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saving-for-japan-trip

@saving-for-japan-trip

#61,64859

0x8b5de720a9699ac39e888ad9bd06c7fec1be57d3

163d· 953 markets · 2627 tradesVol: $120,9122026-06-26T14:04
SMART SCORE SYSTEM

Composite trader rating.
0 to 100.

Smart Score aggregates PnL consistency, win rate, risk management, diversification, timing patterns, and trading behavior into a single 0‑100 score. Combined with bot detection that analyzes trade timing gaps, order patterns, and execution speed.

59
Good
80-100Elite
60-79Diamond
40-59Gold
0-39Standard

Score Components

Win Rate 53%11/20
Profit Factor 1.34x7/15
Sharpe 0.2164/15
Sortino 0.2723/10
EV $+0.33610/10
HHI 4410/10
Profit Days 75%10/10
DD/Peak 51%4/10

Summary

Saving-for-japan-trip is a moderately active trader on Polymarket with 2,627 trades across 381 markets over 339 days, ranking #61,648 globally by net PnL. Their net profit stands at $1,469.92 on a total trading volume of $120,912, reflecting a solid but cautious trading approach. The trader’s portfolio value is $465.21, and they maintain a steady equity trend with no significant drawdowns.

This trader specializes heavily in weather markets, which constitute 97% of their activity, suggesting a focused expertise in this niche. Their trading style is low risk, demonstrated by a very high win rate of 99.3% and an exceptionally high profit factor of 1216.21, indicating consistent profitability. The low sell percentage (6%) and badges like Diamond Hands and DCA Master imply a preference for holding positions and dollar-cost averaging rather than frequent flipping. Their Sharpe ratio of 0.22 signals moderate risk-adjusted returns, while the semi-bot score hints at a hybrid of automated and manual trading.

Key strengths for saving-for-japan-trip include their reliability and consistency in weather markets, as well as strong risk management shown by zero max drawdown duration. However, potential risks involve low portfolio growth and limited diversification, which could expose them to sector-specific downturns. Their semi-bot approach may also introduce vulnerabilities if market conditions shift rapidly. Overall, saving-for-japan-trip demonstrates solid performance within a narrow focus on Polymarket.

Analysis based on the last 250 closed positions. Full trading history — coming soon.

Badges

7
Profitable
PnL $+1,470
Contrarian
91% entries <$0.50
Diamond Hands
6% sell
DCA Master
avg 6.5 entries/market
Weather Pro
97% weather
Win Streak
114 wins in a row
Consistent
87/116 days

Categories

4
🌤️ WEATHER#998$1,631Vol: $114,859
CRYPTO#1,036,027$-6Vol: $212
🏛️ POLITICS#112,989$29Vol: $179
📢 MENTIONS#32,195$2Vol: $9

Overview

#1
Net PnL
$1,470
Polymarket official
Total Volume
$120,912
Total Redeem
$19,839
Portfolio
$465
Predictions
953
total markets
Trades
2477B / 150S
Daily Volume
$62
Account Age
163d
since Jan 21, 2026

Periods

#2
Today
$-12
Vol: $905
Week
$-681
Vol: $6,609
Month
$-511
Vol: $25,118
All Time
$1,470
Vol: $120,912

PnL Analysis

#3
Win Rate (events)
68%
224W / 107L events
Realized PnL
$14,370
Win Rate
99%
141W / 1L
Profit Factor
1216.21x
Avg Win
$79
Avg Loss
$-9

Outlier Sensitivity: Top-3 = $662 (6% of PnL)

Top Winners

Will the highest temperature in Munich be 25°C on May 2?$268
Will the highest temperature in Paris be 29°C on May 22?$205
Will the highest temperature in London be 30°C on May 24?$190
Will the highest temperature in Munich be 20°C on May 1?$189
Will the highest temperature in Madrid be 39°C on June 24?$181
Will the highest temperature in Munich be 31°C or higher on May 2$162
Will the highest temperature in London be 28°C on May 22?$162
Will the highest temperature in Milan be 33°C on May 27?$159
Will the highest temperature in London be 34°C on May 26?$146
Will the highest temperature in Munich be 22°C on May 9?$142

