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Azulito

#89

Total Matches: 15

Community: Levante

7 Wins 6 Losses 2 Draws

1029

S10 End of Season ELO

1039

S10 Peak ELO

53.8%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

53.8%

ELO Growth +29

Tournament Dominance 0/4

Recent Matches

vs Drowsy

domingo Morning Whispers in the Well - Set Championship • Jan 25, 2026

LOSS

-18

vs Agus

domingo Morning Whispers in the Well - Set Championship • Jan 25, 2026

WIN

+19

vs Azkan

domingo Morning Whispers in the Well - Set Championship • Jan 25, 2026

WIN

+22

vs Sofiiamaartin

domingo Morning Whispers in the Well - Set Championship • Jan 25, 2026

LOSS

-14

vs Juanvo

jueves Evening Weekly Play (Constructed) • Jan 15, 2026

LOSS

-14

vs Joan Olivert

jueves Evening Weekly Play (Constructed) • Jan 15, 2026

WIN

+13

vs Israelpr98

jueves Evening Weekly Play (Constructed) • Jan 15, 2026

LOSS

-17

vs Lady Merhyd

jueves Evening Weekly Play (Constructed) • Jan 15, 2026

WIN

+17

vs Jaescry

jueves Evening Weekly Play (Constructed) • Nov 20, 2025

LOSS

-18

vs Parra

jueves Evening Weekly Play (Constructed) • Nov 20, 2025

LOSS

-20

Tournament History

domingo Morning Whispers in the Well - Set Championship #12

Saruman Games SC • Jan 25, 2026

Record: 2-2-0 • 23 players • Avg ELO: 1061

jueves Evening Weekly Play (Constructed) #4

Saruman Games SC • Jan 15, 2026

Record: 2-2-0 • 11 players • Avg ELO: 1025

jueves Evening Weekly Play (Constructed) #7

Saruman Games SC • Nov 20, 2025

Record: 1-2-0 • 9 players • Avg ELO: 1003

jueves Evening Weekly Play (Constructed) #1

Saruman Games SC • Nov 13, 2025

Record: 2-0-2 • 14 players • Avg ELO: 979

Player Insights

Max Win Streak

Max Loss Streak

+29

ELO Gained

ELO Range

Strong Tournaments (60%+ WR)

Different Stores

Tournaments Played

Advanced Analytics

⚔️

Giant Killer Analysis

Upset Victories: 0/1

Upset Rate: 0.0%

📈

ELO Momentum

Recent Trend: ➡️ Stable

Average Change: 0

Consistency: 100%

📅

Performance Patterns

Not enough data to determine patterns yet

⚡

Current Form

Current Streak: 2 Wins

Recent Form:

Recent Achievements

0 achievements earned

�

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

🎮 Achievement Categories

0-1

0% win rate

🤝 Occasional Opponent

🔥

Current Streak

Wins

📊

69%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

Avg ELO Change

Per Match

Stores Played

Saruman Games SC

4 tournaments

Most Faced Opponents

Opponent	Matches	Wins	Losses	Win Rate
Joan Olivert	2	2	0	100%
Drowsy	1	0	1	0%
Agus	1	1	0	100%
Azkan	1	1	0	100%
Sofiiamaartin	1	0	1	0%
Juanvo	1	0	1	0%
Israelpr98	1	0	1	0%
Lady Merhyd	1	1	0	100%
Jaescry	1	0	1	0%
Parra	1	0	1	0%

Joan Olivert

Matches

Wins

Losses

Draws

Win Rate

100%

Drowsy

Matches

Wins

Losses

Draws

Win Rate

Agus

Matches

Wins

Losses

Draws

Win Rate

100%

Azkan

Matches

Wins

Losses

Draws

Win Rate

100%

Sofiiamaartin

Matches

Wins

Losses

Draws

Win Rate

Juanvo

Matches

Wins

Losses

Draws

Win Rate

Israelpr98

Matches

Wins

Losses

Draws

Win Rate

Lady Merhyd

Matches

Wins

Losses

Draws

Win Rate

100%

Jaescry

Matches

Wins

Losses

Draws

Win Rate

Parra

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

Azulito

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

Joan Olivert

Drowsy

Agus

Azkan

Sofiiamaartin

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

🏆 Azulito's Achievements