How Many Traders Pass Prop Firm Challenges? 2026 Data Study

Research by Christian Preciado · Updated 12 October 2026

Short answer: there is no audited industry-wide prop firm pass rate. In the latest first-party statistics we verified, published evaluation-level pass figures range from 8.89% to 36.22%, depending on the firm, programme and denominator. Topstep reported a 16.8% account completion rate for 2025, while Tradeify reported 17.2% for August 2025 to July 2026. A separate FPFX Technology dataset covering more than 300,000 prop trading accounts reported that around 14% of traders reached a funded account.

So, if someone tells you that “90% of prop firm traders fail”, the direction may be broadly plausible for some programmes, but the exact percentage is not an established industry fact. The evidence shows that pass rates vary substantially depending on what is counted.

Passing the evaluation is only the first filter. Reaching a simulated funded account, keeping that account long enough to qualify for a payout and eventually trading real firm capital are separate outcomes with progressively smaller numbers of traders.

What this study covers

• Key findings
• Published prop firm pass-rate data for 2025–2026
• Prop firm pass rates compared
• Do 90% of prop firm traders really fail?
• Why pass-rate figures conflict
• The 300,000-account FPFX dataset
• Our challenge-probability simulation
• How risk per trade changes the result
• Why challenge attempts fail
• How many funded traders receive payouts?
• Passing versus long-term profitability
• How traders can improve their odds
• Sources and methodology

Prop Firm Pass Rate 2026: Key Findings

• There is no audited industry-wide prop firm pass rate covering all forex, CFD, crypto and futures prop firms.
• Among the current first-party disclosures we verified, evaluation-level figures range from 8.89% at Earn2Trade to 36.22% at Take Profit Trader.
• Topstep and Tradeify publish remarkably similar account-level results: 16.8% and 17.2% respectively.
• A broader FPFX Technology dataset covering more than 300,000 accounts and 100,000 traders across 10 firms reported that around 14% of traders passed a challenge and reached funded status.
• The same FPFX dataset reported that roughly 7% of all traders received a payout.
• Passing percentages change dramatically depending on whether the denominator is evaluation accounts, subscriptions or unique people.
• Topstep illustrates this clearly: 16.8% of Trading Combines passed, but 51.8% of individual participants passed at least once across one or more attempts.
• Funded status does not mean real capital. Many modern prop firms initially place successful traders in simulated funded accounts.
• Receiving a payout is a much stronger commercial outcome than merely passing an evaluation.
• Our simulation shows that win rate, realised reward-to-risk and risk per trade can materially change the probability of completing a challenge.

What Percentage of Traders Pass Prop Firm Challenges?

The most defensible answer in 2026 is a range rather than a single percentage.

Current first-party disclosures show evaluation-level success rates ranging from roughly 9% to 36%. However, that range should not be presented as proof that one firm’s challenge is four times easier than another. Firms use different definitions, evaluation structures, pricing models, reset policies and trader populations.

Some figures count each evaluation subscription separately. Others count unique traders. Some programmes are single-stage futures evaluations, while others use different risk rules entirely. A trader may also buy several evaluations before passing one.

Published Prop Firm Pass Rates Compared

The table below uses the latest directly published figures we could verify on 12 October 2026. These are primarily futures prop firms, which is important: they should not automatically be applied to forex or CFD evaluations.

Do not rank these firms by pass percentage alone. A higher percentage can reflect an easier target, different drawdown rules, more experienced customers, a different definition of “started”, the treatment of resets or a completely different evaluation design.

For example, Take Profit Trader’s published 36.22% figure is substantially higher than Earn2Trade’s 8.89%. That does not prove that one service is objectively better. It tells us that the measured programmes and populations produced very different completion rates. Traders still need to compare the actual rules.

You can read our Take Profit Trader review for the current programme rules behind that firm’s evaluation structure.

Why Topstep’s 16.8% and 51.8% are both correct

Topstep provides the clearest example of why the denominator matters.

Its 16.8% figure counts Trading Combines. Its 51.8% figure counts people who entered at least one Trading Combine and eventually advanced in one or more attempts.

