I need to explore this boxing dataset systematically to find surprising patterns. Let me start by understanding the data structure and then look for counterintuitive findings. {"action": "tool_call", "reasoning": "First, I'll examine the basic statistics of fight outcomes and boxer characteristics to establish baseline expectations before looking for surprises.", "tool": "query_sql", "args": {"sql": "SELECT f_boxer_result, COUNT(*) as fight_count, AVG(f_boxer_age) as avg_age, AVG(f_boxer_won) as avg_prior_wins, AVG(f_boxer_lost) as avg_prior_losses, AVG(f_boxer_ranking) as avg_ranking FROM raw.cleandata WHERE f_boxer_ranking IS NOT NULL GROUP BY f_boxer_result ORDER BY f_boxer_result", "purpose": "Establish baseline win/loss patterns and characteristics", "source": "raw"}}