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Agus

#62

Total Matches: 14

Community: Levante

4 Wins 4 Losses 6 Draws

1003

S10 End of Season ELO

1026

S10 Peak ELO

50.0%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

50.0%

ELO Growth +3

Tournament Dominance 1/4

Recent Matches

vs Richimi5

jueves Evening Weekly Play (Constructed) • Dec 04, 2025

DRAW

vs Tokipa

jueves Evening Weekly Play (Constructed) • Dec 04, 2025

DRAW

vs Israelpr98

jueves Evening Weekly Play (Constructed) • Dec 04, 2025

LOSS

-22

vs Jaescry

Semanal Lorcana Saruman • Nov 27, 2025

WIN

+24

vs Richimi5

Semanal Lorcana Saruman • Nov 27, 2025

LOSS

-17

vs Israelpr98

Semanal Lorcana Saruman • Nov 27, 2025

WIN

+19

vs Miguel

Semanal Lorcana Saruman • Nov 27, 2025

WIN

+18

vs Alcote

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

LOSS

-17

vs Tokipa

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

DRAW

vs Jaescry

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

LOSS

-18

Tournament History

jueves Evening Weekly Play (Constructed) #5

Saruman Games SC • Dec 04, 2025

Record: 0-1-2 • 7 players • Avg ELO: 1002

Semanal Lorcana Saruman #1

Saruman Games SC • Nov 27, 2025

Record: 3-1-0 • 10 players • Avg ELO: 1000

jueves Evening Weekly Play (Constructed) #9

Saruman Games SC • Nov 20, 2025

Record: 0-2-1 • 9 players • Avg ELO: 1012

jueves Evening Weekly Play (Constructed) #7

Saruman Games SC • Nov 13, 2025

Record: 1-0-3 • 14 players • Avg ELO: 983

Player Insights

Max Win Streak

Max Loss Streak

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 Losses

Recent Form:

Recent Achievements

1 achievements earned

✨

Fabled Debut

Play 1 match in Season 9.

🎮 Achievement Categories

Seasonal_Participation

🔍 View All Achievements

Top Rivalries

⚔️

Tokipa

3 matches played

0-0-3

0% win rate

🤝 Occasional Opponent

⚔️

Jaescry

3 matches played

1-1-1

33% win rate

🤝 Occasional Opponent

🎯

Richimi5

2 matches played

0-1-1

0% win rate

🤝 Occasional Opponent

⚔️

Israelpr98

2 matches played

1-1

50% win rate

🤝 Occasional Opponent

🏆

Miguel

1 matches played

1-0

100% win rate

🤝 Occasional Opponent

❄️

Current Streak

Losses

📊

67%

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	Draws	Win Rate
Tokipa	3	0	0	3	0%
Jaescry	3	1	1	1	33%
Richimi5	2	0	1	1	0%
Israelpr98	2	1	1	0	50%
Miguel	1	1	0	0	100%
Alcote	1	0	1	0	0%
Leyre_	1	1	0	0	100%
Joan Olivert	1	0	0	1	0%

Tokipa

Matches

Wins

Losses

Draws

Win Rate

Jaescry

Matches

Wins

Losses

Draws

Win Rate

33%

Richimi5

Matches

Wins

Losses

Draws

Win Rate

Israelpr98

Matches

Wins

Losses

Draws

Win Rate

50%

Miguel

Matches

Wins

Losses

Draws

Win Rate

100%

Alcote

Matches

Wins

Losses

Draws

Win Rate

Leyre_

Matches

Wins

Losses

Draws

Win Rate

100%

Joan Olivert

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

Agus

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

Tokipa

Jaescry

Richimi5

Israelpr98

Miguel

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

🏆 Agus's Achievements

Season 9 - Fabled