Imagine one trader starts five evaluations and passes the fifth. At account level, one of five attempts passed: 20%. At trader level, that person eventually passed: 100%.

This matters financially. A trader can eventually become funded while paying for several attempts, resets or monthly subscriptions first.

Do 90% of Prop Firm Traders Really Fail?

Not as a proven universal statistic.

The claim that “90%” or “95%” of prop firm traders fail is repeated frequently, but no regulator, auditor or industry body publishes one figure covering every prop firm.

Some real datasets are close to that level. Earn2Trade’s 8.89% examination pass rate implies that about 91.11% of measured subscriptions were not successfully passed. However, Take Profit Trader reported a 36.22% pass rate during 2025, which implies a very different result.

The 300,000-account FPFX dataset is also frequently misquoted. It reported that roughly 14% of traders passed a challenge and approximately 7% of all traders eventually received a payout. That means the frequently repeated “93% fail” claim appears to confuse not receiving a payout with failing the initial evaluation.

“Prop Firm Pass Rate” Can Mean Five Different Things

Any article giving one prop firm success percentage should explain exactly what is being counted.

1. Evaluation-account pass rate

This divides successfully completed evaluations by all evaluation accounts or subscriptions started.

Repeat attempts are counted separately. If the same person fails four accounts and passes the fifth, the account-level result is one successful evaluation from five attempts.

2. Unique-trader pass rate

This measures how many individual people eventually passed at least once.

It can be dramatically higher because traders can purchase multiple evaluations. Topstep’s 2025 disclosure illustrates this with a 16.8% account-level completion figure versus 51.8% of participants progressing at least once.

3. Funded-account survival rate

This asks what percentage of traders keep the funded-stage account for a meaningful period such as 30, 90 or 180 days.

Most firms still do not publish enough data to calculate this consistently.

4. Payout rate

This measures the proportion of funded traders who actually receive at least one withdrawal or payout.

For a trader evaluating whether a challenge is commercially worthwhile, this is arguably more useful than the pass rate alone.

5. Live-capital progression rate

Many modern retail prop firms use simulated funded accounts before selecting a much smaller group of traders for real-capital trading.

Topstep reported that 0.71% of Express Funded participants moved to a Live Funded Account during its 2025 measurement period. Tradeify reported 3.0%, while MyFundedFutures currently publishes a 4.2% figure for simulated funded participants progressing to live.

The 300,000-Account FPFX Prop Firm Dataset

The broadest multi-firm dataset we found was supplied by prop-firm technology provider FPFX Technology and reported by Finance Magnates.

The dataset covered more than 300,000 accounts belonging to approximately 100,000 traders across 10 prop firms.

• 14% of traders passed a challenge and obtained a funded account.
• About 45% of traders who became funded achieved a payout.
• The source described this as approximately 7% of all traders receiving a payout.
• The average reported payout was approximately 4% of nominal account size.

This is useful because it spans multiple firms rather than one provider. However, it still has limitations. The firms were not named publicly, the measurement period is less transparent than the newer firm disclosures, and the data came from a technology provider serving the industry rather than an independent regulatory audit.

For that reason, we treat the 14% figure as a historical industry benchmark, not a prediction of the probability that an individual trader will pass FTMO, FundedNext, Topstep, Take Profit Trader or another specific programme.

What Was Reported for Topstep in 2024?

Business Insider reported that Topstep’s website showed a 12.4% funding rate for 2024 and that 28.3% of funded traders received a payout.

Topstep’s subsequent 2025 disclosure increased those published figures to 16.8% of Trading Combines successfully completed and 33.3% of funded participants receiving a payout.

However, this should not automatically be interpreted as proof that traders became more skilled or that the challenge became easier. Programme rules, participant mix, products and reporting methodology can change between periods.

Prop Firms Compare Challenge Probability Simulation

Published pass-rate data tells us what happened to groups of traders. It does not tell an individual trader how likely their own strategy is to survive a specific challenge.

To explore that question, Prop Firms Compare created a Monte Carlo simulation of a fictional two-step challenge.

