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paulisknowsbest

#170

Total Matches: 22

Community: Levante

6 Wins 16 Losses

899

S10 End of Season ELO

1000

S10 Peak ELO

27.3%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

27.3%

ELO Growth -101

Tournament Dominance 0/6

Recent Matches

vs Tenedor

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

LOSS

-9

vs Txusi

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

WIN

+25

vs Quick_Kangaroo_3815

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

LOSS

-14

vs Jess

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

WIN

+26

vs ❄️ Kumiho ❄️

LIGA SIMBA 22/01/2026 • Jan 22, 2026

LOSS

-4

vs Fixey

LIGA SIMBA 22/01/2026 • Jan 22, 2026

LOSS

-14

vs Clares

LIGA SIMBA 22/01/2026 • Jan 22, 2026

LOSS

-10

vs Markis.F

LIGA SIMBA 22/01/2026 • Jan 22, 2026

WIN

+30

vs Yisus

LIGA SIMBA 15/01/2026 • Jan 15, 2026

LOSS

-18

vs Markis.F

LIGA SIMBA 15/01/2026 • Jan 15, 2026

LOSS

-8

Tournament History

LIGA SIMBA 29/01/2025 - 18:30H #5

La Escotilla • Jan 29, 2026

Record: 2-2-0 • 14 players • Avg ELO: 1004

LIGA SIMBA 22/01/2026 #11

La Escotilla • Jan 22, 2026

Record: 1-3-0 • 15 players • Avg ELO: 1023

LIGA SIMBA 15/01/2026 #7

La Escotilla • Jan 15, 2026

Record: 1-2-0 • 11 players • Avg ELO: 999

Liga Simba #9

La Escotilla • Jan 08, 2026

Record: 1-3-0 • 12 players • Avg ELO: 1002

Liga Simba - Viernes Afternoon Weekly Play (Constructed) NR

La Escotilla • Jan 02, 2026

Record: 0-3-0 • 11 players • Avg ELO: 1008

SIMBA 23/12/2025 #9

La Escotilla • Dec 23, 2025

Record: 1-3-0 • 10 players • Avg ELO: 1018

Player Insights

Max Win Streak

Max Loss Streak

-101

ELO Gained

140

ELO Range

Strong Tournaments (60%+ WR)

Different Stores

Tournaments Played

Advanced Analytics

⚔️

Giant Killer Analysis

Upset Victories: 2/10

Upset Rate: 20.0%

Biggest Upset: +207 ELO

📈

ELO Momentum

Recent Trend: ➡️ Stable

Average Change: 0

Consistency: 100%

📅

Performance Patterns

Not enough data to determine patterns yet

⚡

Current Form

Current Streak: 1 Wins

Recent Form:

Recent Achievements

0 achievements earned

�

No achievements yet - play some matches to start earning them!

🎮 Achievement Categories

0-2

0% win rate

🤝 Occasional Opponent

🔥

Current Streak

Wins

📊

60%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

-5

Avg ELO Change

Per Match

Stores Played

La Escotilla

6 tournaments

Most Faced Opponents

Opponent	Matches	Wins	Losses	Win Rate
Markis.F	4	1	3	25%
Fiordor	3	3	0	100%
Tenedor	2	0	2	0%
❄️ Kumiho ❄️	2	0	2	0%
Yisus	2	0	2	0%
Cubitoito	2	0	2	0%
Txusi	1	1	0	100%
Quick_Kangaroo_3815	1	0	1	0%
Jess	1	1	0	100%
Fixey	1	0	1	0%

Markis.F

Matches

Wins

Losses

Draws

Win Rate

25%

Fiordor

Matches

Wins

Losses

Draws

Win Rate

100%

Tenedor

Matches

Wins

Losses

Draws

Win Rate

❄️ Kumiho ❄️

Matches

Wins

Losses

Draws

Win Rate

Yisus

Matches

Wins

Losses

Draws

Win Rate

Cubitoito

Matches

Wins

Losses

Draws

Win Rate

Txusi

Matches

Wins

Losses

Draws

Win Rate

100%

Quick_Kangaroo_3815

Matches

Wins

Losses

Draws

Win Rate

Jess

Matches

Wins

Losses

Draws

Win Rate

100%

Fixey

Matches

Wins

Losses

Draws

Win Rate

Understanding ELO Rating System

What is ELO?

The ELO rating system is a method for calculating the relative skill levels of players in zero-sum games such as chess, or in our case, Lorcana tournaments. It was originally developed by Arpad Elo for chess competitions.

Each player starts with a base rating (1000), and this rating changes after each match based on the outcome and the relative skill difference between players.

How Does It Work?

Basic Formula:

New Rating = Old Rating + K × (Actual Score - Expected Score)

Expected Score Formula:

E = 1 / (1 + 10^((Rb - Ra) / 400))

Where Ra is your rating and Rb is opponent's rating

K-Factor:

Determines how much ratings change per game:

• New players: K = 32
• Experienced: K = 16
• Masters: K = 10

Examples

Beating a Higher-Rated Player

You (1000) vs Opponent (1200)

Expected: You have ~24% chance to win

If you win: +24 rating points!

Losing to a Lower-Rated Player

You (1200) vs Opponent (1000)

Expected: You have ~76% chance to win

If you lose: -24 rating points

Key Points

• Ratings are relative - they only matter in comparison to other players
• Beating stronger opponents gives more points than beating weaker ones
• Your rating stabilizes over time as you play more games
• Draws result in no ELO change for both players
• The system is self-correcting - ratings tend toward your true skill level

paulisknowsbest

ELO History

Match Outcome Constellation

Tournament Performance Profile

Performance Metrics Explained

Performance Metrics

Recent Matches

Tournament History

Player Insights

Advanced Analytics

Giant Killer Analysis

ELO Momentum

Performance Patterns

Current Form

Recent Achievements

🎮 Achievement Categories

Top Rivalries

Markis.F

Fiordor

Tenedor

❄️ Kumiho ❄️

Yisus

Stores Played

Most Faced Opponents

Understanding ELO Rating System

What is ELO?

How Does It Work?

Basic Formula:

Expected Score Formula:

K-Factor:

Examples

Beating a Higher-Rated Player

Losing to a Lower-Rated Player

Key Points

📜 Full Match History

🏆 paulisknowsbest's Achievements