REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 8stkoPvHce7jrDsboybkkFK3KvR1wrvik721DURpxPa
F
Behavioral Grade
F
25 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
8stkoPvHce7jrDsboybkkFK3KvR1wrvik721DURpxPa
At your current pace, your capital halves every 0.1 days.
Your brain cost you
547.1 SOL
≈ $42.7k behavioral damage
Survival prob.
0%
35 wins to break even
Capital half-life
0.1d
Bleed rate
7.255 SOL/hr
Win rate
17.1%
Net P&L
−363.5 SOL
Win rate
17.1%
Profit factor
0.56
Tokens
263
SOL in
2.1k
SOL out
1.8k
Primary
Diagnosis
66% of attributed damage came from recurring behavior, not market noise — tilt, sizing, 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.
+547.1 SOL
Catchable Losses
133 / 218
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
218 losses
→
Fast re-entry
73x
→
Bigger size
9 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
73x
BEHAVIORAL DAMAGE REPORT
😤
Revenge Trading
-210.2 SOL($16.4k)
73 trades within 10 min of a loss
Win rate on these: 10%
😴
Session Fatigue
-204.8 SOL($16.0k)
After trade #21, avg P&L drops to -7.447 SOL
Trade #1 avg: -1.8509 SOL
📈
Averaging Down
-192.8 SOL($15.0k)
9 tokens where later buys were 3x larger
Later buys on losing positions
⏰
Late Night Trading
-84.4 SOL($6.6k)
74 trades between 11PM–5AM
Best hours: 4PM
TOTAL BEHAVIORAL DRAG
-692.2 SOL($54.0k)
CIRCADIAN PROFILE
WORST: 7AM▾
12a22
1a15
2a11
3a6
6a1
7a6
8a11
9a5
10a7
11a8
12p5
1p2
2p6
3p14
4p12
5p13
6p8
7p18
8p27
9p20
10p26
11p20
Night (11PM–5AM): -1.1402 SOL/trade · Day (8AM–8PM): -0.638 SOL/trade
DISPOSITION EFFECT
0.2x▾
WINNER HOLD
8.9h
LOSER HOLD
1.6h
You hold losers 0.2x longer than winners.
SESSION FATIGUE
55 SESSIONS▾
#1
-1.8509
#2
+0.8619
#3
-0.2903
#4
-1.4354
#5
-3.7287
#6
-2.8646
#7
+1.4613
#8
-0.4552
Avg session: 4.8 trades. Dominant pattern: Loss from the Start (50%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
8m
BASELINE GAP
9m
73 trades opened within 10 min of a loss. Loss rate on these: 90%
EQUITY CURVE
DISCIPLINED: +547.1 SOL▾
Peak: +6.662 SOL at token #1
Max drawdown: 370.1 SOL
- - - = you without 133 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 1.3k SOL (155% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 3x larger than first buy
→ Would save ~533.5 SOL
2
STOP BUYING ON PUMP_FUN
176 tokens from PUMP_FUN: 11% WR, -364.196 SOL net
→ Would save ~218.5 SOL
3
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 90% vs 83% baseline
→ Would save ~210.2 SOL
4
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 8.359 SOL vs 6.791 after win (1.23x)
→ Would save ~170.1 SOL
5
STOP AFTER 3 TRADES PER SESSION
Trade #1 avg: -1.8509 SOL → Trade #21 avg: -7.447 SOL
→ Would save ~162.3 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.
B3bJ...RCgC
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−24.4 SOL
-40.9%
4.5/10
Full autopsy →
CizT...iGZj
Token went to zero. Wallet went to therapy.
The Rug Victim
−19.6 SOL
-100.0%
7.0/10
Full autopsy →
EnqC...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−19.6 SOL
-34.8%
4.5/10
Full autopsy →
skDG...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−16.4 SOL
-47.3%
4.5/10
Full autopsy →
7qbS...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−13.9 SOL
-30.5%
4.5/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.