This is not an estimate of the industry’s actual pass rate. It is a controlled scenario analysis showing how challenge success changes when trading statistics change.

Simulation assumptions

• Phase-one profit target: 8%
• Phase-two profit target: 5%
• Maximum overall loss: 10%
• Risk per trade: 0.5% in the win-rate analysis
• Average winning trade: +1.5R
• Average losing trade: −1R
• Maximum of 60 trades per phase
• 200,000 simulated paths per phase for each scenario
• Combined two-phase probability assumes statistically independent phase outcomes

The simulation excludes daily drawdown limits, consistency requirements, commissions, spreads, slippage, correlated positions, changing position size and behavioural errors. Real evaluation outcomes may therefore be materially different.

Estimated challenge success by win rate

The result demonstrates why a strategy can have positive expectancy and still struggle to pass within a limited sequence of trades.

At a 45% win rate with an average winner of 1.5R, the strategy has positive expectancy of +0.125R per trade. Yet only 15.4% of simulated paths completed both phases within the specified 60-trade limit per phase.

At a 40% win rate and 1.5R average winner, expectancy is approximately zero before trading costs. The simulated two-phase completion probability fell to just 2.5%.

This is why your realised trading statistics matter more than the reward-to-risk ratio you intend to achieve. A strategy described as “1:2” may produce a much smaller average winner when profitable trades are routinely closed early.

How Risk per Trade Changes Prop Firm Challenge Success

We ran a second simulation while holding win rate at 45% and average winning trade at 1.5R. Only risk per trade changed.

This does not mean that risking 1.5% per trade is optimal.

The fixed 60-trade horizon rewards strategies that reach the target quickly. Increasing position risk reduces the number of winning R-multiples required to reach the target, but simultaneously reduces the number of losses the account can survive.

At 0.5% risk, only 0.5% of phase-one simulations breached the overall loss floor. At 2% risk, the breach rate increased to 27.6%.

Real challenges can be stricter because daily drawdown, floating equity, commissions and several simultaneous positions may trigger a breach before the overall loss limit is reached.

Use our position size calculator to convert your chosen account risk into a trade size, and the drawdown calculator to understand how much room remains before a challenge breach.

Why Do Most Prop Firm Challenge Attempts Fail?

Published pass-rate data tells us that a large proportion of evaluation attempts do not succeed. It does not automatically tell us why each individual account failed.

However, several structural reasons explain why a profitable trading method can still struggle inside a prop firm evaluation.

1. The trader has no measured edge

A profit target cannot turn a break-even or losing trading strategy into a profitable one.

Before buying an evaluation, traders should know their realised win rate, average winner, average loss, maximum losing streak and historical drawdown across a meaningful number of trades.

2. The headline account size disguises the real risk budget

A $100,000 challenge account is not equivalent to having $100,000 available to lose. If maximum loss is $10,000, that amount — and often the smaller daily loss allowance — is the relevant risk budget.

With trailing drawdown structures, the usable buffer may be smaller still.

3. The challenge is path-dependent

Two traders can complete 100 trades with identical final statistics and have very different challenge outcomes.

One may start with a sequence of winners and build a cushion. The other may experience six normal losses before the strategy’s edge has time to emerge and breach the account first.

4. Traders increase risk to chase the target

A trader may follow a controlled approach on demo or personal accounts, then increase position size because a paid challenge feels as though it is progressing too slowly.

That behavioural change creates a different strategy from the one originally tested.

5. Multiple trades can represent one concentrated risk

Three trades do not necessarily represent three independent bets. EUR/USD, GBP/USD and gold positions, for example, may all be driven by the same US-dollar move.

Three positions each risking 0.5% can therefore behave more like one concentrated 1.5% exposure.

6. Prop firm rules can terminate a statistically recoverable strategy

A personal trading account may continue through a drawdown when sufficient capital remains. A prop evaluation ends when its contractual breach threshold is reached, even when the underlying strategy might subsequently recover.

That is why the challenge should be treated as a separate risk-management problem rather than simply trading the same strategy at maximum permitted size.

