```json { "action": "final", "content": "## Missing Values Analysis\n\nThe dataset has **missing values in score columns only** — specifically the `HomeScore` and `AwayScore` columns across the various score tables.\n\n### Key Findings\n\n**Highest Missing Rate:**\n- The **2026_scores** table has the most severe missing data, with **77.05% missing** in both `HomeScore` and `AwayScore` (272 out of 353 rows)\n- This likely represents future/scheduled games that haven't been played yet\n\n**Overall Dataset:**\n- The combined **2010_2026_scores** table shows **13.53% missing** in both score columns (837 out of 6,185 rows)\n\n**Historical Seasons (2010-2025):**\n- Most completed seasons have **~9-10% missing** in score columns\n- The pattern is consistent: when scores are missing, both home and away scores are missing together (same row counts)\n- This suggests these represent games that were scheduled but not played, postponed, or cancelled\n\n**Recent Seasons:**\n- 2023-2025: ~9.24% missing\n- 2017-2022: 9.26-9.51% missing \n- 2010-2019: 9.76-9.78% missing\n- 2020: 11.51% missing (COVID-impacted season)\n\n### No Other Missing Values\n\nThe analysis found **no missing values in any other columns** across the 451 tables in this dataset. All play-by-play tables and other metadata columns are complete — only the final score columns have nulls, and only in the score tables." } ```