**Size** - The dataset has **718,470 rows** across 5 tables. That is the sum of the row counts from `analytics.table_overview`: - `raw_kaggle`: 237,205 - `return_kaggle`: 237,196 - `serve_kaggle`: 237,185 - `players_tournament_man_`: 6,422 - `players_man_`: 462 - **The column count depends on the source.** - The dataset card lists 78 columns: 21 in each of the three match tables, plus 8 in `players_tournament_man_` and 7 in `players_man_`. - The catalog overview reports 58 columns: 17 in each match table, plus 4 and 3 in the two player tables. - I did not reconcile the two counts. The card's figure may include columns the catalog overview doesn't count, so I'd treat 58 to 78 as the range. **Time period** - Yes, the dataset is time-bound. - The three match-level tables (`raw_kaggle`, `return_kaggle`, `serve_kaggle`) store `Date` as text. After parsing, every row converted successfully (237,205, 237,196 and 237,185 rows respectively), and each table spans **13 Aug 2001 to 28 Oct 2024**, about 23 years. - `players_tournament_man_.year` covers **2002 to 2024**. - `players_man_.playing_years` is a text list of years, so I did not compute a range for it. - The card showed narrower date ranges, such as 2013 to 2024 for `raw_kaggle`. Those came from sorting the text values, not from real dates. The parsed values above are the reliable ones.