REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 9habhUzBciheRCouTfLEwjZsJU2XuK5DSwXrStsrrLXX
F
Behavioral Grade
F
20 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
9habhUzBciheRCouTfLEwjZsJU2XuK5DSwXrStsrrLXX
At your current pace, your capital halves every 0 days.
Your brain cost you
667.0 SOL
≈ $51.9k behavioral damage
Survival prob.
0%
112 wins to break even
Capital half-life
0d
Bleed rate
2.845 SOL/hr
Win rate
6.6%
Net P&L
−615.3 SOL
Win rate
6.6%
Profit factor
0.25
Tokens
580
SOL in
1.2k
SOL out
613.2
Primary
Diagnosis
81% 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.
81%
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.
+667.0 SOL
Catchable Losses
421 / 540
Behavioral Drag
81%
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
540 losses
→
Fast re-entry
368x
→
Bigger size
16 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
368x
BEHAVIORAL DAMAGE REPORT
😤
Revenge Trading
-491.4 SOL($38.2k)
368 trades within 10 min of a loss
Win rate on these: 5%
⏰
Late Night Trading
-137.3 SOL($10.7k)
130 trades between 11PM–5AM
Best hours: 9AM
📈
Averaging Down
-101.2 SOL($7.9k)
16 tokens where later buys were 2.9x larger
Later buys on losing positions
😴
Session Fatigue
-37.3 SOL($2.9k)
After trade #58, avg P&L drops to -1.6224 SOL
Trade #1 avg: -1.0235 SOL
TOTAL BEHAVIORAL DRAG
-767.3 SOL($59.7k)
CIRCADIAN PROFILE
WORST: 2PM▾
12a20
1a17
2a23
3a18
4a21
5a25
6a25
7a26
8a21
9a9
10a13
11a7
12p23
1p27
2p15
3p24
4p41
5p26
6p31
7p26
8p35
9p37
10p39
11p31
Night (11PM–5AM): -1.0565 SOL/trade · Day (8AM–8PM): -1.0508 SOL/trade
DISPOSITION EFFECT
0.2x▾
WINNER HOLD
7.8h
LOSER HOLD
1.6h
You hold losers 0.2x longer than winners.
SESSION FATIGUE
46 SESSIONS▾
#1
-1.0235
#2
-1.1113
#3
-0.7363
#4
+0.1837
#5
-0.5204
#6
-0.9199
#7
-1.0873
#8
-1.3721
Avg session: 12.6 trades. Dominant pattern: Loss from the Start (87%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
3m
BASELINE GAP
3m
368 trades opened within 10 min of a loss. Loss rate on these: 95%
EQUITY CURVE
DISCIPLINED: +667.0 SOL▾
Peak: +0.282 SOL at token #1
Max drawdown: 626.4 SOL
- - - = you without 421 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 1.3k SOL (162% of total losses)
1
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 95% vs 93% baseline
→ Would save ~491.4 SOL
2
STOP BUYING ON PUMP_FUN
537 tokens from PUMP_FUN: 5% WR, -605.840 SOL net
→ Would save ~363.5 SOL
3
NEVER ADD TO A LOSING POSITION
Later buys on losers are 2.9x larger than first buy
→ Would save ~239.6 SOL
4
DON'T TRADE 2PM–5PM
Late-night avg: -1.0565 SOL vs -1.0508 daytime
→ Would save ~137.3 SOL
5
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 2.145 SOL vs 1.759 after win (1.22x)
→ Would save ~103.9 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.
2HtH...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−9.878 SOL
-43.1%
4.5/10
Full autopsy →
ETZK...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−9.595 SOL
-60.1%
4.5/10
Full autopsy →
2vZE...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
−9.109 SOL
-100.0%
8.0/10
Full autopsy →
CUfx...pump
Panic sold within minutes. Fear won.
The Paper Hand
−8.945 SOL
-44.9%
3.5/10
Full autopsy →
8Akt...pump
Rug pull. Panic averaging. Mathematical inevitability.
The Rug Victim
−7.920 SOL
-100.0%
7.0/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.