TL;DR: A prop firm challenge is a race between two barriers, and with no edge your chance of hitting the target first is about drawdown ÷ (target + drawdown). That is 37.5% on a Propr Classic 1-Step and 25% on a Turbo 1-Step, whatever your size. Smaller size only slows you down unless you have an edge, and trading costs pull the odds below that ceiling. Any pass-rate claim should be read against this baseline.
Why is a prop challenge a gambler's ruin problem?
Strip a challenge down to its essentials. You start at a balance. Above you is a profit target; below you is a loss floor. Your equity wanders between them until it touches one. That is the setup of the gambler's ruin, one of the oldest problems in probability: a gambler with a fixed bankroll bets until they either reach a goal or go broke.
The classic result is that in a fair game, the probability of reaching the goal depends only on the distances to the two barriers. Nothing else (bet size, number of bets, how you sequence them) changes it, as long as each bet is small relative to the distances to the target and the floor.
What are your odds with no edge?
Here is the short derivation. Suppose your trading has no edge, so on average each trade neither gains nor loses: your equity is a random walk with zero drift. Call the target distance T and the drawdown distance D, both as a percentage of the starting balance. Let p be the chance of hitting the target first.
In a fair game, your expected final result equals where you started, zero. You end at +T with probability p and at −D with probability 1 − p, so:
p × T − (1 − p) × D = 0, which gives p = D ÷ (T + D).
Applied to Propr's four challenges (rules from Propr's rules page):
| Challenge | Target (T) | Max drawdown (D) | Zero-edge odds D/(T+D) |
|---|---|---|---|
| Classic 1-Step | 10% | 6% static | ≈ 37.5% |
| Turbo 1-Step | 9% | 3% static | 25% |
| Pro 1-Step | 12% | 5% static | ≈ 29.4% |
| Classic 2-Step | 10% total | 8% trailing | ≈ 44% by formula; about 32% simulated |
The formula treats the 2-Step floor as if it were static. Propr's 2-Step floor actually trails the high-water mark by a fixed 8% of the starting balance, so after a rally the floor moves up with you. The no-edge odds for the Classic 2-Step are about 32% in our simulations; the simple dd/(target+dd) formula gives 44%, but the trailing floor follows the peak until it locks at the starting balance, which lowers it. The trailing vs static drawdown guide shows how the floor moves.
These are ceilings for a strategy with no edge, not floors. Real strategies with no edge do worse, for two reasons covered below.
Why does position size change speed but not odds?
Look at the formula again: size does not appear in it. Trading at twice the size means each trade moves you twice as far toward one barrier or the other, so you arrive sooner, but which barrier you reach first is still a coin flip weighted by the distances.
Size does change duration dramatically. For a zero-drift walk, the expected number of steps to hit either barrier is roughly T × D divided by the square of the step size. On a Classic 1-Step (T = 10, D = 6):
| Each trade moves equity by | Expected trades to finish | Zero-edge odds |
|---|---|---|
| ±2% | about 15 | 37.5% |
| ±1% | about 60 | 37.5% |
| ±0.5% | about 240 | 37.5% |
Halving size roughly quadruples the time and leaves the odds where they were. That is why a patient, tiny-size strategy with no edge is not "safer" in any useful sense: it simply takes months to deliver the same result.
How do costs push you below the ceiling?
The formula assumes a fair game. Trading is not one: every trade pays fees and slippage, and perps pay or receive funding. With no edge, costs give your equity a negative drift, and a negative drift makes the floor even more likely.
Leverage magnifies the problem. A round trip of about 17 bps in costs at 10x leverage costs about 1.7% of the account per trade, which is more than half of a 3% daily limit spent before the market has moved. Our best results came at 1–3x. See trading fees in perp backtests for how quickly costs compound.
Here is the subtle part: with a negative drift, smaller size makes things worse, because you spend longer exposed to the drift before reaching either barrier. The table below is a hypothetical model, not our data: each trade moves equity by a fixed step, and the average trade either loses or gains 5% of that step.
| Each trade moves equity by | Average trade loses 5% of step | No edge | Average trade gains 5% of step |
|---|---|---|---|
| ±2% | about 28.5% | 37.5% | about 47.1% |
| ±1% | about 20.8% | 37.5% | about 56.5% |
| ±0.5% | about 9.9% | 37.5% | about 72.9% |
Size amplifies whatever you bring. With a cost-driven negative edge, small size grinds you down toward the floor. With a genuine positive edge, small size lets the edge accumulate and raises your odds well above the ceiling. With no edge, size changes nothing but the calendar.
What does the daily loss limit do to the math?
A daily loss limit adds a third barrier that moves every day: equity may not fall more than a set percentage below the balance the day began with. On Propr's 1-Step challenges that is 3%, measured from the 00:00 UTC realised balance, and judged on equity at any moment.
At small sizes the daily limit rarely binds. At larger sizes, a single bad day can breach it long before total drawdown is in danger, so it is one more way to fail and the odds drop below the two-barrier ceiling. Our backtests show this clearly: on the Classic 1-Step Fast plan, 36% of starts failed on the daily limit and only 4% on drawdown. Our post on the daily loss limit covers how to budget for it.
What must an edge add?
To beat the ceiling, a strategy needs a positive expectancy after all costs that is large relative to the noise of its trades. The ratio matters more than either part alone: the model table above shows that an average gain of just 5% of each trade's swing lifts a Classic 1-Step from 37.5% to the mid-50s at ±1% steps.
Our out-of-sample research suggests most picks deliver less than that: candidates chosen on older data passed about 25–34% within 180 days (median about 30%), in line with the zero-edge ceilings (25–37.5%). With a one-year window and small sizes, bands rose to roughly 34%, 45% and 54%, a modest edge for the best picks; our planning figure for the slowest tier is 40–55%.
Very fast attempts sit below the ceiling: about 7% pass in under a day with aggressive SOL breakout sizing, and about 22–25% in 1–2 days with a daily SMA50 trend on BTC and ETH at high size, below the Classic's 37.5% ceiling, because at large size the daily limit becomes the binding barrier.
How should you read any pass-rate claim?
Start with the ceiling. If someone claims 90% or more on rules where the no-edge figure is 37.5%, the claim implies a large, durable edge. Then ask:
- Is it in-sample? Strategies chosen on the data they are scored on look better than they are. See selection bias in backtests.
- How many independent starts? Challenges started on consecutive days share most of their path, so hundreds of starts can behave like a handful of attempts.
- Are costs and exact rules modelled? Momentary equity breaches, the 00:00 daily base and a trailing floor all lower pass rates.
A published community bundle claiming about 94% passed 0–44% under Propr's real rules and never passed a 2025 start within a year. Our own house plans show 58–100% in-sample, and we pair every one of those numbers with the out-of-sample figures above.
How Trigr fits in
Trigr's rules check replays any agent you build yourself and deploy on Propr (house plans show their measured record instead) from every UTC start day against the account's exact daily-loss and drawdown rules, so you can see where your strategy sits relative to the ceiling before you pay a fee. The plans on Discover › Propr show backtest pass rates, failure breakdowns and a live record, and the pass-rate post explains how to read them. The math does not change for anyone: without an edge, the best you can do is the ceiling, and costs make it worse.