REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 9Qdo7PmW8pfZ5tAoGeDGrkcGrskgsBVwfsUUcED3s6z2
F
Behavioral Grade
F
15 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
9Qdo7PmW8pfZ5tAoGeDGrkcGrskgsBVwfsUUcED3s6z2
At your current pace, your capital halves every 0.3 days.
Your brain cost you
1.1k SOL
≈ $85.5k behavioral damage
Survival prob.
0%
293 wins to break even
Capital half-life
0.3d
Bleed rate
2.376 SOL/hr
Win rate
28.7%
Net P&L
−1.4k SOL
Win rate
28.7%
Profit factor
0.26
Tokens
363
SOL in
3.2k
SOL out
1.9k
Primary
Diagnosis
60% 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.
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.
+1.1k SOL
Catchable Losses
111 / 257
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
257 losses
→
Fast re-entry
56x
→
Bigger size
23 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
56x
BEHAVIORAL DAMAGE REPORT
😴
Session Fatigue
-690.4 SOL($53.8k)
After trade #9, avg P&L drops to -9.3936 SOL
Trade #1 avg: -2.1854 SOL
📈
Averaging Down
-670.0 SOL($52.2k)
23 tokens where later buys were 74.8x larger
Later buys on losing positions
😤
Revenge Trading
-221.0 SOL($17.2k)
56 trades within 10 min of a loss
Win rate on these: 12%
⏰
Late Night Trading
-219.2 SOL($17.1k)
40 trades between 11PM–5AM
Best hours: 12AM
TOTAL BEHAVIORAL DRAG
-1.8k SOL($140.3k)
CIRCADIAN PROFILE
WORST: 1AM▾
12a2
1a3
2a3
3a3
4a3
5a10
6a16
7a19
8a14
9a8
10a9
11a10
12p12
1p8
2p9
3p6
4p13
5p20
6p12
7p24
8p32
9p59
10p42
11p26
Night (11PM–5AM): -5.4797 SOL/trade · Day (8AM–8PM): -3.7005 SOL/trade
DISPOSITION EFFECT
1.4x▾
WINNER HOLD
1.8d
LOSER HOLD
2.5d
You hold losers 1.4x longer than winners.
SESSION FATIGUE
147 SESSIONS▾
#1
-2.1854
#2
-4.8593
#3
-4.24
#4
-3.9745
#5
-2.9114
#6
-9.1355
#7
-8.3329
#8
-1.6128
Avg session: 2.5 trades. Dominant pattern: Loss from the Start (42%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
49m
BASELINE GAP
43m
56 trades opened within 10 min of a loss. Loss rate on these: 88%
EQUITY CURVE
DISCIPLINED: +1.1k SOL▾
Peak: +11.7 SOL at token #1
Max drawdown: 1.4k SOL
- - - = you without 111 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 2.6k SOL (141% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 74.8x larger than first buy
→ Would save ~1.1k SOL
2
STOP BUYING ON JUPITER
142 tokens from JUPITER: 6% WR, -914.839 SOL net
→ Would save ~548.9 SOL
3
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 10.014 SOL vs 6.021 after win (1.66x)
→ Would save ~511.0 SOL
4
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 88% vs 71% baseline
→ Would save ~221.0 SOL
5
DON'T TRADE 1AM–4AM
Late-night avg: -5.4797 SOL vs -3.7005 daytime
→ Would save ~219.2 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.
4TyZ...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−78.8 SOL
-18.9%
4.5/10
Full autopsy →
Aydq...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−61.5 SOL
-83.3%
6.0/10
Full autopsy →
GvQH...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−48.7 SOL
-72.5%
4.5/10
Full autopsy →
EKwF...kecG
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−46.9 SOL
-12.3%
4.5/10
Full autopsy →
C9TH...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−36.7 SOL
-64.4%
4.5/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.