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LLMM_Ramon

#13

Total Matches: 18

Community: Levante

11 Wins 5 Losses 2 Draws

1103

S10 End of Season ELO

1107

S10 Peak ELO

68.8%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

68.8%

ELO Growth +103

Tournament Dominance 3/5

Recent Matches

vs MisterioGS

Liga Lorcana 3 de diciembre Zacatrus! Valencia • Dec 03, 2025

WIN

+11

vs TS_RDurban

Liga Lorcana 3 de diciembre Zacatrus! Valencia • Dec 03, 2025

WIN

+19

vs Alex

Liga Lorcana 3 de diciembre Zacatrus! Valencia • Dec 03, 2025

WIN

+11

vs TS_Hearene

Liga Lorcana 3 de diciembre Zacatrus! Valencia • Dec 03, 2025

LOSS

-15

vs MK_Hesiro

HeroFreaks Weekly NOV 05 • Nov 29, 2025

LOSS

-18

vs TG_Emiimrtnez

HeroFreaks Weekly NOV 05 • Nov 29, 2025

WIN

+15

vs MK_Taury

HeroFreaks Weekly NOV 05 • Nov 29, 2025

WIN

+24

vs Hector

HeroFreaks Weekly NOV 05 • Nov 29, 2025

DRAW

vs User19260

Liga Lorcana 26 de noviembre Zacatrus! Valencia • Nov 26, 2025

WIN

+17

vs posketo

Liga Lorcana 26 de noviembre Zacatrus! Valencia • Nov 26, 2025

LOSS

-22

Tournament History

Liga Lorcana 3 de diciembre Zacatrus! Valencia #1

Zacatrus! Valencia • Dec 03, 2025

Record: 3-1-0 • 9 players • Avg ELO: 1015

HeroFreaks Weekly NOV 05 #3

HeroFreaks • Nov 29, 2025

Record: 2-1-1 • 12 players • Avg ELO: 1031

Liga Lorcana 26 de noviembre Zacatrus! Valencia #2

Zacatrus! Valencia • Nov 26, 2025

Record: 2-1-0 • 9 players • Avg ELO: 1015

Liga Lorcana 19 de noviembre Zacatrus! Valencia #1

Zacatrus! Valencia • Nov 19, 2025

Record: 3-0-1 • 9 players • Avg ELO: 1015

Liga Lorcana 12 de noviembre Zacatrus! Valencia #6

Zacatrus! Valencia • Nov 12, 2025

Record: 1-2-0 • 9 players • Avg ELO: 1015

Player Insights

Max Win Streak

Max Loss Streak

+103

ELO Gained

146

ELO Range

Strong Tournaments (60%+ WR)

Different Stores

Tournaments Played

Advanced Analytics

⚔️

Giant Killer Analysis

Upset Victories: 1/1

Upset Rate: 100.0%

Biggest Upset: +104 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

8 achievements earned

⚔️

Upset the Balance

Defeat an opponent rated 100+ ELO above you.

🐉

Giant Tamer

Defeat an opponent rated 150+ ELO above you.

📚

Well-Versed

Play 10 matches.

🧞

Friend Like Me

Play 10 matches in Season 8.

📜

Street Rat

Play 5 matches in Season 8.

🎮 Achievement Categories

Giant_Killer

Participation

2 matches played

1-1

50% win rate

🤝 Occasional Opponent

🔥

Current Streak

Wins

📊

74%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

Avg ELO Change

Per Match

Stores Played

Zacatrus! Valencia

4 tournaments

HeroFreaks

1 tournaments

Most Faced Opponents

Opponent	Matches	Wins	Losses	Draws	Win Rate
TS_RDurban	2	1	0	1	50%
Alex	2	2	0	0	100%
TS_Hearene	2	1	1	0	50%
User19260	2	1	1	0	50%
posketo	2	1	1	0	50%
Mc	2	1	1	0	50%
MisterioGS	1	1	0	0	100%
MK_Hesiro	1	0	1	0	0%
TG_Emiimrtnez	1	1	0	0	100%
MK_Taury	1	1	0	0	100%

TS_RDurban

Matches

Wins

Losses

Draws

Win Rate

50%

Alex

Matches

Wins

Losses

Draws

Win Rate

100%

TS_Hearene

Matches

Wins

Losses

Draws

Win Rate

50%

User19260

Matches

Wins

Losses

Draws

Win Rate

50%

posketo

Matches

Wins

Losses

Draws

Win Rate

50%

Matches

Wins

Losses

Draws

Win Rate

50%

MisterioGS

Matches

Wins

Losses

Draws

Win Rate

100%

MK_Hesiro

Matches

Wins

Losses

Draws

Win Rate

TG_Emiimrtnez

Matches

Wins

Losses

Draws

Win Rate

100%

MK_Taury

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

LLMM_Ramon

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

TS_RDurban

Alex

TS_Hearene

User19260

posketo

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

🏆 LLMM_Ramon's Achievements

Global Achievements

Season 8 - Reign of Jafar