REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 5dbuE3zrhcutzf9vJQKZ6ntZBV4QCh19kFnqrrQK2mWt
F
Behavioral Grade
F
20 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
5dbuE3zrhcutzf9vJQKZ6ntZBV4QCh19kFnqrrQK2mWt
At your current pace, your capital halves every 0.5 days.
Your brain cost you
282.0 SOL
≈ $21.9k behavioral damage
Survival prob.
0%
200 wins to break even
Capital half-life
0.5d
Bleed rate
0.223 SOL/hr
Win rate
15.9%
Net P&L
−342.2 SOL
Win rate
15.9%
Profit factor
0.2
Tokens
320
SOL in
1.1k
SOL out
763.9
Primary
Diagnosis
66% of attributed damage came from recurring behavior, not market noise — sizing, tilt, timing.
§ 03 · Compound Intelligence
THE NUMBERS THAT MATTER.
Avoidable Loss Score
Most losses were behavioral, not random.
66%
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.
+282.0 SOL
Catchable Losses
149 / 269
Behavioral Drag
66%
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
269 losses
→
Fast re-entry
86x
→
Bigger size
28 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
86x
BEHAVIORAL DAMAGE REPORT
😴
Session Fatigue
-210.0 SOL($16.3k)
After trade #10, avg P&L drops to -4.2415 SOL
Trade #1 avg: -0.897 SOL
📈
Averaging Down
-120.5 SOL($9.4k)
28 tokens where later buys were 3.7x larger
Later buys on losing positions
😤
Revenge Trading
-106.1 SOL($8.2k)
86 trades within 10 min of a loss
Win rate on these: 9%
⏰
Late Night Trading
-50.4 SOL($3.9k)
57 trades between 11PM–5AM
Best hours: 10AM
TOTAL BEHAVIORAL DRAG
-487.0 SOL($37.9k)
CIRCADIAN PROFILE
WORST: 3AM▾
12a10
1a12
2a8
3a10
4a5
5a9
6a11
7a14
8a14
9a15
10a11
11a13
12p26
1p28
2p19
3p22
4p17
5p21
6p8
7p2
8p9
9p8
10p16
11p12
Night (11PM–5AM): -0.885 SOL/trade · Day (8AM–8PM): -1.1191 SOL/trade
DISPOSITION EFFECT
0.6x▾
WINNER HOLD
12.2h
LOSER HOLD
7.9h
You hold losers 0.6x longer than winners.
SESSION FATIGUE
99 SESSIONS▾
#1
-0.897
#2
-1.6897
#3
-0.9044
#4
-1.2399
#5
-1.217
#6
+0.2539
#7
+0.255
#8
-0.3434
Avg session: 3.2 trades. Dominant pattern: Loss from the Start (58%)
POST-LOSS VELOCITY
1.1x FASTER▾
POST-LOSS GAP
15m
BASELINE GAP
17m
86 trades opened within 10 min of a loss. Loss rate on these: 91%
EQUITY CURVE
DISCIPLINED: +282.0 SOL▾
Peak: +2.066 SOL at token #1
Max drawdown: 344.3 SOL
- - - = you without 149 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 676.9 SOL (157% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 3.7x larger than first buy
→ Would save ~302.3 SOL
2
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 91% vs 84% baseline
→ Would save ~106.1 SOL
3
STOP BUYING ON JUPITER
84 tokens from JUPITER: 1% WR, -175.891 SOL net
→ Would save ~105.5 SOL
4
STOP AFTER 3 TRADES PER SESSION
Trade #1 avg: -0.897 SOL → Trade #10 avg: -4.2415 SOL
→ Would save ~103.7 SOL
5
AVOID TRADING ON SUNS
SUN avg: -1.434 SOL across 59 trades
→ Would save ~59.2 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.
9asC...BAGS
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−10.7 SOL
-75.1%
4.5/10
Full autopsy →
CQo4...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−10.1 SOL
-60.2%
4.5/10
Full autopsy →
GfqY...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−8.733 SOL
-50.1%
4.5/10
Full autopsy →
jnwN...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−7.517 SOL
-93.1%
6.0/10
Full autopsy →
Dm9d...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−7.447 SOL
-63.6%
3.5/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.