Some traders assume good trading means winning almost every trade. The reality is actually humbling, and it reminds me of tennis. Even the greatest tennis players edge out opponents on only a slim majority of individual battles. It’s not about never losing; it’s about losing a little less often than you win, but doing so consistently.
The Tennis Big Three
There were about two decades of just three players dominating men’s tennis: Rafael Nadal, Roger Federer, and Novak Djokovic. It’s undeniable that these three were amazing in their sport, and one of them was ranked world #1 in nearly all the years from 2004 through 2023. The three of them won 66 out of the 83 grand slams during their era.
What were they actually doing to achieve this level of success? Were they winning every single point? Did they just never lose? Or did they chip away, swing by swing, hit by hit, till they outlasted their opponent?
I grabbed some career stats from ultimatetennisstatistics.com, and everything is as of writing. For those that don’t know anything about tennis: a player must win at least four points with at least a two point lead to win a game. You need to win six games (ahead by two) to win a set. Matches are typically best out of three or five sets, depending on the tournament.
- Rafael Nadal
- Won 54.4% of Points
- Win 59.6% of Games
- Won 76.9% of Sets
- Won 82.6% of Matches
- Roger Federer
- Won 54.1% of Points
- Win 58.1% of Games
- Won 75.8% of Sets
- Won 81.9% of Matches
- Novak Djokovic
- Won 54.5% of Points
- Win 59.3% of Games
- Won 76.6% of Sets
- Won 83.6% of Matches
The greats didn’t win every single point. They win a little over 54% of them, but they’ve played hundreds of thousands of them. This led them to winning 58.1% to 59.6% of their games. Which led to winning 75.8% to 76.9% of their sets. Which led to winning 81.9% to 83.6% of their matches. All of this resulted in their dominance of tennis and being considered the best tennis players of all time. Just winning a little over 54% of each point they played.
What does this have to do with trading?
For some reason, a 54% win rate with a 1:1 risk to reward sounds small to newer traders. It’s actually quite huge, especially as you start to scale up. If you can win 54% of the time with 1:1 risk-to-reward over a large enough sample size and across multiple market conditions, then you should be able to find a way to make good money.
A point in tennis is mostly binary (excepting replays/ hindrances) where a player either wins a point or their opponent does. Think of this like a trade risking $100 to win $100 (1:1). You either win $100 or lose $100 (excluding commissions and fees here). Binary outcome. Think of each point as a trade, each game is a trading day, each set is a trading week, and finally each match is a trading month.
I asked an AI:
“If I have a 54.33% win rate and I trade with a 1:1 one risk to reward ratio, and I take 5 trades per day, what would my daily win rate be?”.
It answered 58.1% of days would be winning days using binomial probabilities. This is right around the realm of the tennis stats above where games are like trading days. I know tennis games are played till a player gets 4 points (with at least a lead of 2 points), but I wanted to eliminate scenarios of neither winning or losing a day (2 wins and 2 losses).
I then asked AI the same, but changed it to asking what my weekly win rate and monthly win rate would be. It becomes 67% of weeks are winning weeks and 78% of months are winning months. These aren’t as high as the tennis numbers, but there are differences in inputs too. There are 5 days a week but 6 games per set and around 100 trades per month but a tennis matches are best out of 5.
The point remains: You can achieve fantastic results with a slightly better than 50% win rate at 1:1. The same can be said of lower or higher win rates as long as your risk to reward ratio adjusts accordingly. You shouldn’t expect a single trade to win it all for you. Stop chasing perfection. Hunt for that repeatable setups that yields winning expectancy. It’s about repetition. It’s about the results from hundreds if not thousands of trades.
