REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / DYAn4XpAkN5mhiXkRB7dGq4Jadnx6XYgu8L5b3WGhbrt
D
Behavioral Grade
D
47 / 100
Wallet Autopsy Report
The math gives you a 99% chance of going to zero.
DYAn4XpAkN5mhiXkRB7dGq4Jadnx6XYgu8L5b3WGhbrt
At your current pace, your capital halves every 0.8 days.
Your brain cost you
635.6 SOL
$46.6k behavioral damage
Survival prob.
Capital half-life
0.8d
Bleed rate
4.060 SOL/hr
Win rate
33.7%
Net P&L
+253.3 SOL
Win rate
33.7%
Profit factor
1.32
Tokens
258
SOL in
1.5k
SOL out
1.8k
Primary
Diagnosis
80% of attributed damage came from recurring behavior, not market noise — timing, sizing, tilt.
§ 03 · Compound Intelligence
THE NUMBERS THAT MATTER.
Avoidable Loss Score
Most losses were behavioral, not random.
80%
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.
+635.6 SOL
Catchable Losses
71 / 139
Behavioral Drag
80%
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
139 losses
Fast re-entry
24x
Bigger size
2 tokens
Late entry
Held collapse
Stages Fired
3 / 5
Fast Re-entries
24x
BEHAVIORAL DAMAGE REPORT
Late Night Trading
-264.7 SOL($19.4k)
49 trades between 11PM–5AM
Best hours: 8AM
😴
Session Fatigue
-247.6 SOL($18.2k)
After trade #13, avg P&L drops to -4.9034 SOL
Trade #1 avg: +1.5373 SOL
📈
Averaging Down
-210.5 SOL($15.4k)
2 tokens where later buys were 1.6x larger
Later buys on losing positions
😤
Revenge Trading
-38.3 SOL($2.8k)
24 trades within 10 min of a loss
Win rate on these: 21%
🌀
Tilt Cascade
Each loss makes your next trade 5.5x worse
SPEED: 1.3x faster · FATIGUE: Trade #1: +1.5373 → #13: -4.9034
TOTAL BEHAVIORAL DRAG
-761.1 SOL($55.8k)
CIRCADIAN PROFILE
WORST: 1AM
12a13
1a10
2a10
3a2
4a2
5a12
6a26
7a11
8a8
9a4
10a2
11a1
1p1
3p2
4p4
5p13
6p22
7p26
8p23
9p20
10p34
11p12
Night (11PM–5AM): -5.4013 SOL/trade · Day (8AM–8PM): +1.0604 SOL/trade
DISPOSITION EFFECT
0.9x
WINNER HOLD
10.1h
LOSER HOLD
9.5h
You hold losers 0.9x longer than winners.
SESSION FATIGUE
101 SESSIONS
#1
+1.5373
#2
-1.5754
#3
+4.1367
#4
+1.5958
#5
-4.2446
#6
+11.4189
#7
-12.2026
#8
-0.9833
Avg session: 2.6 trades. Dominant pattern: Unpredictable (47%)
POST-LOSS VELOCITY
1.3x FASTER
POST-LOSS GAP
23m
BASELINE GAP
31m
24 trades opened within 10 min of a loss. Loss rate on these: 79%
EQUITY CURVE
DISCIPLINED: +635.6 SOL
Peak: +259.7 SOL at token #250
Max drawdown: 466.1 SOL
- - - = you without 71 behavioral trades
P&L SUMMARY
ADVANCED METRICS
LOSS CONCENTRATION
DEX ANALYSIS
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 1.1k SOL (142% of total losses)
1
CAP POSITIONS AT 2.994 SOL
14 oversized trades = 62% of total losses
→ Would save ~297.5 SOL
2
DON'T TRADE 1AM–4AM
Late-night avg: -5.4013 SOL vs +1.0604 daytime
→ Would save ~264.7 SOL
3
AVOID TRADING ON FRIS
FRI avg: -11.294 SOL across 30 trades
→ Would save ~237.2 SOL
4
NEVER ADD TO A LOSING POSITION
Later buys on losers are 1.6x larger than first buy
→ Would save ~198.9 SOL
5
STOP AFTER 3 TRADES PER SESSION
Trade #1 avg: +1.5373 SOL → Trade #13 avg: -4.9034 SOL
→ Would save ~135.3 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.
EPjF...Dt1v
Watched it die slowly and did nothing.
The Slow Bleeder
291.1 SOL
-91.0%
4.0/10
Full autopsy →
Aa3M...JN3P
Never sold. Still holding. Still hoping.
The Bag Holder
42.2 SOL
-100.0%
8.0/10
Full autopsy →
EJE1...pump
Never sold. Still holding. Still hoping.
The Bag Holder
22.4 SOL
-100.0%
9.0/10
Full autopsy →
yoX5...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
19.2 SOL
-84.5%
6.0/10
Full autopsy →
8NVj...pump
Panic sold within minutes. Fear won.
The Paper Hand
19.1 SOL
-36.5%
3.5/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.