REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / 73wLTVh6B2uvntsUsP9MzsTdQ7GyrPfypiEgKY8W6caD
F
Behavioral Grade
F
25 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
73wLTVh6B2uvntsUsP9MzsTdQ7GyrPfypiEgKY8W6caD
At your current pace, your capital halves every 0.1 days.
Your brain cost you
521.9 SOL
≈ $40.5k behavioral damage
Survival prob.
0%
37 wins to break even
Capital half-life
0.1d
Bleed rate
1.392 SOL/hr
Win rate
15.4%
Net P&L
−269.8 SOL
Win rate
15.4%
Profit factor
0.66
Tokens
455
SOL in
1.7k
SOL out
1.4k
Primary
Diagnosis
67% 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.
67%
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.
+521.9 SOL
Catchable Losses
214 / 380
Behavioral Drag
67%
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
380 losses
→
Fast re-entry
42x
→
Bigger size
50 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
42x
BEHAVIORAL DAMAGE REPORT
😴
Session Fatigue
-235.9 SOL($18.3k)
After trade #15, avg P&L drops to -3.8358 SOL
Trade #1 avg: -0.9198 SOL
📈
Averaging Down
-233.6 SOL($18.1k)
50 tokens where later buys were 3.4x larger
Later buys on losing positions
⏰
Late Night Trading
-55.5 SOL($4.3k)
174 trades between 11PM–5AM
Best hours: 8PM
😤
Revenge Trading
-42.5 SOL($3.3k)
42 trades within 10 min of a loss
Win rate on these: 17%
TOTAL BEHAVIORAL DRAG
-567.5 SOL($44.1k)
CIRCADIAN PROFILE
WORST: 12PM▾
12a33
1a28
2a21
3a34
4a17
5a11
6a11
7a7
8a5
9a2
11a3
12p7
1p22
2p21
3p13
4p20
5p22
6p28
7p24
8p26
9p25
10p34
11p41
Night (11PM–5AM): -0.3187 SOL/trade · Day (8AM–8PM): -1.4185 SOL/trade
DISPOSITION EFFECT
0.4x▾
WINNER HOLD
7.6d
LOSER HOLD
3.4d
You hold losers 0.4x longer than winners.
SESSION FATIGUE
123 SESSIONS▾
#1
-0.9198
#2
-0.7224
#3
+1.558
#4
+0.1646
#5
-0.9193
#6
-0.9961
#7
-1.8654
#8
-1.9455
Avg session: 3.7 trades. Dominant pattern: Loss from the Start (70%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
43m
BASELINE GAP
36m
42 trades opened within 10 min of a loss. Loss rate on these: 83%
EQUITY CURVE
DISCIPLINED: +521.9 SOL▾
Peak: +130.9 SOL at token #54
Max drawdown: 400.7 SOL
- - - = you without 214 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 (134% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 3.4x larger than first buy
→ Would save ~413.1 SOL
2
DON'T INCREASE SIZE AFTER A LOSS
Avg size after loss: 3.885 SOL vs 2.615 after win (1.49x)
→ Would save ~240.6 SOL
3
STOP BUYING ON PUMP_AMM
274 tokens from PUMP_AMM: 14% WR, -355.867 SOL net
→ Would save ~213.5 SOL
4
STOP AFTER 3 TRADES PER SESSION
Trade #1 avg: -0.9198 SOL → Trade #15 avg: -3.8358 SOL
→ Would save ~125.4 SOL
5
AVOID TRADING ON SATS
SAT avg: -1.3294 SOL across 64 trades
→ Would save ~59.6 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.
USD1...EmuB
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−23.8 SOL
-84.0%
6.0/10
Full autopsy →
EXrP...fomo
Never sold. Still holding. Still hoping.
The Bag Holder
−21.3 SOL
-100.0%
9.0/10
Full autopsy →
Njix...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−17.7 SOL
-92.3%
6.0/10
Full autopsy →
5LJA...pump
Never sold. Still holding. Still hoping.
The Bag Holder
−15.7 SOL
-100.0%
9.0/10
Full autopsy →
Hb2R...onAo
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−12.4 SOL
-83.9%
6.0/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.