Our guide to passing a prop firm challenge explains how to set personal loss limits below the firm’s official boundaries.

How Many Funded Prop Firm Traders Actually Receive a Payout?

This is arguably the more important question.

A funded-stage badge has limited commercial value if the trader breaches the account before receiving money.

Again, these percentages use different denominators and cannot be ranked as though they measure identical things.

However, they consistently demonstrate an important point: reaching funded status does not guarantee a payout.

Reasons can include breaching the funded-stage account, failing to meet payout conditions, insufficient qualifying profit, consistency restrictions, inactivity or simply entering the funded stage too late in the measurement period to have received a payout yet.

The published figures do not imply that every participant who did not receive a payout necessarily lost their account or acted improperly.

Passing a Prop Firm Challenge Is Not the Same as Being Profitable

A challenge pass measures whether a trader satisfied a specific set of rules over one sequence of trades. It does not establish long-term profitability.

A trader can pass through a favourable sequence and later lose the funded-stage account. Conversely, a profitable low-volatility strategy may fail a challenge because its returns are too slow relative to the target and evaluation constraints.

Academic research into retail day trading provides useful context. Barber, Lee, Liu, Odean and Zhang found negative aggregate net performance among day traders in every year of the Taiwan Stock Exchange sample they studied, while related research found that only a small minority displayed persistent profitability.

SEBI research into Indian equity derivatives also found that the great majority of individual traders lost money during its measured period.

Neither study measures prop firm challenge success. They are included only to reinforce an important distinction: an evaluation structure does not create a trading edge that was not already present.

Which Prop Firm Pass Rate Matters Most?

For someone deciding whether to buy a challenge, the most useful funnel would contain four numbers:

1. Evaluation attempts that pass.
2. Unique traders who eventually become funded.
3. Funded traders who receive at least one payout.
4. Traders whose cumulative payouts exceed all fees, resets and subscriptions paid.

The fourth figure is arguably the most commercially meaningful — and it is almost never published.

A trader could receive a $500 payout after spending $800 across repeated evaluations and still be negative overall. “Received a payout” and “made money from prop trading” are not identical outcomes.

What Prop Firms Should Publish

Pass-rate comparisons would become far more useful if prop firms used standard definitions.

At minimum, an annual performance disclosure should include:

• total evaluations started;
• number of unique participants;
• number and percentage successfully completing each evaluation stage;
• number of resets and repeat attempts;
• number of unique traders reaching simulated funded status;
• funded-account survival after 30, 90 and 180 days;
• number and percentage receiving at least one payout;
• median payout as well as average payout;
• percentage whose cumulative payouts exceed their cumulative fees;
• number and percentage moved to real-capital accounts;
• and whether reported funded accounts are simulated or live.

Until disclosures become standardised, pass-rate league tables should be treated cautiously.

How to Improve Your Probability of Passing a Prop Firm Challenge

No checklist can guarantee that a trader passes. However, the challenge can be made unnecessarily difficult through poor programme selection and excessive risk.

1. Know your actual statistics. Use realised win rate, average winner, average loss, maximum losing streak and drawdown rather than estimates.
2. Choose rules that fit the strategy. Compare static versus trailing drawdown, daily-loss calculations, consistency rules, news trading and overnight restrictions.
3. Risk from the drawdown limit, not the headline balance. A $100K challenge with $5K usable drawdown should be risk-managed around that $5K constraint.
4. Create a personal daily loss limit. Stop trading before reaching the firm’s hard breach threshold.
5. Control correlated exposure. Calculate total account risk across positions that respond to the same underlying move.
6. Do not manufacture a deadline. When a programme has no time limit, there is little reason to double risk simply because progress feels slow.
7. Understand the funded-stage rules before buying. Passing an evaluation is less useful when the subsequent payout structure is incompatible with the strategy.
8. Review the cause of a failed attempt before buying another. More attempts create more opportunities, but repeating the same risk process also repeats the same failure mechanism.

If you are new to evaluations, see our prop firms for beginners. You can also browse our prop firm reviews for programme-specific analysis.

