Prop firm challenge simulator: your odds of passing

A prop firm challenge simulator estimates your odds of passing a funding evaluation, and your odds of blowing the account, from three inputs: your win rate, your risk-reward ratio and your risk per trade. It does this with a Monte Carlo simulation: it replays the evaluation thousands of times with random trades that match your statistics and counts how many runs hit the profit target and how many hit the drawdown. The takeaway is almost always the same: with a positive-expectancy strategy, cutting your risk per trade raises your pass rate, at the cost of taking more days.

How to use the prop firm challenge simulator

1. Enter the challenge rules: profit target, maximum drawdown and daily loss limit, as a percentage or in dollars.
2. Enter your strategy: risk per trade, risk-reward ratio (R:R) and win rate. Use data from at least 100 of your own trades, from a demo account or an honest backtest.
3. Set how many trades you take per day. This drives how many days the challenge takes and how much the daily limit matters.
4. Run it and read three numbers: probability of passing, probability of blowing the account and median days to pass.
5. Change one variable at a time (risk first) and watch how the probabilities move.

Trading expectancy: the number that decides everything

Expectancy is what you make or lose on average per trade, measured in units of risk (R). If you risk $100 per trade, 1R = $100.

E = (win rate × B) − (1 − win rate), where B is how many R you make on a winner.

R:R ratio	Breakeven win rate	Example win rate	Expectancy per trade
1:1	50%	55%	+0.10 R
1:1.5	40%	42%	+0.05 R
1:2	33.3%	40%	+0.20 R
1:3	25%	30%	+0.20 R
1:1	50%	48%	−0.04 R

Expectancy also tells you how many trades you need to pass a prop firm challenge: target ÷ (E × risk). With an 8% target, 1% risk and E = +0.2 R, the average is about 8 ÷ 0.2 = 40 trades. That is an average: some paths get there sooner on a good streak and others take far longer.

Why lower risk raises your pass rate

Think of the evaluation as a race between two lines: the profit target above and the drawdown below. What matters is not the percentage but how many R away each line is. In Phase 1 of the EmergeFX 2-Step (8% target, 10% maximum drawdown):

• At 2% per trade, the target is 4 R away and the drawdown 5 R away. A five-trade losing streak, which is normal at a 40% win rate, ends the challenge.
• At 0.5%, the target is 16 R away and the drawdown 20 R away. You need many more trades, and over more trades your statistical edge beats the noise.

It is the same idea as risk of ruin: the smaller each bet is relative to the capital available, the lower the chance a bad streak knocks you out. But it only works with positive expectancy. With negative expectancy the opposite happens: more trades mean the disadvantage wins out too, and your pass rate drops as you cut risk. The fix in that case is not to risk more but to fix the strategy before you pay for an evaluation.

Odds of passing an evaluation: scenario table

We ran these scenarios through our own Monte Carlo simulation in Python, with 20,000 paths per scenario, on Phase 1 of the EmergeFX 2-Step Evaluation (8% target, 5% daily loss limit, 10% static maximum drawdown), two trades per day and a 5-day minimum. These are simulations, not trader results.

Strategy	Risk per trade	Passes	Blows the account	Median days to pass
40% win rate, 1:2 (E = +0.20 R)	0.5%	98%	2%	31
40% win rate, 1:2 (E = +0.20 R)	1%	88%	12%	11
40% win rate, 1:2 (E = +0.20 R)	2%	74%	26%	5
55% win rate, 1:1 (E = +0.10 R)	0.5%	98%	2%	61
55% win rate, 1:1 (E = +0.10 R)	1%	89%	11%	22
55% win rate, 1:1 (E = +0.10 R)	2%	76%	24%	6
42% win rate, 1:1.5 (E = +0.05 R)	0.5%	81%	19%	67
42% win rate, 1:1.5 (E = +0.05 R)	1%	69%	31%	19
42% win rate, 1:1.5 (E = +0.05 R)	2%	62%	38%	6
48% win rate, 1:1 (E = −0.04 R)	0.5%	23%	77%	95
48% win rate, 1:1 (E = −0.04 R)	1%	38%	62%	26
48% win rate, 1:1 (E = −0.04 R)	2%	46%	54%	7

Three takeaways. With a clear edge, going from 2% to 0.5% turns a challenge where “one in four fails” into one where “one in fifty fails.” With a thin edge (+0.05 R), even at 0.5% almost one path in five blows the account: real-world costs could erase that edge. And with negative expectancy, low risk gives the worst result, a sign that the problem is the strategy.

