BIGINT): Career knockouts before this fight (0-42, 12 nulls)\n- **s_boxer_ranking** (BIGINT): Fighter's ranking (1-24)\n\n### Match Details (3 columns)\n- **rounds** (VARCHAR): Detailed match information including fighter names and round details (~68 distinct values)\n- **matchRounds** (BIGINT): Number of rounds fought (0-9, 11 nulls)\n- **fightEnd** (VARCHAR): How the fight ended (5 types: DQ, KO, TKO, UD/decision, Unknown)\n\n## Data Quality Notes\n\n- **127 total records** across most tables\n- **Missing values**: Age and KO statistics have 12 nulls each; matchRounds has 11 nulls; s_boxer_height has 6 nulls\n- **Stance column anomaly**: Both f_boxer_stance and s_boxer_stance contain height measurements mixed with actual stance values (orthodox/southpaw), suggesting data quality issues\n- The dataset tracks career statistics (wins/losses/KOs) at the time of each match, allowing analysis of how fighter experience correlates with outcomes" } ```