REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / DMDmFhoNtLmishJ95W399tJ5RXAnK53Avn5jHpnFf6Kp
F
Behavioral Grade
F
7 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
DMDmFhoNtLmishJ95W399tJ5RXAnK53Avn5jHpnFf6Kp
At your current pace, your capital halves every 0.1 days.
Your brain cost you
19.7 SOL
$1.4k behavioral damage
Survival prob.
0%
505 wins to break even
Capital half-life
0.1d
Bleed rate
0.538 SOL/hr
Win rate
5.4%
Net P&L
33.0 SOL
Win rate
5.4%
Profit factor
0.01
Tokens
74
SOL in
36.3
SOL out
3.326
Primary
Diagnosis
59% 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.
59%
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.
+19.7 SOL
Catchable Losses
35 / 70
Behavioral Drag
59%
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
70 losses
Fast re-entry
12x
Bigger size
6 tokens
Late entry
Held collapse
511x hold
Stages Fired
4 / 5
Fast Re-entries
12x
BEHAVIORAL DAMAGE REPORT
📈
Averaging Down
-11.1 SOL($811.80)
6 tokens where later buys were 2.2x larger
Later buys on losing positions
Late Night Trading
-6.232 SOL($456.51)
18 trades between 11PM–5AM
Best hours: 2AM
💎
Diamond Hand Delusion
-5.476 SOL($401.17)
Held losers 511x longer than winners
Winners: <1m · Losers: 4.2h
😴
Session Fatigue
-4.001 SOL($293.08)
After trade #11, avg P&L drops to -0.3637 SOL
Trade #1 avg: -0.2531 SOL
😤
Revenge Trading
-3.148 SOL($230.59)
12 trades within 10 min of a loss
Win rate on these: 8%
TOTAL BEHAVIORAL DRAG
-29.9 SOL($2.2k)
CIRCADIAN PROFILE
WORST: 10AM
12a7
1a3
2a1
4a1
10a1
11a4
12p9
1p10
2p8
3p9
4p2
7p1
8p5
9p3
10p4
11p6
Night (11PM–5AM): -0.3462 SOL/trade · Day (8AM–8PM): -0.4451 SOL/trade
DISPOSITION EFFECT
511x
WINNER HOLD
<1m
LOSER HOLD
4.2h
You hold losers 511x longer than winners. This is extreme. Cut losers faster.
SESSION FATIGUE
22 SESSIONS
#1
-0.2531
#2
-0.6404
#3
-0.5454
#4
-0.6866
#5
-0.4712
#6
-0.2734
#7
-0.7011
#8
-0.1318
Avg session: 3.4 trades. Dominant pattern: Loss from the Start (88%)
POST-LOSS VELOCITY
NORMAL
POST-LOSS GAP
33m
BASELINE GAP
33m
12 trades opened within 10 min of a loss. Loss rate on these: 92%
EQUITY CURVE
DISCIPLINED: +19.7 SOL
Peak: +0.422 SOL at token #1
Max drawdown: 32.5 SOL
- - - = you without 35 behavioral trades
P&L SUMMARY
ADVANCED METRICS
LOSS CONCENTRATION
DEX ANALYSIS
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 41.7 SOL (125% of total losses)
1
STOP BUYING ON PUMP_FUN
66 tokens from PUMP_FUN: 0% WR, -32.055 SOL net
→ Would save ~19.2 SOL
2
NEVER ADD TO A LOSING POSITION
Later buys on losers are 2.2x larger than first buy
→ Would save ~8.315 SOL
3
DON'T TRADE 10AM–1PM
Late-night avg: -0.3462 SOL vs -0.4451 daytime
→ Would save ~6.232 SOL
4
AVOID TRADING ON WEDS
WED avg: -0.5218 SOL across 13 trades
→ Would save ~4.749 SOL
5
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 92% vs 95% baseline
→ Would save ~3.148 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.
3khi...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
1.946 SOL
-100.0%
6.0/10
Full autopsy →
3giB...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
1.572 SOL
-100.0%
7.0/10
Full autopsy →
A4Qf...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
1.408 SOL
-100.0%
5.0/10
Full autopsy →
8ftd...pump
Never sold. Still holding. Still hoping.
The Bag Holder
1.020 SOL
-100.0%
7.0/10
Full autopsy →
7w9p...pump
Token went to zero. Wallet went to therapy.
The Rug Victim
0.984 SOL
-100.0%
5.0/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.