In discretionary trading, you’re handicapped by the lack of reliable testing and repeatable iteration. Because decisions are made case-by-case, you can’t generate the large sample of trades or the statistical confidence that a systematic process provides. That absence of rigorous testing means you can’t lean on iterations to refine or validate an idea; you must judge opportunities in real time with far less evidence. That constraint forces discretionary traders to be extremely selective: there are far fewer trades to take, and any prospective edge has to jump out as obvious and convincing. If an edge isn’t blatantly clear to you in the moment, it won’t be repeatable under different market conditions, so you effectively do nothing most of the time, waiting for setups that feel unmistakably tilted in your favor. By contrast, systematic trading builds confidence through structure: defined rules, backtests, and iterative improvement let you harvest many smaller, statistically defensible edges. Where a discretionary trader needs a glaringly obvious advantage to act, a systematic approach can accumulate lots of subtle advantages. This is not meant to judge either way; everyone has to find the approach that best fits their personality.