Between June 2021 and February 2024 we published a spreadsheet every month containing every signal we had sent: 33 files, 33,694 orders, 33,095 wins and 599 losses. Monthly hit rates in those files run from 92.4% to 100.0%, with a median of 98.9% as reported in those spreadsheets. The files are still downloadable, and this article is about what they do and do not prove.
Almost every signal provider advertises a win rate. Almost none publish the rows behind it. The difference matters more than the number itself, because a rate is a claim while a file is evidence — and evidence can be recounted by somebody who does not like you. What follows is the whole record, the accounting rules that produced it, the months we would rather not show you, and the reasons your own result would not have matched it.
What is actually inside the thirty-three files
Each monthly file is a spreadsheet of the orders sent that month, one row per order, with the symbol, the direction, the entry, the outcome and the return. They are not summaries. The month's rate is what you get when you count the rows yourself.
The sheets are archived, unedited, at our published reports page. A row that was written in 2021 says the same thing today as it did then, which is the only property that makes a track record worth anything at all.
Volume varies enormously by month, and that variance is itself informative. June 2021 has 409 orders. June 2023 has 2,522. January 2024 has 2,578. A provider posting three calls a week and a provider posting eighty a day are not doing the same job, and a single percentage flattens that distinction away.
The shape of the record, month by month
An average hides the thing a sceptic wants most: the dispersion. So here is every month plotted rather than summarised.
Two features are worth naming. The first is that the weak months cluster at the beginning — four of the five lowest readings fall before October 2022. The second is that the line is not flat, which is the only reason to believe it was not written by a marketing department.
The median month reads 98.9% as reported in those spreadsheets. Aggregated instead across all 33,694 rows, the record is 98.2%, because the weaker months tend to be the busier ones and carry more weight. Both numbers are true; they answer slightly different questions, and quoting only the friendlier one would be the first small dishonesty.
The three crossed lines on that card are the claims a headline rate is usually stretched to cover. None of them survive contact with the files.
Why these spreadsheets have no "expired" column
This is the caveat that matters most, so it gets its own section rather than a footnote.
In those files, every order resolved as either a win or a loss. There is no third category. Nothing sat open at month end, nothing was recorded as having run out of time without reaching a target or a stop. That accounting choice is a large part of why the number is as high as it is, and any reader who takes the headline rate at face value without knowing it has been misled — by omission, but misled.
We are not defending the choice. We are telling you it existed, because a rate you cannot interpret is worth exactly nothing. If you are comparing us against another provider's advertised figure, the first question to ask them is the same one: what happened to the trades that ended neither way? A provider who cannot answer it is quoting a number they have not examined. How to read crypto signals covers what the fields in a signal mean; the outcome rules are the half that rarely gets written down.
The four weakest months, named
Naming your worst months is cheap to do and almost nobody does it, which is precisely why it is worth doing.
June 2021 is the floor: 409 orders, 31 of them stopped out, 92.4%. September 2021 is the loudest, because the volume was high — 1,204 orders and 78 losses at 93.5%. August and September 2022 sit at 93.6% and 94.1%, in the middle of a market that punished long exposure and in which the sheet was overwhelmingly long.
Individual rows go much further into the red than the monthly average suggests. The worst single order in May 2022 is recorded at -141.4%; February 2024 contains one at -179.84%. Those are leveraged per-order figures, not account outcomes, but they are in the file, and they are the reason a hit rate on its own tells you nothing about whether the month was survivable.
What the live performance page counts differently
The spreadsheet series stops at February 2024. Since June 2026 there has been a second, stricter record: the performance page, regenerated hourly straight from the trade database.
Its definitions are printed on the page. A win is a target hit. A loss is a stop hit. An expired trade is one that reached maximum hold with neither, and expired trades count against the rate: the target-hit rate is wins divided by wins plus losses plus expiries. Open positions are listed separately rather than being quietly counted as anything. Profit and loss is shown unleveraged.
