Ask any new trader how they measure their success and the answer will be win rate. If they've won 7 out of 10 trades they'll be chuffed, if they've won 4 out of 10 they'll be convinced they're a failure. Win rate on its own tells you absolutely nothing about whether a strategy is going to be profitable. What actually matters is the amount you make on the winning trade versus the amount you lose on the losing trade.
Risk to reward is the comparison of those two figures on a single trade. If you're risking $1 per share to potentially make $3 per share then your risk to reward ratio is 1 to 3. That's often expressed in R's where 1R is the amount you're risking on the trade. A trade that makes three times your risk is a 3R winner and a trade that hits your stop is a 1R loser.
The reason this is so important is simple maths. The win rate you need to break even is a function of your reward in relation to your risk. If you win 2R and lose 1R you only need to win around 33% of your trades to break even as one win will cover two losses. If you win 3R and lose 1R you need about 25%. If your wins and losses are the same size you need to win 50% to break even. If your winners are smaller than your losers you need to win significantly more than half your trades just to break even. It's that simple. Break even win rate is 1/(1 + reward to risk ratio).
That's why a trader with a 40% win rate can end up more profitable than a trader with a 70% win rate. Take the first trader who wins 3R on average and loses 1R. Over 10 trades they'll have 4 wins and 6 losses. That's 4 x 3R i.e. 12R, minus 6R, so they're up 6R. Now take the second trader who wins 0.5R on average and loses 1R. Over 10 trades they'll have 7 wins and 3 losses. That's 3.5R minus 3R so they're up 0.5R. One bad streak and that's all gone.
The thing that brings it all together is expectancy. Expectancy is your win rate multiplied by your average win, minus your loss rate multiplied by your average loss. In the first trader example that's 0.4 x 3R minus 0.6 x 1R which is 1.2R minus 0.6R or 0.6R per trade. So over many trades you can expect to make 0.6R per trade on average. If they're risking $100 per trade that's $60 of expected profit per trade before costs. A positive expectancy is a plus. A negative expectancy is a minus. It means the strategy is going to lose money over time regardless of how good the wins look.
To use this in your own trading you'll need real data. Take your last 30 to 50 trades and put them in a journal. For each trade record how much you risked, the result in R's and whether you adhered to your plan. Work out your win rate, your average winner and your average loser. Many traders are surprised by the results. Some will find their win rate is actually quite good but their losses are bigger than their winners (often down to them moving stops and/or holding losers too long). Others will find they're cutting their winners too early which will of course drag their average win down even if they're picking the good setups.
Risk to reward also helps you to filter the trades. If you've got a 2 dollar stop and the nearest realistic target is only 2.50 dollars away then your reward is only 1.25 times your risk and you'd need to win over 50% of the time to make that worthwhile. That's why you'll often see people pass on those trades as a form of discipline. You're looking for setups where the target is at least 2 or 3 times the risk so that the maths work in your favour even if you lose the majority of the time.
There's a balance to be struck. If you're chasing massive risk to reward ratios by setting out completely unrealistic targets then you'll end up with a very low win rate as price will rarely move any significant distance without first stalling. Setting a 10R target on a stock that normally moves a few per cent in a week is pure fantasy. Targets need to be based on something real rather than on what you want the ratio to be. A prior resistance level, a measured move or a multiple of the stock's normal volatility would all be far more sensible bases for a target.
It's also important to remember that expectancy is an average across many trades, not a guarantee for the next trade. A strategy with excellent expectancy can and will have five or six losses in a row (this is entirely normal). That's precisely why position sizing is so important. You need to keep each individual loss small (typically 1% of your account or less) so that you can survive those bad runs long enough for the maths to work out.
If you take one thing from this it's that you don't need to be right most of the time. You just need your winners to be meaningfully bigger than your losers and you need to know your own numbers. Track them, review them regularly and let the numbers tell you what to change rather than what you felt in the last trade.