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Anya

#279

Total Matches: 12

Community: Madrid

2 Wins 10 Losses

880

S10 End of Season ELO

1000

S10 Peak ELO

16.7%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

16.7%

ELO Growth -120

Tournament Dominance 0/4

Recent Matches

vs Tiny_Duck_6132

Construido - Whispers in the Well • Jan 17, 2026

WIN

+26

vs TJM_Sulaco

Construido - Whispers in the Well • Jan 17, 2026

LOSS

-9

vs sanzellos

Construido - Whispers in the Well • Jan 17, 2026

LOSS

-13

vs sanzellos

Friday Lorcana Afternoon Tournament Rivas TJM • Jan 09, 2026

LOSS

-16

vs User32708

Friday Lorcana Afternoon Tournament Rivas TJM • Jan 09, 2026

LOSS

-15

vs TJM_Lord_Darkstar

Friday Lorcana Afternoon Tournament Rivas TJM • Jan 09, 2026

LOSS

-16

vs Iñaki

Friday Lorcana • Dec 19, 2025

LOSS

-18

vs TJM_Lord_Darkstar

Friday Lorcana • Dec 19, 2025

LOSS

-21

vs TJM_Sulaco

Friday Lorcana • Dec 19, 2025

LOSS

-9

vs IBRA

Construido WHISPERS (WP) • Nov 21, 2025

LOSS

-22

Tournament History

Construido - Whispers in the Well #7

TE JUEGO MUCHO • Jan 17, 2026

Record: 1-2-0 • 12 players • Avg ELO: 1004

Friday Lorcana Afternoon Tournament Rivas TJM NR

TE JUEGO MUCHO • Jan 09, 2026

Record: 0-3-0 • 8 players • Avg ELO: 1000

Friday Lorcana NR

TE JUEGO MUCHO • Dec 19, 2025

Record: 0-3-0 • 4 players • Avg ELO: 957

Construido WHISPERS (WP) #4

TE JUEGO MUCHO • Nov 21, 2025

Record: 1-2-0 • 6 players • Avg ELO: 994

Player Insights

Max Win Streak

Max Loss Streak

-120

ELO Gained

124

ELO Range

Strong Tournaments (60%+ WR)

Different Stores

Tournaments Played

Advanced Analytics

⚔️

Giant Killer Analysis

Upset Victories: 1/4

Upset Rate: 25.0%

Biggest Upset: +124 ELO

📈

ELO Momentum

Recent Trend: ➡️ Stable

Average Change: 0

Consistency: 100%

📅

Performance Patterns

Not enough data to determine patterns yet

⚡

Current Form

Current Streak: 2 Losses

Recent Form:

Recent Achievements

6 achievements earned

📜

Street Rat

Play 5 matches in Season 8.

📖

The First Chapter

Play your first match.

🥇

First Victory

Win your first match.

🐍

Jafar's Recruit

Play 1 match in Season 8.

🗺️

Store Hopper

Play at 2 different stores.

🎮 Achievement Categories

Seasonal_Participation

Participation

1 matches played

0-1

0% win rate

🤝 Occasional Opponent

❄️

Current Streak

Losses

📊

59%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

-10

Avg ELO Change

Per Match

Stores Played

TE JUEGO MUCHO

4 tournaments

Most Faced Opponents

Opponent	Matches	Wins	Losses	Win Rate
TJM_Sulaco	2	0	2	0%
sanzellos	2	0	2	0%
Tiny_Duck_6132	1	1	0	100%
User32708	1	0	1	0%
TJM_Lord_Darkstar	1	0	1	0%
Iñaki	1	0	1	0%
TJM_Lord_Darkstar	1	0	1	0%
IBRA	1	0	1	0%
TJM_Arroyo	1	0	1	0%
LBT_MeryOuat	1	1	0	100%

TJM_Sulaco

Matches

Wins

Losses

Draws

Win Rate

sanzellos

Matches

Wins

Losses

Draws

Win Rate

Tiny_Duck_6132

Matches

Wins

Losses

Draws

Win Rate

100%

User32708

Matches

Wins

Losses

Draws

Win Rate

TJM_Lord_Darkstar

Matches

Wins

Losses

Draws

Win Rate

Iñaki

Matches

Wins

Losses

Draws

Win Rate

TJM_Lord_Darkstar

Matches

Wins

Losses

Draws

Win Rate

IBRA

Matches

Wins

Losses

Draws

Win Rate

TJM_Arroyo

Matches

Wins

Losses

Draws

Win Rate

LBT_MeryOuat

Matches

Wins

Losses

Draws

Win Rate

100%

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

Anya

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

TJM_Sulaco

sanzellos

Tiny_Duck_6132

User32708

TJM_Lord_Darkstar

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

🏆 Anya's Achievements

Season 8 - Reign of Jafar

Global Achievements