Every figure below was recomputed from raw trade rows pulled through the platform's own API — none of it is read off a summary widget, and a fair amount of it disagrees with them.
Kinfo links a trader's profile to their real broker account and verifies the trades, which turns a track record into data instead of marketing. Its leaderboard sorts by all-time profit.
That ranking is close to useless, and why is the subject of this piece. I pulled complete histories for the entire top 20, plus three traders found by sweeping all 1,005 profiles, and re-derived every number from the individual fills. Profit turned out to be the wrong question. Whether the profit is real — whether it measures trading at all, whether it repeats, whether the mechanism is visible — separates these records far more sharply.
The four axes, and why profit is not one of them
Credibility
Is the reported profit actually trading? Positions with no cost basis, imported versus live-tracked history, and stock legs that quietly absorb the losses an option win rate advertises away.
Consistency
Does it repeat? Losing months, profitable years, monthly stability, drawdown against profit, and how much rides on the best month, best year and ten biggest trades.
Clarity
Can the mechanism be seen? Transparency settings, plus whether an exit rule is actually visible in the fills. You can only rebuild what you can read.
Replicability
Could a retail account run it? The capital implied by median position size and notional, and whether the posture needs a balance sheet most people do not have.
None of this scores skill. jurn is probably the best trader on the board and ranks 11th, because his edge needs $55bn of notional throughput and he holds naked index positions to expiry. Excellent and unreplicable are not contradictory.
All 23, ranked
| # | Trader | Score | Cred | Cons | Clar | Repl | Reported | Instr | Yrs+ | Lose mo | Fake% | Sells |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01 | onezerozerom | 93.2 | 85 | 95 | 100 | 100 | $1,191,444 | OPT | 7/7 | 18% | 2.7% | — |
| 02 | Kyle Williams | 92.0 | 89 | 100 | 100 | 72 | $10,689,559 | STK | 8/8 | 13% | 0.0% | YES |
| 03 | edu_trades | 88.7 | 90 | 100 | 88 | 65 | $3,757,530 | STK | 8/8 | 8% | 0.0% | YES |
| 04 | daily_harvester | 87.8 | 77 | 89 | 95 | 100 | $743,923 | OPT | 3/3 | 4% | 15.1% | — |
| 05 | KrisVerma | 82.5 | 90 | 79 | 88 | 65 | $3,065,901 | STK | 6/6 | 26% | 0.0% | YES |
| 06 | Gex | 82.1 | 80 | 74 | 86 | 100 | $1,042,158 | OPT | 6/7 | 14% | 0.4% | — |
| 07 | dom | 81.9 | 95 | 64 | 100 | 65 | $1,916,297 | STK | 5/6 | 29% | 0.0% | YES |
| 08 | TctTrader | 80.7 | 86 | 62 | 100 | 80 | $1,834,864 | STK | 7/8 | 33% | 0.0% | — |
| 09 | vette | 79.4 | 67 | 69 | 100 | 100 | $2,696,036 | OPT* | 7/7 | 28% | 16.5% | — |
| 10 | Weekly OPTIONS | 76.4 | 94 | 58 | 86 | 60 | $1,917,812 | OPT | 3/3 | 30% | 0.0% | YES |
| 11 | jurn | 75.0 | 100 | 53 | 95 | 35 | $5,704,957 | OPT | 3/3 | 27% | 0.0% | — |
| 12 | Steven Dux | 74.3 | 87 | 70 | 76 | 50 | $11,772,881 | STK | 9/10 | 25% | 0.0% | YES |
| 13 | Jay Gamma Trader | 73.5 | 91 | 46 | 95 | 60 | $1,804,278 | OPT | 2/3 | 38% | 0.0% | — |
| 14 | blacknugget | 73.3 | 90 | 32 | 100 | 80 | $2,615,164 | STK | 2/3 | 33% | 4.0% | — |
| 15 | Bobdog | 72.1 | 89 | 40 | 71 | 100 | $3,021,211 | OPT | 2/3 | 40% | 4.6% | YES |
| 16 | Aikido Trading Enigma | 70.3 | 88 | 50 | 95 | 38 | $10,309,138 | STK | 6/7 | 37% | 2.8% | YES |
| 17 | Pace | 70.2 | 56 | 55 | 95 | 100 | $1,710,888 | OPT | 5/6 | 31% | 12.3% | YES |
| 18 | Heliomaster | 68.1 | 80 | 63 | 59 | 62 | $10,904,738 | STK | 9/11 | 26% | 0.0% | — |
