REKT AUTOPSY
FORENSIC TRADING ANALYSIS
BEHAVIORAL AUTOPSY / Ey1DmXXbCih4k7jEw1jfxcpUg6ZVb43guKeGRvXCTg4A
F
Behavioral Grade
F
20 / 100
Wallet Death Certificate
The math gives you a 99% chance of going to zero.
Ey1DmXXbCih4k7jEw1jfxcpUg6ZVb43guKeGRvXCTg4A
At your current pace, your capital halves every 0.1 days.
Your brain cost you
748.3 SOL
≈ $58.1k behavioral damage
Survival prob.
0%
136 wins to break even
Capital half-life
0.1d
Bleed rate
2.832 SOL/hr
Win rate
20.7%
Net P&L
−699.2 SOL
Win rate
20.7%
Profit factor
0.43
Tokens
497
SOL in
3.0k
SOL out
2.3k
Primary
Diagnosis
61% of attributed damage came from recurring behavior, not market noise — sizing, tilt, timing.
§ 03 · Compound Intelligence
THE NUMBERS THAT MATTER.
Avoidable Loss Score
Most losses were behavioral, not random.
61%
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.
+748.3 SOL
Catchable Losses
170 / 392
Behavioral Drag
61%
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
392 losses
→
Fast re-entry
83x
→
Bigger size
60 tokens
→
Late entry
→
Held collapse
Stages Fired
3 / 5
Fast Re-entries
83x
BEHAVIORAL DAMAGE REPORT
📈
Averaging Down
-585.9 SOL($45.5k)
60 tokens where later buys were 50.2x larger
Later buys on losing positions
😴
Session Fatigue
-231.8 SOL($18.0k)
After trade #20, avg P&L drops to -5.094 SOL
Trade #1 avg: -1.0651 SOL
😤
Revenge Trading
-126.3 SOL($9.8k)
83 trades within 10 min of a loss
Win rate on these: 10%
⏰
Late Night Trading
-31.8 SOL($2.5k)
19 trades between 11PM–5AM
Best hours: 1PM
TOTAL BEHAVIORAL DRAG
-975.8 SOL($75.8k)
CIRCADIAN PROFILE
WORST: 1AM▾
12a2
1a1
3a5
4a1
5a9
6a19
7a32
8a34
9a32
10a36
11a29
12p36
1p33
2p32
3p29
4p16
5p24
6p34
7p28
8p19
9p18
10p18
11p10
Night (11PM–5AM): -1.6751 SOL/trade · Day (8AM–8PM): -1.3817 SOL/trade
DISPOSITION EFFECT
0.2x▾
WINNER HOLD
2.6d
LOSER HOLD
13.9h
You hold losers 0.2x longer than winners.
SESSION FATIGUE
91 SESSIONS▾
#1
-1.0651
#2
-1.5312
#3
-2.1106
#4
+0.3039
#5
-1.1044
#6
-1.9441
#7
-1.3876
#8
-1.6336
Avg session: 5.5 trades. Dominant pattern: Loss from the Start (48%)
POST-LOSS VELOCITY
NORMAL▾
POST-LOSS GAP
13m
BASELINE GAP
14m
83 trades opened within 10 min of a loss. Loss rate on these: 90%
EQUITY CURVE
DISCIPLINED: +748.3 SOL▾
Peak: +23.5 SOL at token #13
Max drawdown: 722.7 SOL
- - - = you without 170 behavioral trades
P&L SUMMARY
▾
ADVANCED METRICS
▾
LOSS CONCENTRATION
▾
DEX ANALYSIS
▾
YOUR PRESCRIPTION
Rules derived from your trading data that would have saved you 1.6k SOL (132% of total losses)
1
NEVER ADD TO A LOSING POSITION
Later buys on losers are 50.2x larger than first buy
→ Would save ~875.7 SOL
2
STOP BUYING ON JUPITER
359 tokens from JUPITER: 21% WR, -520.933 SOL net
→ Would save ~312.6 SOL
3
STOP AFTER 3 TRADES PER SESSION
Trade #1 avg: -1.0651 SOL → Trade #20 avg: -5.094 SOL
→ Would save ~185.3 SOL
4
AVOID TRADING ON THUS
THU avg: -2.9327 SOL across 63 trades
→ Would save ~129.3 SOL
5
WAIT 30 MIN AFTER A LOSS
Post-loss trades lose 90% vs 79% baseline
→ Would save ~126.3 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.
3YGa...H19a
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−33.4 SOL
-65.9%
4.5/10
Full autopsy →
JBLR...pump
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−32.1 SOL
-75.5%
4.5/10
Full autopsy →
7o4Y...zxUU
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−30.2 SOL
-69.6%
4.5/10
Full autopsy →
GCHi...cQHX
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−29.2 SOL
-68.1%
4.5/10
Full autopsy →
EJVL...1WTY
Kept buying. It kept dumping. They kept buying.
The Repeat Offender
−27.3 SOL
-71.7%
3.5/10
Full autopsy →
NOT FINANCIAL ADVICE. JUST THE MATH.