REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 55mMJZbAgBNXhtexmCBsXSaSD9SPCMXn9ey2gKgsipYm
F
Behavioral Grade
F
25 / 100
Wallet Death Certificate
At your current pace, your capital halves every 0.1 days.
55mMJZbAgBNXhtexmCBsXSaSD9SPCMXn9ey2gKgsipYm
60% of your losses are behavioral — not bad picks, bad habits. That's 418.739 SOL.
Your brain cost you
418.7 SOL
≈ $30.7k behavioral damage
Survival prob.
0%
218 wins to break even
Capital half-life
0.1d
Bleed rate
3.220 SOL/hr
Win rate
2.8%
Net P&L
−649.6 SOL
Win rate
2.8%
Profit factor
0.07
Tokens
613
SOL in
817.2
SOL out
167.6
Primary
Diagnosis
60% of attributed damage came from recurring behavior, not market noise — tilt, sizing, timing.
§ 03 · Compound Intelligence
THE NUMBERS THAT MATTER.
Avoidable Loss Score
Most losses were behavioral, not random.
60%
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.
+418.7 SOL
Catchable Losses
297 / 595
Behavioral Drag
60%
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
595 losses
→
Fast re-entry
212x
→
Bigger size
31 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
212x
BEHAVIORAL DAMAGE REPORT
😤
Revenge Trading
-227.5 SOL($16.7k)
212 trades within 10 min of a loss
Win rate on these: 2%
😴
Session Fatigue
-226.4 SOL($16.6k)
After trade #24, avg P&L drops to -2.3954 SOL
Trade #1 avg: -1.0168 SOL
⏰
Late Night Trading
-132.3 SOL($9.7k)
99 trades between 11PM–5AM
Best hours: 12PM
📈
Averaging Down
-110.1 SOL($8.1k)
31 tokens where later buys were 3.1x larger
Later buys on losing positions
TOTAL BEHAVIORAL DRAG
-696.3 SOL($51.0k)
CIRCADIAN PROFILE
WORST: 2AM▾
12a42
1a25
2a4
8a1
9a1
10a17
11a33
12p36
1p38
2p46
3p59
4p63
5p37
6p47
7p41
8p32
9p34
10p29
11p28
Night (11PM–5AM): -1.3368 SOL/trade · Day (8AM–8PM): -1.007 SOL/trade
DISPOSITION EFFECT
0.1x▾
WINNER HOLD
22.7h
LOSER HOLD
2.8h
You hold losers 0.1x longer than winners.
SESSION FATIGUE
189 SESSIONS▾
#1
-1.0168
#2
-0.8853
#3
-0.9906
#4
-1.1444
#5
-1.1469
#6
-1.0892
#7
-1.6027
#8
-1.2071
Avg session: 3.2 trades. Dominant pattern: Loss from the Start (88%)
POST-LOSS VELOCITY
1.1x FASTER▾
POST-LOSS GAP
14m
BASELINE GAP
15m
212 trades opened within 10 min of a loss. Loss rate on these: 98%
EQUITY CURVE
DISCIPLINED: +418.7 SOL▾
Peak: +0.0000 SOL at token #1
Max drawdown: 649.6 SOL
- - - = you without 297 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 937.6 SOL (134% of total losses)
1
STOP BUYING ON PUMP_FUN
586 tokens from PUMP_FUN: 2% WR, -634.813 SOL net
→ Would save ~380.9 SOL
2
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 98% vs 97% baseline
→ Would save ~227.5 SOL
3
DON'T TRADE 2AM–5AM
Late-night avg: -1.3368 SOL vs -1.007 daytime
→ Would save ~132.3 SOL
4
NEVER ADD TO A LOSING POSITION
Later buys on losers are 3.1x larger than first buy
→ Would save ~121.8 SOL
5
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 1.343 SOL vs 1.090 after win (1.23x)
→ Would save ~75.0 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.
GDea...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−10.2 SOL
-100.0%
6.0/10
Full autopsy →
69JL...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−9.920 SOL
-99.2%
7.0/10
Full autopsy →
Brbz...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−6.948 SOL
-100.0%
8.0/10
Full autopsy →
HWYy...VyL6
Token went to zero. Wallet went to therapy.
The Rug Victim
−5.003 SOL
-100.0%
6.0/10
Full autopsy →
EV35...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−4.707 SOL
-100.0%
5.0/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.