| 19 | ravenloft | 64.6 | 36 | 58 | 98 | 100 | $2,927,849 | OPT | 4/4 | 12% | 43.7% | — |
| 20 | greenmachine | 62.0 | 91 | 9 | 88 | 65 | $1,655,623 | STK | 5/9 | 49% | 0.0% | — |
| 21 | zanger | 60.4 | 63 | 18 | 95 | 92 | $2,084,488 | OPT | 8/12 | 35% | 9.4% | — |
| 22 | madaz | 55.6 | 80 | 17 | 64 | 65 | $11,328,730 | STK | 6/10 | 40% | 0.0% | YES |
| 23 | NeilStrikes | 42.2 | 30 | 0 | 100 | 78 | $2,724,544 | OPT | 6/13 | 57% | 141.2% | — |
* vette is 53% options by trade count but loses money on them. Fake% is the share of reported profit from positions with no purchase price — money that entered the account rather than being earned in it.
Where the money actually comes from
Of the eight top-20 traders who trade options, six earn their money somewhere else. And the two most consistent records on the whole board — edu_trades and madaz — never touched a contract: 27,958 and 53,278 trades, all stock.
Win rate is refuted twice, from opposite directions
madaz — 93.1% of trades win
The best rate on the leaderboard, and the second-worst record here. His losses average 11.5× his wins — $17,959 against $1,564. Worst single trade −$1,901,276. Months of −$3.05m, −$2.96m and −$1.82m sit inside a +$6.7m year, and his deepest holes have no recovery date at all.
jurn — the best bucket is the losing one
His 0-DTE trades are half of everything he does, win 78.8% of the time, and lose $931,081. At zero days to expiry the credit does not cover the tail: he wins four times in five and returns it on the fifth.
| Days to expiry at entry | Trades | Win rate | Net P&L |
|---|---|---|---|
| 0 DTE | 3,361 | 78.8% | −$931,081 |
| 1–2 | 1,776 | 71.7% | +$873,141 |
| 3–7 | 995 | 71.6% | +$3,913,885 |
| 8–30 | 399 | 76.9% | +$1,109,707 |
| >30 | 83 | 67.5% | +$632,969 |
Every profitable seller in this study loses two to three times more per loss than they win per win. The hit rate is a property of the structure, not evidence of skill.
One record inverts when you remove nine rows
Kinfo prices a position from its buy fills. When a position arrives without a purchase price — what a transferred-in holding looks like — the cost basis is zero and the entire sale books as profit.
NeilStrikes
His actual options book is roughly flat: +$71,180 across 1,252 rows. 47 of 82 months losing, and 56.1% of all gross wins come from ten trades.
Two of the top twenty are running bots
Nobody is asked to declare automation, so the evidence has to come from timestamps: entries landing on a :00/:15/:30/:45 grid, baskets of different underlyings filled in the same second, position sizes that are obviously computed.
Confirmed, and says so — the account is named "Algo account". 48.7% of 6,768 trades fire within 3 seconds of a :00 or :30 boundary, across 37 slots. A half-hourly timer loop.
rank 87 · 52% losing daysVery likely a bot; his profile does not mention it. 52.9% of entries land on the quarter-hour grid against 6.7% expected. Not feed rounding — those :00-second rows appear in only 21 of 60 minutes.
15-minute pollPartly automated; his profile does not mention it. Baskets of up to 15 different stocks bought inside 2 seconds with share counts like 33, 78, 86, 129 — the output of a sizing routine, not somebody typing.
algorithmic sizingNothing on the platform asks them to disclose it — this is an observation about how the trades were placed, not an accusation of concealment. Of the 1,005 profiles, 19 mention automation themselves, and the best of those ranks 40th; the tail is negative, one account down $329,542.
