I need to identify time dimensions in this dataset and analyze them for notable patterns. Let me start by examining the temporal columns mentioned in the dataset card. ```json { "action": "tool_call", "reasoning": "The dataset card lists several temporal axes. The main historical data appears to be in raw.matches_1930_2022 with Date (1930-07-13 to 2022-12-18) and Year (1930-2022). I'll query this table to see the distribution of matches over time and identify any notable spikes, dips, or breaks in the timeline.", "tool": "query_sql", "args": { "sql": "SELECT Year, COUNT(*) as match_count FROM raw.matches_1930_2022 GROUP BY Year ORDER BY Year", "purpose": "Get the distribution of World Cup matches by year to identify temporal patterns, gaps, and anomalies" } } ```