One trader, one playbook, one firm — Tradeify's 50K Growth. The strategy is not one thing: it's a policy that maps the account's state to a setup filter and a risk size. This page builds that policy from the ground up: first the playbook as a graded population of setups, then the eval priced step by step, then what stricter bias criteria do to your statistics, then why a funded account in profit is treated as a different asset entirely.
Every number on this page is computed live by the same engine as the calculator — deterministic seeds, no hand-waving.
"33% win rate" is a blend. Underneath it, setups arrive in grades — each with its own frequency and quality. A bias criterion is a filter over this population: raise the bar and you trade less often, win more often, and shrink variance. That's the whole mechanism, made explicit:
Rules that matter: $3,000 target · $2,000 EOD trailing drawdown · $1,250 daily loss limit (soft — ends your day, not your account) · no consistency rule · pass in as little as 1 day · $145 one-time, $95 resets, no clock. Here is the whole calculation, one step at a time, at the default eval strategy (every setup, $250 risk):
Three Tradeify rules turn the funded account into a different game — each one pushes the optimal strategy toward fewer, better trades:
Every payout needs 5 days of >$150 profit. A win must clear the bar: below ≈$65 risk a single 2.4R winner can't, and the account becomes structurally unable to ever pay out. The rule sets a floor under viable risk — you can be too small to get paid.
Your best day ≤ 35% of profit since the last payout — and losing days shrink the denominator. A $700 hero day demands $2,000 of cycle profit before you can withdraw. Big days don't win the funded phase; they raise its bar. Capped, repeatable days ($150–$250) walk straight through it.
The $2,000 trail rises only until it hits +$100, then freezes forever — triggered the first EOD balance at +$2,100. Before the lock, your real bankroll is the shrinking gap to a moving floor. After it, the account cannot be chased down. That line is the regime change your strategy switches on.
The same $100 of risk means different things at different states, because what you stand to lose is the account's continuation value — and that value climbs fast:
| State | What you're protecting | Setup filter | Risk posture | Day rule |
|---|---|---|---|---|
| Evaluation | $95 reset — almost nothing | Every playbook setup | High — buy time, not safety | Stop at the target; day stop 2R |
| Funded, below +$2,100 | The whole account EV, vs a moving floor | A and above | Moderate — reach the lock alive | No hero days; day stop 2R |
| Funded, floor locked | An annuity of capped payouts | A++ only | Sized to the ruin cap | Bank the day past $150–$250 |
| Live (post-review) | Real capital at 80/20 | A++ only — full stop | Out of scope here | Live strategies are a different animal |
The model is only as honest as its inputs. Tag every trade with its stage and grade, and these numbers become measured, not assumed:
| Metric | How to tag it | Feeds |
|---|---|---|
| Eval win rate (by grade) | tags: eval + a++/a/b | §1 population table, eval stage sims |
| Funded win rate (by grade) | tags: funded-grow / funded-protect + grade | funded sims — keep it separate from eval; pressure changes execution |
| Payout rate | payouts requested vs approved, days per payout cycle | validates simulated payout cadence |
| Qualifying-day rate | share of trading days > $150 | the payout-gate math in §3 |
| Best-day / cycle-profit ratio | largest green day ÷ profit since last payout | consistency-rule headroom (keep ≤ 35%) |
Trades are drawn independently within each grade — real losing streaks cluster, so ruin
probabilities read slightly optimistic; size the caps accordingly. The grade populations are assumptions
until your journal fills them in. The engine stops at Tradeify's live review and assigns the live account
no value — real EV is higher. Rules are the published numbers as of August 2026 and firms change them;
the spec sits at the top of engine.js with sources.