CFD · open dataset · verified 2026-01-15
Alpha Capital Group Alpha Pro 100K (10% drawdown, 2-step) pass rate: simulated odds
10,000 Monte Carlo paths per profile at seed 42, on the challenge’s exact published rules. Distributions under stated assumptions, never promises.
Developing trader
45% win rate, 1.4R average winner, 4 trades/day, risking 1% per trade
55.0%
pass per attempt · 95% CI 54.3%–55.7%
Consistent trader
48% win rate, 1.6R average winner, 4 trades/day, risking 0.75% per trade
95.3%
pass per attempt · 95% CI 94.9%–95.7%
Proven edge
52% win rate, 1.8R average winner, 3 trades/day, risking 0.5% per trade
100.0%
pass per attempt · 95% CI 99.9%–100.0%
Seed 42 · 10,000 paths per profile · engine v1.1.2. EV is net of every fee across a full journey (attempts, resets, activation, then 90 funded trading days of gated payouts); payout probability is the chance a funded account collects at least once. Assumptions and unsimulated rules: daily-loss-balance-based, payout-consistency-option-40pct, trades-resolve-same-day, post-target-min-days-risk-free, attempts-iid, funded-withdrawal-model, calendar-days-approximated. Details reproduce in the simulator run.
Precomputed odds
Not a ranking: simulated odds for three reference profiles.| Challenge | Developing trader | Consistent trader | Proven edge | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Pass % | EV | Payout | Pass % | EV | Payout | Pass % | EV | Payout | |
Alpha Capital Group · Alpha Pro 100K (10% drawdown, 2-step) CFD | 55.0% | +$14,114 | 74.2% | 95.3% | +$49,903 | 98.0% | 100.0% | +$48,813 | 100.0% |
Seed 42 · 10,000 paths per cell · engine v1.1.2. Deterministic Monte Carlo: same seed, same numbers. Pass % is per attempt, with its 95% CI on hover; EV is net of every fee. Assumptions and unsimulated rules are listed in each challenge’s simulator view.
What the numbers say
Simulated at seed 42, 10,000 paths per archetype: reproduce every figure in the on-page simulator. The developing trader (45% win rate, 1.4R average winner, four trades a day at 1% risk) passes 55.0% of attempts (CI 54.3–55.7%), averages 1.82 attempts and $904 in fees to fund, and shows +$14,114 expected value across the full journey including 90 funded trading days at the 80% split. The consistent trader (48%, 1.6R, 0.75% risk) passes 95.3% with +$49,903 EV; the proven-edge trader (52%, 1.8R, 0.5% risk) failed once in 10,001 simulated attempts. The 8% first target and the day-scaled loss allowance make this, alongside FundingPips’ Standard, the mildest evaluation geometry among the CFD two-steps in this dataset.
Read the funded numbers with the withdrawal model in mind (maximum allowed per cycle, never below the floor, flagged in every result): the developing profile collects at least once in 74.2% of funded runs but breaches in 87.6% of them within the horizon, netting positive EV through payouts banked before the breach. That is not a defect of the program; it is what a marginal edge does against any loss floor. The number that would change the picture (the on-demand payout path with its 40% best-day condition) is flagged as not simulated, so treat the biweekly baseline as the modeled case.
The rules, worked through
A balance-based daily loss: floating losses do not trip it
As the firm’s own rules explainer describes it (and as we encode it), Alpha Pro’s daily drawdown is measured from your balance at the daily reset, and the daily check looks at closed results: a position floating $5,500 against you mid-session does not by itself end the account on the daily rule, where an equity-based check at another firm would have. Worked example: from a $100,000 day-start balance the daily floor sits at $95,000; what matters is where you close, not where you traveled. Two honest caveats. First, the overall 10% floor still stands beneath everything: the daily rule being lenient does not make the account unbreakable. Second, whether the 5% allowance is computed on the day-start balance (as we encode) or on the initial balance is flagged in the dataset as needing first-party verification.
What the balance-vs-equity distinction is worth, and when it is not worth much
At the simulator’s trade-by-trade granularity, where each trade resolves at its close, Alpha Pro’s daily rule prices out almost identically to an equity-checked anchor rule with the same numbers: its simulated pass rates match FundingPips’ 2-Step Standard to the decimal. The difference lives inside the trading day, which the engine flags rather than models: a scale-in trader or a wide-stop trader who routinely floats large intraday losses will find equity-checked rules fail them on days balance-checked rules would not. If that describes you, the encoded numbers here understate the difference in your favor; if you flatten losers quickly, the two rule styles are equivalent for you.
The static floor, and the failure arithmetic
The maximum loss is 10% measured from the initial balance: a $90,000 floor that never moves, so profit banks as cushion. In the 10,000-path run of the developing archetype the account failed at the daily line 55.7% of the time and at the static floor 44.3%; per phase, that profile cleared the 8% step 71.2% of the time and the 5% step 77.3%, compounding to 55.0% per attempt. The $497 recorded fee does not refund, so the marginal trader’s expected cost across an average 1.82 attempts is $904.
Payouts, and the parts we flag instead of simulate
As encoded and last verified 2026-01-15: an 80% performance split with a biweekly cycle whose first payout comes roughly a week (about five trading days) into the funded account, or an on-demand option gated by a 40% best-day consistency condition, which the engine flags and does not simulate. In the 90-trading-day funded simulation under maximum withdrawals, 74.2% of developing-profile funded accounts collected at least one payout and 87.6% eventually breached; the consistent profile collected 98.0% of the time. The dataset also records a tighter Alpha Pro 8% variant (8% max, 4% daily). These numbers are for the 10% variant only. Pricing and rules change; the firm’s product pages are authoritative.
Where these rules come from
Simulated from the open-source rules dataset entry alpha-capital-group/100k-alpha-pro-10 (last verified 2026-01-15, against the firm’s published terms and cited sources), simulated with the open-source engine at github.com/LuxAlgo/prop-firm-sim. Rules change; Alpha Capital Group’s own page is authoritative. Every number above is a seeded Monte Carlo estimate: re-run the same inputs and you get the same digits.
These are reference profiles. You are not one.
Open this exact challenge in the simulator (it restores the encoded rules at seed 42 and runs), then swap in your own win rate, R-multiples, and risk.
Frequent questions.
There is no single pass rate: it is a property of your trading statistics. At seed 42 with 10,000 Monte Carlo paths per profile, the Alpha Pro 10% rules pass a 45% win-rate 1.4R trader risking 1% on 55.0% of attempts, a 48% win-rate 1.6R trader risking 0.75% on 95.3%, and a 52% win-rate 1.8R trader risking 0.5% on effectively all attempts. Run your own statistics in the simulator on this page for the number that actually applies to you.