REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 6A7mFK47LB8WGkrUpZh8dw32s5R3ATGSHLduKAxZx536
F
Behavioral Grade
F
7 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
6A7mFK47LB8WGkrUpZh8dw32s5R3ATGSHLduKAxZx536
At your current pace, your capital halves every 10 days.
Your brain cost you
443.0 SOL
≈ $34.5k behavioral damage
Survival prob.
0%
91 wins to break even
Capital half-life
10d
Bleed rate
0.502 SOL/hr
Win rate
22.5%
Net P&L
−436.5 SOL
Win rate
22.5%
Profit factor
0.17
Tokens
80
SOL in
674.3
SOL out
237.8
Primary
Diagnosis
85% 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.
85%
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.
+443.0 SOL
Catchable Losses
27 / 60
Behavioral Drag
85%
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
60 losses
→
Fast re-entry
3x
→
Bigger size
11 tokens
→
Late entry
→
Held collapse
3.7x hold
Stages Fired
4 / 5
Fast Re-entries
3x
BEHAVIORAL DAMAGE REPORT
📈
Averaging Down
-427.4 SOL($33.2k)
11 tokens where later buys were 11440.6x larger
Later buys on losing positions
💎
Diamond Hand Delusion
-9.937 SOL($772.86)
Held losers 3.7x longer than winners
Winners: 15.6d · Losers: 57.4d
⏰
Late Night Trading
-9.937 SOL($772.85)
3 trades between 11PM–5AM
Best hours: 5PM
😤
Revenge Trading
-5.681 SOL($441.88)
3 trades within 10 min of a loss
Win rate on these: 0%
TOTAL BEHAVIORAL DRAG
-452.9 SOL($35.2k)
CIRCADIAN PROFILE
WORST: 4PM▾
1a1
4a1
5a1
6a1
7a4
8a4
9a3
10a5
11a2
12p4
1p6
2p5
3p8
4p3
5p1
6p2
7p8
8p8
9p9
10p3
11p1
Night (11PM–5AM): -3.3122 SOL/trade · Day (8AM–8PM): -7.6787 SOL/trade
DISPOSITION EFFECT
3.7x▾
WINNER HOLD
15.6d
LOSER HOLD
57.4d
You hold losers 3.7x longer than winners. This is extreme. Cut losers faster.
SESSION FATIGUE
21 SESSIONS▾
#1
-2.3957
#2
-13.314
#3
-0.3367
#4
-0.3431
#5
-1.3514
#6
-2.1025
#7
-2.2238
#8
-48.1057
Avg session: 3.8 trades. Dominant pattern: Loss from the Start (40%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
12.3h
BASELINE GAP
8.3h
3 trades opened within 10 min of a loss. Loss rate on these: 100%
EQUITY CURVE
DISCIPLINED: +443.0 SOL▾
Peak: +17.4 SOL at token #1
Max drawdown: 419.0 SOL
- - - = you without 27 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 876.2 SOL (167% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 11440.6x larger than first buy
→ Would save ~277.1 SOL
2
CAP POSITIONS AT 4.214 SOL
6 oversized trades = 70% of total losses
→ Would save ~221.0 SOL
3
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 9.804 SOL vs 4.793 after win (2.05x)
→ Would save ~147.8 SOL
4
STOP BUYING ON DFLOW
23 tokens from DFLOW: 9% WR, -228.173 SOL net
→ Would save ~136.9 SOL
5
AVOID TRADING ON WEDS
WED avg: -11.114 SOL across 12 trades
→ Would save ~93.4 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.
9HHr...gLyu
Token went to zero. Wallet went to therapy.
The Rug Victim
−146.9 SOL
-96.1%
7.0/10
Full autopsy →
76ED...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−139.6 SOL
-90.6%
6.0/10
Full autopsy →
EPjF...Dt1v
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−23.6 SOL
-80.5%
5.0/10
Full autopsy →
Es9v...wNYB
Never sold. Still holding. Still hoping.
The Bag Holder
−22.7 SOL
-100.0%
8.0/10
Full autopsy →
EfPo...pump
Never sold. Still holding. Still hoping.
The Bag Holder
−18.0 SOL
-100.0%
7.0/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.