The same strategy across different evaluations

With a 40% win rate, a 1:2 ratio and two trades per day, here is how the odds change by challenge (same simulation assumptions; for futures, the EOD drawdown was modeled as a threshold that rises with the highest end-of-day balance).

Evaluation	Risk per trade	Passes	Blows	Median days
EmergeFX 1-Step (10% / 3% / 6%)	0.5%	91%	9%	38
EmergeFX 1-Step	1%	71%	29%	13
EmergeFX 2-Step, Phase 1 (8% / 5% / 10%)	1%	88%	12%	11
EmergeFX 2-Step, Phase 2 (5% / 5% / 10%)	1%	90%	10%	6
EmergeFX 2-Step, both phases	1%	≈ 79%	≈ 21%	≈ 17 in total
Futures 50K ($2,500 target, $2,500 EOD drawdown)	$125	94%	6%	39
Futures 50K	$250	77%	23%	13
Futures MICRO ($850 target, $800 EOD drawdown)	$60	84%	16%	25
Futures MICRO	$100	69%	31%	11

The 1-Step does worse at the same 1% because its drawdown is 6 R instead of 10 R. To match it you have to drop to 0.5%, and then it takes longer. We compare all three formats in more detail in 1-Step vs 2-Step vs Instant Funding.

How to read the simulator’s results

• Pass probability below 60%: your strategy or your risk doesn’t fit that challenge. Lower your risk or pick an evaluation with more room.
• Between 60% and 85%: workable, but one bad week could cost you the challenge. Check whether cutting risk by half a point is worth the extra days.
• Above 85%: the outcome now depends mostly on your actual win rate matching the one you entered. That is the weakest assumption.
• Median days: half of the passing paths pass before that number. If it feels like a long time, remember that Emerge evaluations have no time limit.

Run a stress test: knock 5 points off your win rate and simulate again. If the odds collapse, your edge is too thin to rely on. Once your risk is set, convert it into lots with the position size calculator or into contracts with the futures contract calculator.

Which Emerge Profit evaluation to choose based on your simulation

Emerge Profit offers simulated trading accounts in futures and in forex (EmergeFX). Trading involves risk and no simulation predicts the outcome of a specific challenge, but it does help you pick the format that best fits your numbers.

Option	Key rules	Best if…	Price
EmergeFX 2-Step Evaluation	8% and 5%; 5% daily; 10% static max; 1:100	Your simulation shows over 75% at 0.5% to 1% risk	From $68
EmergeFX 1-Step Evaluation	10%; 3% daily; 6% static max; 1:30	You trade low risk (0.5% or less) and prefer a single target	From $68
Futures Evaluation	$850 to $6,000 target depending on size; EOD drawdown; 5-day minimum	You trade indices, oil or gold on CME	From $60
EmergeFX Instant Funding	No evaluation; static drawdown; swing trading allowed	You don’t want to depend on the odds of passing	From $120
Futures Instant Funding	No evaluation; Classic or Flex; EOD or static	Same, for futures	From $130

• If your numbers fit a forex challenge, the EmergeFX Evaluation has a 5-day minimum, no time limit, and refunds the challenge fee with your first reward (100% on the 1-Step, 125% on the 2-Step). Static drawdown and weekend holding allowed.
• For futures, the Futures Evaluation has no activation fee and pays 100% of your first rewards once you pass. Positions are closed before the end of each session.
• If you would rather skip the challenge, compare EmergeFX Instant Funding and Futures Instant Funding: the risk math still applies, because those accounts also have a daily loss limit and a drawdown.

Prop firm challenge simulator FAQ

Sources

• IBM – What is Monte Carlo Simulation? (accessed November 2026).
• Wikipedia – Risk of ruin (accessed November 2026).
• Emerge Profit – in-house Monte Carlo simulation in Python, 20,000 paths per scenario with the assumptions stated in each table (November 2026).
• Emerge Profit – Account selector (evaluation and Instant Funding rules, accessed November 2026).

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