Prop Firm Backtest Simulator

Buying a prop firm challenge is a bet with a capped downside and an uncapped-looking upside — but most tools that estimate your odds do it with a formula, assuming your strategy behaves like a textbook random walk. Real markets don't. A real losing streak clusters in ways a closed-form model can't see, and a mandatory hold period before your first payout can quietly give back profit a formula never accounted for.

This prop firm backtest simulator skips the formula. Upload your own MT5 Strategy Tester report, and it replays every real historical starting point in your trade history against the challenge's actual rules — phase targets, drawdown, daily loss limits, payout timing — to show you what would genuinely have happened, not what a model predicts should happen.

It takes two inputs — your strategy's trading statistics and a prop firm's rules — and returns what actually matters before you pay for an evaluation: your probability of passing, your expected value per attempt, your ROI, and roughly how long it will take.

Upload your MT5 Strategy Tester .html export — it's read entirely in your browser and never leaves your device. The tool normalizes every trade to a risk-adjusted unit (a multiple of what you actually risked per trade), then confirms the risk % it detected from your backtest's inputs.

From there, it runs a walk-forward simulation: for every single real day your history offers as a starting point, it replays your actual subsequent trades forward through the challenge's rules — evaluation targets, drawdown, daily loss limit, minimum trading days — and into the funded stage, including the mandatory hold period before a first payout. Starting points without enough real trading history ahead of them to reach a resolution are discarded, never filled in with invented data.

The result is a real distribution built entirely from your own trading, not an assumption about how markets behave.

P(pass evaluation) — the share of your own real historical starting points that would have reached the funded stage.

Median outcome — the typical real net result (payouts + refund − price) across all usable starting points. More reliable than the average, which a handful of unusually strong stretches can pull upward.

Effective sample size — how many genuinely independent tests your history actually provides, correcting for the fact that nearby starting points overlap and aren't separate evidence. A low number is a real caution flag, not a technicality.

How your attempts typically played out — the split between never funded, funded but never paid out, and funded with at least one payout.

Economics per attempt — expected value, average and largest payout, and a couple of real-data honesty checks: the worst actual run of consecutive failed attempts in your history (no independence assumption), and what share of funded accounts were still active — not failed — when your data or horizon simply ran out.

Real distribution table — worst case through best case, each figure a real outcome from an actual day in your history, not a projection.

Why walk-forward instead of a Monte Carlo simulation or a formula?

A formula assumes your strategy behaves like a statistical model — Monte Carlo resampling invents synthetic trade sequences that never happened. Walk-forward does neither: it replays only real, actual sequences of your own trades, so it naturally captures real market clustering — the way a bad stretch tends to bring several losses close together — that a formula or synthetic resample can miss.

Why is "effective sample size" so much smaller than the number of usable starting points?

Two starting points a day apart share almost the exact same subsequent trades — they're not independent evidence, just the same evidence counted twice. Effective sample size estimates how many truly distinct tests your history provides once that overlap is accounted for. A low number means: get a longer backtest or use a shorter horizon before trusting the result too far.

Can I see what happens at a different risk % without re-running my backtest?

Yes — the simulator lets you set a risk % to simulate separately from the risk % actually used in your uploaded backtest, for both the evaluation and funded stages. It rescales your real trade outcomes proportionally, which mirrors how position sizing itself works — though it can't account for lot-size rounding or margin limits at extreme risk levels.

Is a high pass rate a guarantee?

No. It's what actually happened across every real starting point your own history provides — not a prediction for any single future attempt. Markets change, and a strategy that performed well in the past isn't guaranteed to keep doing so.

Where do the challenge rules and prices come from?

You enter them yourself, exactly as the firm lists them at checkout. The simulator makes no assumption about any specific firm's current terms — always confirm against the firm's live rulebook before paying.

This tool is for educational purposes only. It replays your own uploaded backtest against rules you provide — it does not predict, guarantee, or recommend any specific trading strategy, prop firm, or purchase. A backtest is not a guarantee of future performance, and market conditions change. Verify every rule, price, and add-on against the prop firm's current terms before making a purchase decision. Nothing on this page is financial advice.