Under that rule the four months so far read 94.3% for June 2026, 88.3% for July, 91.0% for August and 97.2% for September so far — the last one partial, with 50 positions still open at the time of writing. Only signals actually broadcast to members are counted; informational reports and internal experiments are excluded.
One column needs saying out loud. Losses read zero every month, and not because stops rarely trigger: broadcast signals carry no stop price, so a stop hit cannot be recorded. Every miss lands in expired, and where to cut a loser is left to you.
The same month scored under both rules
Here is the comparison stated as plainly as we know how to state it.
July 2026 broadcast 5,448 signals. 4,811 reached their target. 637 expired. Zero hit a stop. Under the live page's rule that is 88.3%. Under the spreadsheets' rule — where the only outcomes are win and loss — the same month would have printed 100%, because no stop was hit.
That gap is not a rounding difference or a bad quarter. It is the same trades scored two ways, and it is the single most important thing on this page. A historical 98.9% as reported in those sheets and a live 88.3% describe different measurements, not different performance. Anyone lining our historical figure up against a competitor's advertised one is comparing accounting systems, and probably losing the comparison without knowing it.
What counts as an order, and what the return columns mean
For the sheets to be auditable the definitions have to be boring and fixed.
An order is one signal broadcast to the channel, on one symbol, in one direction, with its entry and its levels stated at the time of sending. Re-entries on the same symbol are separate rows. Nothing is merged, and nothing is added after the fact.
Two return columns appear per month, and they are not interchangeable:
- Average return is the mean per-order result for the month — 2.19% in June 2021, 0.31% in August 2022, 2.57% in June 2023. It is a per-trade figure and says nothing about how much of an account was committed.
- Return at 1% sizing is what the month's rows would have produced under a fixed 1%-risk position sizing rule applied across all of them: 8.97% for June 2021, 3.08% for August 2022, 64.8% for June 2023. It is a modelled figure derived from the rows, not a statement of anyone's realised account balance.
The second column swings far harder than the first because it compounds volume. A month with a modest average return and 2,522 orders looks very different from one with the same average and 400. That is arithmetic, not skill, and reading it as skill is the most common mistake made with any published record.
Longs, shorts and how many symbols were traded
Every row carries a direction, and the direction mix is uncomfortable in a way worth flagging.
The record is heavily long. September 2021 is 1,181 longs against 23 shorts. May 2022 is 1,963 against 111. January 2024 is 2,288 against 290. The one clearly short-side month in the whole series is July 2021, at 373 shorts to 152 longs. A record built mostly from long exposure has not been stress-tested equally in both directions, and you should weigh it accordingly.
Symbol coverage widens steadily across the series: 99 distinct symbols in June 2021, 138 by April 2022, 194 by August 2023, 245 by January 2024. The signals come from a model that evaluates 240+ indicators, formulas and components across 500+ Binance USDT-M perpetual pairs, and the sheets show that breadth arriving gradually rather than being claimed up front. If perpetual futures are new to you, crypto futures trading for beginners covers the instrument these rows are denominated in.
Why your own result would not have matched the sheet
This section exists because the alternative is letting you assume something we know to be false. The record is a record of signals, not of accounts. Between the two sit at least six things:
- Entry timing. A row's entry is the price at the moment of sending. Yours is the price at the moment you acted.
- The free-channel delay. The free channel — 3,940 members as of 6 September 2026 — carries the same signals 20 minutes later. Twenty minutes is a long time in a perpetual futures market.
- Fills and slippage. Thin books and fast moves mean the price you see and the price you get are two different numbers.
- Fees and funding. Neither is in the per-order return column. Both are real, and on high-volume months they are not small.
- Sizing. The 1%-sizing column is a model. If you sized differently, took some signals and skipped others, or ran higher leverage, your result diverges immediately and permanently.
- Selection. Nobody takes every signal in a 2,500-order month. The subset you took is your track record, not ours.
