REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / HpUQBdJmPXQtPsSniyUyf5qFMZT61rwx5SsQKUZE1KDb
F
Behavioral Grade
F
25 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
HpUQBdJmPXQtPsSniyUyf5qFMZT61rwx5SsQKUZE1KDb
At your current pace, your capital halves every 0.1 days.
Your brain cost you
102.4 SOL
≈ $8.1k behavioral damage
Survival prob.
0%
56 wins to break even
Capital half-life
0.1d
Bleed rate
0.345 SOL/hr
Win rate
24.7%
Net P&L
−60.1 SOL
Win rate
24.7%
Profit factor
0.68
Tokens
482
SOL in
782.3
SOL out
722.2
Primary
Diagnosis
54% of attributed damage came from recurring behavior, not market noise — sizing, timing, tilt.
§ 03 · Compound Intelligence
THE NUMBERS THAT MATTER.
Avoidable Loss Score
Most losses were behavioral, not random.
54%
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.
+102.4 SOL
Catchable Losses
165 / 363
Behavioral Drag
54%
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
363 losses
→
Fast re-entry
79x
→
Bigger size
7 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
79x
BEHAVIORAL DAMAGE REPORT
😴
Session Fatigue
-44.3 SOL($3.5k)
After trade #16, avg P&L drops to -0.6822 SOL
Trade #1 avg: -0.2775 SOL
📈
Averaging Down
-41.6 SOL($3.3k)
7 tokens where later buys were 1.5x larger
Later buys on losing positions
😤
Revenge Trading
-25.2 SOL($2.0k)
79 trades within 10 min of a loss
Win rate on these: 18%
⏰
Late Night Trading
-2.827 SOL($222.39)
114 trades between 11PM–5AM
Best hours: 6AM
TOTAL BEHAVIORAL DRAG
-114.0 SOL($9.0k)
CIRCADIAN PROFILE
WORST: 8PM▾
12a25
1a18
2a17
3a27
4a20
5a17
6a14
7a17
8a9
9a11
10a16
11a23
12p42
1p33
2p37
3p34
4p21
5p18
6p20
7p13
8p9
9p16
10p18
11p7
Night (11PM–5AM): -0.0248 SOL/trade · Day (8AM–8PM): -0.1757 SOL/trade
DISPOSITION EFFECT
0.5x▾
WINNER HOLD
22.7h
LOSER HOLD
12.0h
You hold losers 0.5x longer than winners.
SESSION FATIGUE
130 SESSIONS▾
#1
-0.2775
#2
+0.106
#3
-0.0755
#4
-0.1589
#5
-0.4199
#6
-0.2565
#7
+0.2179
#8
-0.2562
Avg session: 3.7 trades. Dominant pattern: Loss from the Start (45%)
POST-LOSS VELOCITY
1.1x FASTER▾
POST-LOSS GAP
21m
BASELINE GAP
23m
79 trades opened within 10 min of a loss. Loss rate on these: 82%
EQUITY CURVE
DISCIPLINED: +102.4 SOL▾
Peak: +0.848 SOL at token #3
Max drawdown: 59.3 SOL
- - - = you without 165 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 174.2 SOL (92% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 1.5x larger than first buy
→ Would save ~90.6 SOL
2
STOP BUYING ON PUMP_AMM
434 tokens from PUMP_AMM: 26% WR, -50.686 SOL net
→ Would save ~30.4 SOL
3
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 82% vs 75% baseline
→ Would save ~25.2 SOL
4
STOP AFTER 3 TRADES PER SESSION
Trade #1 avg: -0.2775 SOL → Trade #16 avg: -0.6822 SOL
→ Would save ~18.2 SOL
5
AVOID TRADING ON THUS
THU avg: -0.3475 SOL across 40 trades
→ Would save ~9.731 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.
Dw5p...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−3.086 SOL
-42.6%
3.5/10
Full autopsy →
oqmD...pump
Watched it die slowly and did nothing.
The Slow Bleeder
−2.954 SOL
-91.6%
4.0/10
Full autopsy →
7EvF...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−2.713 SOL
-39.3%
3.5/10
Full autopsy →
EWBz...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−2.680 SOL
-86.8%
5.0/10
Full autopsy →
B9NU...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−2.423 SOL
-54.7%
4.5/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.