I need to analyze the temporal patterns in this dataset. The card shows two temporal axes: Date (6/10/2022..7/8/2022) and Time (0:00:00..9:55:00). Let me start by examining the distribution of matches over time to identify any spikes, dips, or breaks. ```json { "action": "tool_call", "reasoning": "The dataset has Date and Time columns. I'll query the daily distribution of matches to identify spikes, dips, or breaks in the temporal pattern. This will show me the volume of matches per day across the roughly one-month period.", "tool": "query_sql", "args": { "sql": "SELECT Date, COUNT(*) as match_count FROM raw.table_tennis_sept2022 GROUP BY Date ORDER BY Date", "purpose": "Get daily match counts to identify temporal spikes, dips, or breaks" } } ```