REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / BpaAw2jWQY5QJxg4cLYiJ99mch9gMcAw1xnsytPDoH7R
F
Behavioral Grade
F
20 / 100
Wallet Death Certificate
At your current pace, your capital halves every 0 days.
BpaAw2jWQY5QJxg4cLYiJ99mch9gMcAw1xnsytPDoH7R
86% of your losses are behavioral — not bad picks, bad habits. That's 751.161 SOL.
Your brain cost you
751.2 SOL
≈ $58.5k behavioral damage
Survival prob.
0%
342 wins to break even
Capital half-life
0d
Bleed rate
13.7 SOL/hr
Win rate
3.2%
Net P&L
−809.0 SOL
Win rate
3.2%
Profit factor
0.07
Tokens
750
SOL in
1.1k
SOL out
321.5
Primary
Diagnosis
87% of attributed damage came from recurring behavior, not market noise — tilt, timing, sizing.
§ 03 · Compound Intelligence
THE NUMBERS THAT MATTER.
Avoidable Loss Score
Most losses were behavioral, not random.
87%
BEHAVIOR-DRIVEN
NOISE

Estimated share of total attributed loss caused by repeatable actions: re-entry after loss, average-down escalation, and holding through terminal drawdown.

Recovered Perf.
+751.2 SOL
Catchable Losses
578 / 676
Behavioral Drag
87%
Behavioral Kill Chain
The repeatable sequence of destruction.

The autopsy does not just rank mistakes — it identifies the recurring sequence that converts a normal loss into a terminal drawdown.

Loss
676 losses
→
Fast re-entry
447x
→
Bigger size
38 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
447x
BEHAVIORAL DAMAGE REPORT
😤
Revenge Trading
-506.5 SOL($39.5k)
447 trades within 10 min of a loss
Win rate on these: 7%
⏰
Late Night Trading
-375.2 SOL($29.2k)
359 trades between 11PM–5AM
Best hours: 1PM
📈
Averaging Down
-77.3 SOL($6.0k)
38 tokens where later buys were 6.9x larger
Later buys on losing positions
😴
Session Fatigue
-48.6 SOL($3.8k)
After trade #73, avg P&L drops to -2.8608 SOL
Trade #1 avg: -1.0188 SOL
TOTAL BEHAVIORAL DRAG
-1.0k SOL($78.5k)
CIRCADIAN PROFILE
WORST: 10AM▾
12a80
1a66
2a43
3a44
4a61
5a19
6a12
7a22
8a21
9a20
10a9
11a8
12p6
1p25
2p5
3p34
4p62
5p48
6p25
7p14
8p4
9p25
10p32
11p65
Night (11PM–5AM): -1.0451 SOL/trade · Day (8AM–8PM): -1.1481 SOL/trade
DISPOSITION EFFECT
0.2x▾
WINNER HOLD
6.2h
LOSER HOLD
1.3h
You hold losers 0.2x longer than winners.
SESSION FATIGUE
34 SESSIONS▾
#1
-1.0188
#2
-1.1432
#3
-1.4778
#4
-1.031
#5
-1.2264
#6
-0.8148
#7
-1.1193
#8
-1.0706
Avg session: 22.1 trades. Dominant pattern: Loss from the Start (81%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
2m
BASELINE GAP
2m
447 trades opened within 10 min of a loss. Loss rate on these: 93%
EQUITY CURVE
DISCIPLINED: +751.2 SOL▾
Peak: +1.006 SOL at token #1
Max drawdown: 808.0 SOL
- - - = you without 578 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 1.7k SOL (197% of total losses)
1
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 93% vs 97% baseline
→ Would save ~506.5 SOL
2
STOP BUYING ON PUMP_FUN
652 tokens from PUMP_FUN: 0% WR, -821.491 SOL net
→ Would save ~492.9 SOL
3
DON'T TRADE 10AM–1PM
Late-night avg: -1.0451 SOL vs -1.1481 daytime
→ Would save ~375.2 SOL
4
NEVER ADD TO A LOSING POSITION
Later buys on losers are 6.9x larger than first buy
→ Would save ~198.6 SOL
5
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 1.548 SOL vs 1.147 after win (1.35x)
→ Would save ~135.1 SOL
Select a token for AI-narrated forensic analysis
Individual Token Autopsies
Forensic breakdown of 5 autopsied tokens — winners and losers. Open any for the full report, or trade directly.
41M3...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−10.5 SOL
-100.0%
8.0/10
Full autopsy →
GPwN...pump
Panic sold within minutes. Fear won.
The Paper Hand
−6.703 SOL
-73.1%
4.5/10
Full autopsy →
8vsM...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−5.868 SOL
-100.0%
8.0/10
Full autopsy →
2U52...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−5.582 SOL
-100.0%
7.0/10
Full autopsy →
8qBK...qh2W
Token went to zero. Wallet went to therapy.
The Rug Victim
−5.523 SOL
-100.0%
7.0/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.