What is a good profit factor?
A computed table by win rate and risk/reward, the effect of costs, and why a high number on 30 trades means little.
Short answer
A profit factor above 1 means a strategy made money; after all costs, about 1.2 to 1.5 is a modest edge, 1.5 to 2 a solid one, and anything above 2 deserves suspicion until it holds over a few hundred trades. Profit factor = gross profit ÷ gross loss, and with losers at −1R it equals win rate × average win ÷ (loss rate × 1R) – so 40% winners at 2R give 1.33, and 50% at 1.5R give 1.50. There is no universal “good” value: it depends on the costs per trade and, above all, on the number of trades behind it.
Profit factor by win rate and average win
| Win rate | Avg win 0.5R | Avg win 1R | Avg win 1.5R | Avg win 2R | Avg win 2.5R | Avg win 3R |
|---|---|---|---|---|---|---|
| 30% | 0.21 (−0.55R) | 0.43 (−0.40R) | 0.64 (−0.25R) | 0.86 (−0.10R) | 1.07 (+0.05R) | 1.29 (+0.20R) |
| 35% | 0.27 (−0.48R) | 0.54 (−0.30R) | 0.81 (−0.13R) | 1.08 (+0.05R) | 1.35 (+0.22R) | 1.62 (+0.40R) |
| 40% | 0.33 (−0.40R) | 0.67 (−0.20R) | 1.00 (0.00R) | 1.33 (+0.20R) | 1.67 (+0.40R) | 2.00 (+0.60R) |
| 45% | 0.41 (−0.33R) | 0.82 (−0.10R) | 1.23 (+0.13R) | 1.64 (+0.35R) | 2.05 (+0.57R) | 2.45 (+0.80R) |
| 50% | 0.50 (−0.25R) | 1.00 (0.00R) | 1.50 (+0.25R) | 2.00 (+0.50R) | 2.50 (+0.75R) | 3.00 (+1.00R) |
| 55% | 0.61 (−0.17R) | 1.22 (+0.10R) | 1.83 (+0.38R) | 2.44 (+0.65R) | 3.06 (+0.93R) | 3.67 (+1.20R) |
| 60% | 0.75 (−0.10R) | 1.50 (+0.20R) | 2.25 (+0.50R) | 3.00 (+0.80R) | 3.75 (+1.10R) | 4.50 (+1.40R) |
| 65% | 0.93 (−0.02R) | 1.86 (+0.30R) | 2.79 (+0.63R) | 3.71 (+0.95R) | 4.64 (+1.27R) | 5.57 (+1.60R) |
| 70% | 1.17 (+0.05R) | 2.33 (+0.40R) | 3.50 (+0.75R) | 4.67 (+1.10R) | 5.83 (+1.45R) | 7.00 (+1.80R) |
Profit factor, with expectancy per trade in brackets, for losers of exactly −1R and no costs. Computed: PF = win rate × avg win ÷ ((1 − win rate) × 1R).
How to read the table
- The diagonal of 1.00 is breakeven: 50% at 1R, 40% at 1.5R, 33% at 2R. Everything above it made money before costs. The breakeven win rate for each R:R is in what is a good win rate.
- The same profit factor can hide very different systems. 50% at 1.5R and 60% at 1R both give 1.50, yet the first earns +0.25R per trade and the second +0.20R.
- Profit factor says nothing about frequency. A 1.3 system with five trades a day can earn more than a 2.0 system with two trades a month. Read it next to the expectancy.
Ranges, honestly
These bands are our reading of the arithmetic above, not an industry standard. They assume results after fees, slippage and funding, and a sample of at least 100 trades.
- Below 1.0: the strategy lost money in this sample.
- 1.0 to 1.2: a thin edge. Costs of 0.05R to 0.1R per trade, a few slipped stops or a change in market phase can erase it.
- 1.2 to 1.5: a modest but real edge if the sample is large.
- 1.5 to 2.0: a solid edge for most discretionary strategies.
- Above 2.0: possible, especially with few, selective trades, but check the sample size, whether one outlier carries the result, and whether costs are included.
What costs do to the profit factor
| System | No costs | Costs 0.05R per trade | Costs 0.10R per trade |
|---|---|---|---|
| 40% × 2R | 1.33 | 1.24 | 1.15 |
| 50% × 1.5R | 1.50 | 1.38 | 1.27 |
| 60% × 1R | 1.50 | 1.36 | 1.23 |
| 30% × 3R | 1.29 | 1.20 | 1.13 |
Costs (fees, slippage, funding) lower every winner and deepen every loser by the same amount in R: PF = w × (b − c) ÷ ((1 − w) × (1 + c)).
Why sample size matters more than the number
With 30 trades the measured profit factor of a system whose true value is 1.33 lands anywhere between about 0.7 and 2.3. Only with a few hundred trades does it settle near the true value – from the same simulation as the guide how many trades does a backtest need:
| System (true PF) | 30 Trades | 100 Trades | 300 Trades |
|---|---|---|---|
| 40% × 2R (1.33) | 0.73–2.29 | 0.94–1.85 | 1.09–1.61 |
| 50% × 1.5R (1.50) | 0.87–2.59 | 1.09–2.07 | 1.24–1.81 |
| 60% × 1R (1.50) | 0.88–2.75 | 1.08–2.13 | 1.24–1.83 |
Range in which 90% of simulated samples fell (5th to 95th percentile), 20,000 runs per cell, fixed seed 20261022. Method and script: see “How many trades does a backtest need?”.
Profit factor in Edgetrail
The profit factor calculator works from your sums of winners and losers. In the journal, Edgetrail calculates profit factor from net results after fees, to eight decimal places, per system and period, shows ∞ when there are no losers yet and puts the number of closed trades and the win rate next to it. Replay trades get their own profit factor in R in the backtest journal of the system. The exact rules are on the methodology page, the definitions of profit factor and its neighbours in the glossary. A good profit factor still fails with too much risk per trade – the risk of ruin calculator shows how much. Edgetrail costs $24 a month or $199 a year; the first 50 Founders pay $99 once, after that a Lifetime plan costs $249 once. The first 14 days are free without a credit card, and every payment comes with a 14-day money-back guarantee.
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Frequently asked questions
What is a good profit factor for day trading?
After fees and slippage, about 1.2 to 1.5 is a modest edge and 1.5 to 2 a solid one, provided it holds over at least a hundred trades. Day trading pays more costs per trade, so check the number after costs.
Is a profit factor of 3 realistic?
On a small sample, yes – with 30 trades a system whose true profit factor is 1.5 shows 2.5 or more in roughly one sample in twenty. Over hundreds of trades after costs, values above 2 are rare and deserve a second look.
How is profit factor different from win rate?
Win rate counts how often you win; profit factor weighs how much. A 30% win rate with 3R winners has a profit factor of about 1.29, higher than a 55% win rate with 1R winners (1.22).
Should profit factor include fees?
Yes. Costs cut every winner and deepen every loser, so a profit factor of 1.33 before costs drops to about 1.15 with 0.1R costs per trade.
Keep reading
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