Ask a new trader what makes a good strategy and almost all of them say the same thing: a high win rate. It's intuitive — winning more often feels like the definition of success. It's also the reason most retail strategies quietly lose money while looking "good" on paper.
Over 100 logged trades on a Topstep $50K Express account, the NY Open Breakout system I trade wins 47% of the time. It's wrong more often than it's right. Net result: +$12,861.84, a 1.82 profit factor. Here's the math behind why that's not a contradiction.
Win rate answers the wrong question
Win rate tells you how often a strategy is right. It says nothing about how much you make when it's right, or how much you lose when it's wrong. Those two numbers matter more than win rate, because trading isn't scored per-trade — it's scored on the sum.
Expectancy = (Win rate × Average win) − (Loss rate × Average loss)
A strategy can have this be positive even with a win rate under 50%, as long as the average win is large enough relative to the average loss.
The math, worked through
Say you risk $300 per trade with a 1:3 reward-to-risk ratio — a $900 target against a $300 stop. Run that at a 47% win rate over 100 trades:
- 47 wins × $900 = $42,300
- 53 losses × $300 = $15,900
- Net: +$26,400
Now compare a strategy with a much more comfortable 70% win rate, but a 1:1 reward-to-risk ratio — the kind of setup traders end up with when they take profit early "to lock it in":
- 70 wins × $300 = $21,000
- 30 losses × $300 = $9,000
- Net: +$12,000
The 47%-win-rate strategy made more than double the money. It felt worse to trade — you're wrong most days — but it was mathematically superior. This is the entire reason profit factor (gross profit ÷ gross loss) is a more honest scorecard than win rate: it accounts for size, not just frequency.
Why this trips traders up psychologically
A 47% win rate means slightly more than half your trades end in a loss. Emotionally, that reads as "this isn't working," even in weeks where the P&L is green. This is the single biggest reason traders abandon mechanically sound systems — not because the math stopped working, but because losing was uncomfortable at a rate the math always predicted.
It's also why traders self-sabotage a good setup by cutting winners early. If you take a 1:1 profit on a system built for 1:3 targets because "at least it's a win," you've quietly converted a profitable strategy into a losing one — same win rate, worse expectancy.
What to actually optimize for
- Reward-to-risk, not win rate. A 1:3 minimum target means you only need to be right about a third of the time to break even.
- Consistent stop logic. If your stop size varies randomly trade to trade, your risk:reward ratio isn't real — it's a number you calculated after the fact.
- Profit factor over a real sample. Ten trades tell you almost nothing. A hundred trades, logged honestly — wins and losses both — starts to tell you whether the edge is real.
- Letting winners run to the actual target, not to whatever number feels safe in the moment.
None of this means win rate is irrelevant — a strategy with a 5% win rate needs an enormous reward-to-risk ratio to survive variance, and most traders can't emotionally sustain that. But treating win rate as the scoreboard, instead of one input into expectancy, is the most common reason a statistically sound approach gets abandoned right before it would have paid off.
The system behind these numbers
The NY Open Breakout Playbook is built around fixed 1:3+ targets and structure-based stops — the exact framework that produced the 47%-win-rate, 1.82-profit-factor result above.
See the Playbook →