During a two-week dry run we ran identical scripts across several platforms with the same historical feed, identical fee schedules and a conservative slippage model to see where backtests diverged from live behavior. For clarity in the results our choice was the best crypto backtesting tool which supported per-tick replay, custom exchange fee ladders, funding-rate simulations and range-based order fills. The logs showed realistic execution timestamps, fill latencies and an itemised PnL cadence so we could compare fee drag and worst-case slippage. Bottom line: test on small live slices after backtests and prioritise tools that expose raw fills and time-of-fill data so strategy assumptions hold up in the real market.