Top Losers

Will the highest temperature in Madrid be 19°C on May 8?$-9

Risk Metrics

#4
Sharpe
0.216
Sortino
0.272
HHI
44
Diversified
EV per $1
$0.336
Kelly %
99.0%
Half-Kelly
49.5%
Top-1 market
2.1%
Top-5 markets
8.2%

Behavior Analysis

#5
Trades / Day
22.5
Active
Markets / Day
3.3
Active Hours
24/24
Around the clock
Peak Hour
8:00 UTC
Median Gap
2.1m
between trades
Avg Gap
33.7m
between trades
Night Trading
10%
22:00–06:00 UTC
Size Variance
1.76
Variable
Session Statistics
Sessions
50
Avg Duration
1 min
Avg Trades / Session
1.8

Bot Detection

#6
40
SEMI-BOT (bot + manual)MEDIUM probability

7 indicators analyzed

Trade Speed
LOW
Night Activity
LOW
Active Hours
HIGH
Trade Frequency
LOW
Size Consistency
LOW
Market Coverage
LOW
Median gap 124s — typical for humanSize CV 1.76 — diverse, typical for human10% at night — normal sleep pattern24/24 hours — around the clockSession CV 1.09 — human randomness22 trades/day — suspiciously high490 total positions — large-scale activity

Timing Patterns

#7

Peak hour: 8:00 UTC

0
4
8
12
16
20

DCA Analysis

#8
Avg entries/market
6.5
Active DCA
<=1
74 entries
<=2
102 entries
<=5
184 entries
<=10
306 entries
<=20
373 entries
<=50
381 entries
>50
0 entries

Price Levels

#9
Low (<20c)6.4%
Mid (20-55c)89.1%
High (>55c)4.6%

City Stats

#10

YES bias: 94.6%

Munich$2,980
London$2,313
Milan$2,123
Madrid$1,784
Paris$1,694
Other$192

Bracket Analysis

#11
Avg brackets/event
1.9
Events covered
201

Single bracket

<=1
47 brackets
<=2
175 brackets
<=3
201 brackets
<=4
201 brackets
<=5
201 brackets
<=8
201 brackets
>8
0 brackets

Sessions

#12
3/1/2026, 12:25:13 PM1 trades$180 min
3/1/2026, 9:56:23 PM1 trades$100 min
3/4/2026, 4:09:57 PM1 trades$480 min
4/24/2026, 4:43:10 PM2 trades$70 min
4/24/2026, 5:00:36 PM2 trades$60 min
4/25/2026, 1:02:42 AM1 trades$40 min
4/25/2026, 4:17:12 AM1 trades$10 min
4/25/2026, 6:17:42 PM2 trades$70 min
4/27/2026, 4:12:22 PM1 trades$620 min
4/27/2026, 4:18:36 PM2 trades$213 min
4/27/2026, 4:29:30 PM1 trades$00 min
4/28/2026, 3:22:38 PM2 trades$320 min
4/28/2026, 3:55:34 PM1 trades$00 min
4/28/2026, 9:03:58 PM1 trades$20 min
4/28/2026, 9:18:10 PM1 trades$30 min
4/28/2026, 9:29:00 PM1 trades$10 min
4/28/2026, 9:38:26 PM2 trades$214 min
4/29/2026, 6:51:08 AM8 trades$8611 min
4/29/2026, 7:16:02 AM1 trades$10 min
4/29/2026, 7:27:12 AM2 trades$60 min

Equity Curve

#13
Cumulative PnL by market end date Profit Loss Today
01-26
03-19
04-08
04-27
05-17
06-07
06-27

Faded bars = markets ending in the future (PnL from early exits)

Profile

#14
Specialization
WEATHER
97.1% weather
Holding Style
HOLD
5.7% sell
DCA Style
HEAVY
avg 6.5/mkt
Hedging
SINGLE
avg 1.9 br/event