None of that makes the file less true. It makes it a different measurement from your account statement, and the honest framing is that the record tells you about the signals, while risk management tells you what happens to your money.
How a sceptic can audit the whole thing
You do not need our cooperation to check this, which is the point of publishing it.
- Download. Take the monthly files from /reports. They are static; nothing is generated on request.
- Count rows. Recompute the month's rate from the rows rather than trusting the header. Wins over total.
- Recompute strictly. Apply the live page's rule instead. In these files it changes nothing, because there are no expiries to reclassify — which is itself the finding.
- Spot-check. Pick ten rows at random and check the symbol, direction and timestamp against exchange price history for that date.
- Compare. Set the result beside the live performance page, and watch the free channel for a fortnight to see whether what arrives resembles what is recorded.
Step four is the one that separates a real record from a manufactured one, and it takes about an hour. If you are evaluating anyone else in this category, the legitimacy checks for Telegram trading bots is the version of this process aimed at a provider who has published nothing.
What we do not publish, and why
We publish outcomes. We do not publish the recipe. There is no indicator list, no weighting scheme, no trigger logic anywhere in the sheets or on this site, and there will not be — a signal model that is fully described is a signal model that has been given away.
That is a genuine limitation for the reader and we will not pretend otherwise: you cannot inspect the process, only the results. Our answer is to make the results as inspectable as possible instead — a fixed file per month, a live page rebuilt hourly on stricter rules, and a free channel where the signals arrive in public before anyone pays for anything. Whether AI trading bots actually work is the broader version of that argument.
What changed after February 2024
The monthly spreadsheet series ends there. It was a manual process, and it stopped being the best available evidence once the trade database could be queried directly. The gap between February 2024 and June 2026 is not covered by either record, and we would rather say so than backfill it.
What replaced it is stricter in every respect that matters: hourly regeneration instead of monthly publication, three outcome categories instead of two, expiries counted against the rate rather than omitted, and open positions shown as open. Losing months will appear on that page when they happen, because nothing filters them out.
None of this is investment advice, and no track record is a forecast. Leveraged crypto trading can take the entire deposit, so trade only what you can afford to lose — and treat a published record, ours included, as a reason to look harder rather than a reason to stop looking.
Frequently asked questions
How many crypto signals has HafizeBot published? The monthly spreadsheets covering June 2021 to February 2024 contain 33,694 orders across 33 files, of which 33,095 are recorded as wins and 599 as losses. Since June 2026 the live performance page has counted several thousand broadcast signals per month, rebuilt hourly from the trade database.
Why is the historical hit rate higher than the live one? Because they are computed differently. The spreadsheets resolved every order as either a win or a loss, with no expiry category at all. The live page adds a third outcome — maximum hold reached with neither target nor stop — and counts it against the rate. The same month can read 100% under the first rule and 88.3% under the second.
What was the worst month in the record? June 2021, at 92.4%: 409 orders with 31 losses. The next weakest are September 2021 at 93.5% on 1,204 orders, August 2022 at 93.6%, and September 2022 at 94.1%. All four are published in full alongside the better months.
Can I verify the track record myself? Yes, and without asking us. The monthly files are downloadable, so you can count the rows, recompute the rate under whichever definition you prefer, and check individual entries against exchange price history for the date on the row. The live page can be compared against the free channel in real time.
Would I have made the returns shown in the spreadsheets? No, and the sheets do not claim you would. They record signals, not accounts. Entry timing, fills, fees, funding, position sizing, the 20-minute delay on the free channel and the simple fact that nobody takes every signal all move a real result away from the file.
Why don't you publish the strategy behind the signals? Because a fully described model can be copied, and the value of the signals would go with it. The published ceiling is that the signals are AI-generated from a system evaluating 240+ indicators, formulas and components across 500+ Binance USDT-M perpetual pairs. Everything we can prove without giving it away is in the record instead.