Sources and Methodology

We updated this study on 12 October 2026. Performance statistics were checked against current first-party firm disclosures where available. Because reporting standards differ, figures are reproduced according to the source’s own denominator rather than converted into a fabricated industry average.

First-party prop firm disclosures

• Topstep: 2025 Trader Performance Statistics. Reports 16.8% of Trading Combines successfully completed, 51.8% of individual participants progressing at least once, 33.3% of funded participants receiving a payout and 0.71% of Express Funded participants progressing to Live.
• Tradeify: Trader Performance Statistics covering August 2025 to July 2026, calculated as of 9 August 2026. Reports 17.2% evaluation-account completion, 40.3% participant-level progression, 28.5% funded-participant payout and 3.0% Live progression.
• MyFundedFutures: current Program Performance disclosure checked 12 October 2026. Reports 19.97% completing required evaluation objectives, approximately 19.95% advancing to simulated funded stage, 39.2% of simulated funded participants earning at least one payout and 4.2% progressing to Live.
• Take Profit Trader: 2025 Trading Test disclaimer. Reports 36.22% of Trading Tests successfully passed with traders attaining a PRO account.
• Earn2Trade: 2025 Exam Disclaimer. Reports an 8.89% examination pass rate, with separate LiveSim, Live and withdrawal statistics.

Multi-firm industry dataset

FPFX Technology data reported by Finance Magnates covered more than 300,000 accounts belonging to approximately 100,000 traders across 10 prop firms. The source reported that around 14% of traders passed a challenge and obtained a funded account, around 45% of those funded traders achieved a payout, and approximately 7% of all traders received a payout.

Historical reporting

Business Insider’s December 2025 reporting was used for historical Topstep 2024 figures and wider industry context.

External trading-performance research

Barber, Lee, Liu, Odean and Zhang, “Do Day Traders Rationally Learn About Their Ability?”, October 2017. The research examines Taiwan Stock Exchange trading data from 1992 to 2006.

Securities and Exchange Board of India research on individual equity-derivatives traders, reported September 2024, is included only as wider retail-trading profitability context and not as prop firm pass-rate evidence.

Prop Firms Compare original simulation

Prop Firms Compare Monte Carlo analysis, originally conducted June 2026.

Each scenario used 200,000 simulated trade paths per phase. A win added 1.5R and a loss deducted 1R. A path passed when the relevant phase target was reached, failed when maximum loss was reached, or was marked incomplete when neither boundary was reached within 60 trades.

The combined two-phase figure multiplies separately estimated phase-one and phase-two probabilities. It assumes independent phase outcomes and identical trading statistics in both phases.

The model excludes daily-loss limits, consistency rules, spread, commission, slippage, variable position sizing, correlated trades, market-regime changes and behavioural errors. The results are illustrative rather than forecasts of an individual’s trading outcome.

References

• Topstep Risk Disclosure: 2025 account, participant, payout and Live Funded progression statistics.
• Tradeify Trader Performance Statistics: official disclosure covering August 2025 to July 2026, checked 12 October 2026.
• MyFundedFutures Program Performance Disclosure: current official programme statistics checked 12 October 2026.
• Take Profit Trader Terms / Trading Test Disclaimer: official 2025 Trading Test completion statistic.
• Earn2Trade Exam Disclaimer: official 2025 examination, LiveSim, Live and withdrawal statistics.
• FPFX Technology / Finance Magnates: multi-firm dataset covering more than 300,000 accounts, approximately 100,000 traders and 10 prop firms.
• Business Insider industry report: historical Topstep 2024 data and wider reporting on industry disclosure.
• Barber et al. academic research: long-term evidence on retail day-trader performance.
• SEBI derivatives research reported by Reuters: wider context on individual leveraged-trading profitability.

How to Cite This Study

Prop Firms Compare (2026), “How Many Traders Pass Prop Firm Challenges? 2026 Data Study”, PropFirmsCompare.com. Last materially updated 12 October 2026.

Researchers, journalists and publishers may quote the findings with attribution and a link to this page. Contact Prop Firms Compare if you require additional information about the simulation assumptions or source definitions.