Good decisions and good outcomes are not the same thing
Decision theory begins with a distinction that cuts against ordinary language. A good decision is one that follows sound reasoning from the information available at the time of the choice. A good outcome is what actually happens afterward. These two things often coincide, but they are logically separate: you can make a careful, well-reasoned choice that happens to turn out badly, and you can make a reckless choice that happens to turn out well. The first is still a good decision, and the second is still a bad one.
This distinction matters because it determines how we learn from our choices. If you judge decisions by their outcomes, then a lucky gambler looks wise and a thoughtful planner looks foolish whenever bad luck strikes. That makes it nearly impossible to improve your reasoning over time. If instead you judge decisions by the quality of the thinking behind them — given what you knew and could have known — you can actually extract lessons from experience without confusing yourself every time variance intervenes.
The technical name for confusing decision quality with outcome quality is resulting. A poker player who makes a mathematically correct fold but would have won the hand had she stayed in is often told she made a mistake. She did not. A venture capitalist who invests in a company with strong fundamentals, a sound team, and a clear market, but which fails because of an unforeseeable regulatory change, made a good decision with a bad outcome. Professionals in high-variance domains — medicine, investing, military strategy, emergency management — learn this distinction early or burn out from the emotional toll of judging themselves by results they cannot fully control.