What a monthly curve hides — and what it reveals
The first version of this ranking gave edu_trades a max drawdown of $3,284 against $3.76m of profit. Somebody who follows him pointed out he had reported a loss of roughly $100k four weeks earlier.
Then the same reader pushed back again: doesn't a large gap also mean he recovers?
| Trader | Monthly DD | Daily DD | Ratio | Median days to fill |
|---|---|---|---|---|
| edu_trades | −$3,284 | −$125,166 | 38.1× | 12 |
| KrisVerma | −$406,658 | −$613,201 | 1.5× | 23 |
| onezerozerom | −$66,382 | −$76,805 | 1.2× | 24 |
| Kyle Williams | −$342,488 | −$516,441 | 1.5× | 32 |
| jurn | −$2,944,019 | −$3,949,478 | 1.3× | 63 |
| madaz | −$6,301,873 | −$7,181,342 | 1.1× | never |
Neither number is the number. Daily answers how deep the hole is while you are in it, which governs sizing. Monthly answers whether the strategy out-earns its holes, which governs whether you survive them.
The best record on the board is a habit, not an algorithm
onezerozerom never appears in the top 20 — he surfaced only by sweeping all 1,005 profiles. Seven profitable years out of seven, a median position of one contract, median 56 days to expiry, and 86% of short positions closed before expiry at a median 63% of the credit collected. He sells nothing and has 45 followers.
The obvious next step was to pin down the exact profit target. There isn't one.
Cross-tabbed against days remaining, the median capture slides from 53% with 30+ days left to 85% with 4–7 left, so it is not a time rule either. His entry is less specified still: 145 underlyings, a flat weekday distribution, expiries from 35 to 70 days out, and a credit-to-notional ratio from 0.02% to 4.91%. Nothing in 5,462 trades says why he opened that strike on that day.
He is not quietly automated either — schedule score 0.9%, same-second clusters collapse to 13 across the whole history. The sizing and the managed exits are a rule he follows by hand.
The broker settles what is left
| Trader | Executable | Already a spread | Naked call | Median collateral | Fits $1,000 |
|---|---|---|---|---|---|
| Jay Gamma Trader | 98% | 33% | 2% | $11 | 62% |
| onezerozerom | 69% | 12% | 31% | $9,700 | 28% |
| Bobdog | 80% | 1% | 20% | $9,400 | 26% |
| Gex | 73% | 12% | 27% | $12,900 | 19% |
| jurn | 54% | 2% | 46% | $4,440,000 | 7% |
| ravenloft | 51% | 0% | 49% | $67,500 | 5% |
| Pace | 47% | 2% | 53% | $75,000 | 1% |
Alpaca has no naked-option level. Shorts must be covered, cash-secured, or a defined-risk spread leg; there is no level 4. Every high-scoring trader here is a naked seller — their long-leg share runs 1.5% to 19%, and what makes them capital-efficient is exactly what a retail account cannot do. jurn is blocked twice over: 79% of his book is NDX-scale index options, and Alpaca does not list NDX at all.
The only book that natively fits is Jay Gamma Trader's, whose verticals and condors are what level 3 exists for — and he is a 44%-win 0-DTE buyer ranked 13th. Cheapest to execute, among the weakest to emulate.
What the whole exercise actually produced
Win rate is not an objective function
Refuted from both ends: 93.1% ranks 22nd of 23, and the highest-win-rate DTE bucket is the only losing one.
Consolidate every leg first
Assignment losses and delta hedges live outside the option ledger. Pace's option win rate is 89.6% and his book keeps a third of what that implies.
Say which drawdown you mean
One tells you how deep the hole is, the other whether you climb out. The wrong one here was 38× off.
Check the broker before the backtest
The winner scored 100/100 on replicability before anyone established that a retail account cannot place a third of his positions.
Five corrections in two days, and three came from someone else asking a question the analysis had not thought to ask — about a loss he happened to know about, about whether a ratio might mean something good, about whether the framing was fair. The data was complete from the first hour. What kept being wrong was the question put to it.
Monthly stability figures are monthly mean ÷ monthly standard deviation — unitless, for ranking only, not an annualised Sharpe ratio. Scores are a blunt summary; the columns behind them matter more than the composite. Research notes, not investment advice.