I have already obtained the distribution statistics for all numeric columns in the dataset. Let me present these findings: ```json { "action": "final", "content": "## Distribution Summary for All Numeric Columns\n\nThe dataset contains numeric measures across two tables: **fighters** (fighter career statistics) and **popular_matches** (match-level opponent metrics).\n\n### Fighters Table\n\n**Career Record Statistics:**\n- **Wins**: Range 0–262, mean 19.7, median 9.0, stddev 29.5. The distribution is right-skewed with most fighters having fewer wins (median 9) but some elite fighters reaching 262 wins.\n- **Losses**: Range 0–190, mean 4.5, median 1.0, stddev 10.0. Most fighters have very few losses (median 1), with the distribution heavily concentrated at the lower end.\n- **Draws**: Range 0–60, mean 1.0, median 0.0, stddev 2.9. Draws are rare—half of all fighters have zero draws.\n\n### Popular Matches Table\n\n**Punch Power & Resistance (0–100 scale):**\n- **Opponent 1 Punch Power**: Range 0–89, mean 66.3, median 69.0, stddev 14.9\n- **Opponent 2 Punch Power**: Range 0–89, mean 66.3, median 69.0, stddev 14.9\n- **Opponent 1 Punch Resistance**: Range 0–73.9, mean 55.5, median 58.0, stddev 11.8\n- **Opponent 2 Punch Resistance**: Range 0–73.4, mean 54.9, median 58.2, stddev 13.1\n- **Opponent 1 Ability to Take Punch**: Range 0–86, mean 69.7, median 76.0, stddev 15.3\n- **Opponent 2 Ability to Take Punch**: Range 0–89, mean 69.8, median 73.0, stddev 15.0\n\nBoth opponents show similar distributions across these metrics, with punch power averaging in the mid-60s and ability to take punches in the high 60s–70s.\n\n**Experience Metrics:**\n- **Opponent 1 Rounds Boxed**: Range 0–462, mean 145.3, median 135.0, stddev 94.2\n- **Opponent 2 Rounds Boxed**: Range 0–391, mean 121.2, median 107.0, stddev 83.1\n\nOpponent 1 tends to have slightly more ring experience on average.\n\n**KO Percentages:**\n- **Opponent 1 Round KO %**: Range 0–100%, mean 16.1%, median 12.2%, stddev 14.4%\n- **Opponent 2 Round KO %**: Range 0–100%, mean 24.4%, median 15.6%, stddev 21.2%\n- **Opponent 1 Has Been KO'd %**: Range 0–62.5%, mean 5.0%, median 0.0%, stddev 8.9%\n- **Opponent 2 Has Been KO'd %**: Range 0–25.0%, mean 1.9%, median 0.0%, stddev 5.2%\n\nOpponent 2 has a higher knockout rate (24.4% vs 16.1%), while Opponent 1 has been knocked out more frequently (5.0% vs 1.9%).\n\n**Weight:**\n- **Opponent 1 Avg Weight**: Range 0–432.86 lbs, mean 191.8 lbs, median 178.7 lbs, stddev 75.6 lbs\n- **Opponent 2 Avg Weight**: Range 0–661.5 lbs, mean 191.2 lbs, median 200.9 lbs, stddev 79.0 lbs\n\nBoth opponents average around 191 lbs, though the wide ranges and high standard deviations suggest matches span multiple weight classes.\n\n### Key Observations\n\n1. **Skewed Career Records**: Fighter wins/losses/draws are heavily right-skewed, with medians well below means—most fighters have modest records, while a few have extensive careers.\n2. **Symmetric Match Metrics**: Opponent punch power, resistance, and ability metrics show relatively symmetric distributions (means ≈ medians).\n3. **Experience Asymmetry**: Opponent 1 consistently shows slightly more experience (more rounds boxed, higher \"has been KO'd\" rate), suggesting they may be the more established fighter in these popular matches.\n4. **High Variability**: Large standard deviations across most metrics indicate substantial diversity in fighter profiles and match characteristics." } ```