Enhanced the trading statistics reporting in the c9s/bbgo repository by developing new metrics for performance analysis, including trade count, net profit, drawdown, and risk-adjusted returns. This feature enables interval-based evaluation of trading strategies, supporting more granular trend identification and risk assessment. The work focused on back end development using Go, with an emphasis on data analysis and financial modeling to deliver richer, auditable metrics. By tying the enhancements to a specific commit for traceability, the update improved data-driven decision making for the trading desk and product analytics, offering greater visibility into profitability and risk across trading intervals.