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Elvira

#56

Total Matches: 11

Community: Levante

6 Wins 5 Losses

1019

S10 End of Season ELO

1038

S10 Peak ELO

54.5%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

54.5%

ELO Growth +19

Tournament Dominance 1/3

Recent Matches

vs Clares

Liga Simba • Dec 11, 2025

LOSS

-20

vs ❄️ Kumiho ❄️

Liga Simba • Dec 11, 2025

LOSS

-15

vs Mizuki

Liga Simba • Dec 11, 2025

WIN

+16

vs Yisus

Liga Simba • Dec 11, 2025

WIN

+12

vs Clares

LIGA SIMBA 4/12 • Dec 04, 2025

LOSS

-18

vs ❄️ Kumiho ❄️

LIGA SIMBA 4/12 • Dec 04, 2025

WIN

+25

vs Markis.F

LIGA SIMBA 4/12 • Dec 04, 2025

WIN

+23

vs Fiordor

LIGA SIMBA 4/12 • Dec 04, 2025

WIN

+14

vs Cubitoito

Liga Simba 27 de Noviembre 18:30h • Nov 27, 2025

LOSS

-20

vs Ángela

Liga Simba 27 de Noviembre 18:30h • Nov 27, 2025

WIN

+20

Tournament History

Liga Simba #5

La Escotilla • Dec 11, 2025

Record: 2-2-0 • 12 players • Avg ELO: 1014

LIGA SIMBA 4/12 #1

La Escotilla • Dec 04, 2025

Record: 3-1-0 • 9 players • Avg ELO: 1009

Liga Simba 27 de Noviembre 18:30h #6

La Escotilla • Nov 27, 2025

Record: 1-2-0 • 9 players • Avg ELO: 1006

Player Insights

Max Win Streak

Max Loss Streak

+19

ELO Gained

ELO Range

Strong Tournaments (60%+ WR)

Different Stores

Tournaments Played

Advanced Analytics

⚔️

Giant Killer Analysis

No matches against higher-ranked opponents yet

📈

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

6 achievements earned

📚

A Tale for the Ages

Play 10 matches in Season 9.

📖

The Next Chapter

Play 5 matches in Season 9.

✨

Fabled Debut

Play 1 match in Season 9.

📜

Street Rat

Play 5 matches in Season 8.

📖

The First Chapter

Play your first match.

🎮 Achievement Categories

Seasonal_Participation

Participation

🔍 View All Achievements

Top Rivalries

🎯

Clares

2 matches played

0-2

0% win rate

🤝 Occasional Opponent

⚔️

❄️ Kumiho ❄️

2 matches played

1-1

50% win rate

🤝 Occasional Opponent

🏆

Mizuki

1 matches played

1-0

100% win rate

🤝 Occasional Opponent

🏆

Yisus

1 matches played

1-0

100% win rate

🤝 Occasional Opponent

🏆

Markis.F

1 matches played

1-0

100% win rate

🤝 Occasional Opponent

🔥

Current Streak

Wins

📊

68%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

Avg ELO Change

Per Match

Stores Played

La Escotilla

3 tournaments

Most Faced Opponents

Opponent	Matches	Wins	Losses	Win Rate
Clares	2	0	2	0%
❄️ Kumiho ❄️	2	1	1	50%
Mizuki	1	1	0	100%
Yisus	1	1	0	100%
Markis.F	1	1	0	100%
Fiordor	1	1	0	100%
Cubitoito	1	0	1	0%
Ángela	1	1	0	100%
Tenedor	1	0	1	0%

Clares

Matches

Wins

Losses

Draws

Win Rate

❄️ Kumiho ❄️

Matches

Wins

Losses

Draws

Win Rate

50%

Mizuki

Matches

Wins

Losses

Draws

Win Rate

100%

Yisus

Matches

Wins

Losses

Draws

Win Rate

100%

Markis.F

Matches

Wins

Losses

Draws

Win Rate

100%

Fiordor

Matches

Wins

Losses

Draws

Win Rate

100%

Cubitoito

Matches

Wins

Losses

Draws

Win Rate

Ángela

Matches

Wins

Losses

Draws

Win Rate

100%

Tenedor

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

Elvira

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

Clares

❄️ Kumiho ❄️

Mizuki

Yisus

Markis.F

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

🏆 Elvira's Achievements

Season 9 - Fabled

Season 8 - Reign of Jafar

Global Achievements