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FACTS, NOT ADVICE

Your Trade Reality Report

A factual reconstruction of your real trading results — after every real cost.
PeriodJan 2023 – Jun 2026
Fills analyzed5,154
Closed trades2,287
Win rate42%
Notional traded$1.97M
–$46,550
REAL NET RESULT — after real fees and slippage, across 2,287 closed trades
You don’t have a selection problem. You have an exit problem.
Your picks earned +$48,735. Your exits gave back –$95,285.
A 42% win rate feels survivable — and in your best names you win 79–100% of the time. The reality is a six-figure round-trip into a deep loss. This report shows exactly where it went.
Layer 1 · Hidden Cost

What the costs actually were

The surprise isn’t fees or slippage — those are tiny. The cost that matters doesn’t show up on any statement: it’s the gap created by how trades were exited.

–$1,480
Real trading fees (0.07% of notional)
–$744
Slippage, book-walk (0.038%) · lower bound
–$45,070
Gross P&L before costs
–$46,550
Real net result
Fees + slippage together are under 5% of the damage. The execution is fine. The decisions are not.
Layer 2 · Decision Audit

Selection vs. exit

Split every closed trade into what your winners earned and what your losers gave back. The asymmetry is the whole story.

+$48,735
Selection edge — total earned on winning trades
winners
Avg winner +$50.55 · avg capital staked $293
–$95,285
Exit gap — total given back on losing trades
losers
Avg loser –$72.02 · avg capital staked $438 (1.5× bigger)
You stake 1.5× more capital on losers than winners — so the trades most likely to be held down are also the largest. Two mistakes compounding.
Layers 3 & 4 · Error Memory + Personal Encyclopedia

The patterns in your trading

Each pattern below is detected from your own fills and rated by how much of your data supports it. Confirmed = 15+ trades and a strong effect.

PAYOFF-ASYMMETRYConfirmed

Disposition effect — small wins, big losses

Average win far smaller than average loss, so even a high win rate loses money.
At a 42% win rate you’d need to average ≥1.37 in win-per-loss to break even. You average 0.70.
CATASTROPHIC-TAILConfirmed

Catastrophic losses — no downside cap

A small number of trades allowed to fall past –30% do outsized damage.
257 trades worse than –30% lost –$41,609 — more than your entire net result.
HELD-TO-ZEROConfirmed

Names with zero wins

Assets traded repeatedly without a single profitable exit — held down rather than cut.
26 assets had 0 winning closes (e.g. W, SOMI, CAKE, LINK).
REPEAT-LOSSConfirmed

Returning to losing names

Names closed at a loss three or more times and still net-negative — re-entering what keeps costing you.
48 names lost ≥3 times and stayed negative. Worst: SLP –$10,818 across 172 trades (1% win rate).
CUT-WINNERS-EARLYConfirmed

Winners closed small

Winners taken at a small gain while losers run further than winners.
Median winner +10.8% vs median loser –12.4% — you let losers travel further than winners.
LOSS-CONCENTRATIONProbable

Loss concentrated in a few names

Most damage from a handful of assets, not broad bleed.
Top-5 losing names = –$28,251 (61% of net).
These entries are the seed of your personal trading encyclopedia. Anonymized, the same taxonomy feeds Isnadia’s collective Failure Encyclopedia — one spine, two failure layers.
Layer 2 · The Decision Gap

The price of one missing rule

Because price is continuous, a trade that closed at –50% did trade through –10% on the way down. So we can ask, soundly from your own data: what if a downside cap had been in place?

+$52,496

A simple –10% stop would have turned your –$46,550 into +$5,945. Same entries, same picks — one rule. That swing is the cost of decisions, not the market.

Actual
–$46,550
–30%
–$34,702
–20%
–$19,985
–15%
–$8,635
–10%
+$5,945
Caveats: winners are left untouched (no intrabar peak data, so no claim you “could have held longer”); stops are applied only where the trade actually closed below the level. This is a directional lower bound, not a wick-accurate backtest.
Reality Gap · Over time

Year by year — and the tell

Your one profitable year is the year you traded least. Activity and losses move together.

2023 · 904 trades · 45%
–$5,937
2024 · 97 trades · 42%
+$1,167
2025 · 944 trades · 34%
–$30,756
2026 · 342 trades · 56%
–$11,024
2024: 97 trades, the only green year. 2025: 944 trades, lowest win rate, your worst year by far. More clicks, more damage.
Where it concentrates

Best and worst names

Top winnersWin%Net
XRP79+$9,165
DOGE100+$2,458
TRU100+$1,845
NEAR100+$1,121
VOXEL100+$880
PROS100+$736
Worst losersWin%Net
SLP1–$10,818
SUI36–$4,851
TWT44–$4,311
DASH19–$4,293
APT23–$3,976
AVAX20–$3,974
How this was built

Methodology & honesty

Reconstructed from your real Binance spot trade-history exports — 5,154 unique fills, merged and de-duplicated, matched into 2,287 closed long round-trips by FIFO.

What is real

  • Fees — taken directly from your exports, converted to USDT.
  • Net, gross, ROI, win rate — computed from your actual fills.
  • Slippage (–$744) — measured from your own fills (book-walk within each order). A true lower bound.
  • Stop-loss counterfactual — sound because price is continuous: a trade that closed below a level necessarily traded through it.

What is not claimed

  • Slippage vs the market mid (the spread you paid on arrival) needs an external reference price, which was not available — so true slippage is somewhat higher than –$744.
  • Winners are never altered; we make no claim you could have held them longer.
  • Pre-existing holdings sold without a matching buy in the data are excluded.
  • This report contains no advice, signals, or predictions — only what already happened, with evidence.
Isnadia · Trade Reality Engine — Personal Reality Report
Generated 14 Jun 2026 · Facts, not advice