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The Math Behind Prop Firm Expected Value
The Expected Value Formula
Every prop firm evaluation is a financial bet. Like any bet, it has an expected value (EV) that determines whether it is worth taking. The formula is straightforward:
EV per attempt = (probability of passing x expected payout if you pass) - evaluation cost
If your EV is positive, the evaluation is a good bet over many attempts. If it is negative, you are paying for the privilege of losing money. Most traders never calculate this number. They buy evaluations based on marketing, sales prices, or what their favorite YouTuber recommends.
The difficulty is that both variables -- pass probability and expected payout -- depend heavily on your personal skill, discipline, and the specific firm's rules. A trader with a genuine 55% win rate and disciplined sizing has a completely different EV than a trader who revenge-trades after losses. The evaluation cost is the only number that is certain.
Simulation Setup and Assumptions
To estimate realistic EVs, we ran Monte Carlo simulations across 9 major prop firms using the following assumptions for a moderately skilled MES trader:
Base win rate: 53% (slightly above breakeven after commissions). Average winner: 8 points ($40 on MES). Average loser: 6 points ($30 on MES). Trades per day: 2. Trading days per week: 4 (selective, sits out low-quality days). No revenge sizing -- fixed 1 MES contract per trade.
For each firm, we simulated 10,000 evaluation attempts using that firm's specific rules: profit target, drawdown type (trailing vs static, real-time vs EOD), consistency requirements, minimum trading days, and fee structure.
The pass rate is the percentage of simulations that hit the profit target before hitting the drawdown limit. The expected payout is the average amount extracted from funded accounts that survive long enough to request a withdrawal, accounting for payout caps, profit splits, and the probability of blowing the funded account before reaching a payout threshold.
Firm-by-Firm Results
Results for a 50K account tier (evaluation costs at standard pricing, not sale pricing):
Apex ($167/month, real-time trailing): Pass rate approximately 35-40%. The real-time trailing drawdown is punishing -- intraday equity peaks tighten your buffer. But the 100% payout on the first $25K and relatively low monthly cost make the EV among the best when purchased during one of their frequent 80% off sales ($35/month).
Topstep ($49/month, EOD trailing): Pass rate approximately 45-50%. EOD trailing is more forgiving for intraday strategies. The $49 price point is the lowest standard cost among major firms. Payout caps ($5K or 50%) slow extraction, but the high pass rate and low cost yield positive EV for most skill levels.
MyFundedFutures ($100 one-time, EOD trailing Core): Pass rate approximately 40-45% on Core. One-time fee rather than monthly subscription changes the math -- you cannot bleed money month after month if you struggle. The Rapid plan (intraday trailing, 2-day minimum) has a lower pass rate but faster resolution.
The key finding across all firms: EV is most sensitive to evaluation cost, not to payout terms. A firm with a $35 evaluation and a 70/30 split often has better EV than a firm with a $200 evaluation and a 90/10 split, because the cost of repeated failed attempts dominates the equation.
The Hidden Costs
The evaluation fee is not the only cost. Hidden costs that erode EV include:
Platform fees: Most firms require a specific trading platform. Rithmic-based firms charge $25-30/month for data. NinjaTrader, Tradovate, and others have their own fee structures. These costs accrue whether you are trading or not.
Opportunity cost: Time spent trading evaluations is time not spent trading a live account, learning, or working. If you spend 3 months failing evaluations, that is 3 months of compounding you missed in a personal account.
Churn cost: The most insidious hidden cost is the cycle of fail-reset-fail. Each failed attempt costs the evaluation fee plus the emotional toll of starting over. Traders in a churn cycle often degrade in performance over time as frustration compounds. The EV formula assumes constant skill, but real traders tilt after repeated failures.
Sale timing: Evaluation costs during sales (commonly 50-80% off at Apex, Leeloo, and Bulenox) can cut the cost variable by 4-5x, which dramatically improves EV. The mathematically optimal strategy is to only buy evaluations during sales and never pay full price.
When to Walk Away
EV goes negative when any of the following are true:
Your pass rate is below the break-even threshold. For a $50/month evaluation with an expected payout of $500, you need to pass at least 1 in 10 attempts to break even. If your historical pass rate is lower, the evaluation is costing you money.
You are churning through funded accounts. If you pass evaluations but consistently blow funded accounts within the first month, your effective payout is zero and every evaluation fee is a pure loss. Fix the funded account problem before buying more evaluations.
You are paying full price repeatedly. At standard pricing, many evaluations have marginal or negative EV for average traders. The math only works consistently at sale pricing. If you find yourself paying full price because you "need to get back in now," you are making an emotional decision, not a mathematical one.
You are trading ES instead of MES. Our simulations show that switching from MES to ES roughly halves the pass rate while increasing the average loss per failed attempt. The EV destruction is multiplicative -- lower probability of success AND higher cost of failure.
The honest answer: prop firm evaluations are positive EV for disciplined MES traders who buy during sales, trade selectively, and never revenge-size. For everyone else, the math is likely working against them. Knowing which category you fall into -- and being honest about it -- is the most valuable calculation you can make.
This article is for educational purposes only and does not constitute trading or financial advice. Always do your own analysis and manage your own risk.