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Miguel

#89

Total Matches: 14

Community: Levante

4 Wins 6 Losses 4 Draws

969

S10 End of Season ELO

1020

S10 Peak ELO

40.0%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

40.0%

ELO Growth -31

Tournament Dominance 0/4

Recent Matches

vs Tokipa

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

WIN

+23

vs Israelpr98

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

LOSS

-21

vs Jaescry

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

DRAW

vs Azulito Sielva

Semanal Lorcana Saruman • Nov 27, 2025

DRAW

vs Alcote

Semanal Lorcana Saruman • Nov 27, 2025

LOSS

-16

vs Dok

Semanal Lorcana Saruman • Nov 27, 2025

WIN

+21

vs Agus

Semanal Lorcana Saruman • Nov 27, 2025

LOSS

-18

vs Richimi5

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

LOSS

-22

vs Parra

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

WIN

+22

vs Jaescry

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

LOSS

-17

Tournament History

jueves Evening Weekly Play (Constructed) #3

Saruman Games SC • Dec 04, 2025

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

Semanal Lorcana Saruman #6

Saruman Games SC • Nov 27, 2025

Record: 1-2-1 • 10 players • Avg ELO: 1000

jueves Evening Weekly Play (Constructed) #7

Saruman Games SC • Nov 20, 2025

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

jueves Evening Weekly Play (Constructed) #8

Saruman Games SC • Nov 13, 2025

Record: 1-1-2 • 14 players • Avg ELO: 983

Player Insights

Max Win Streak

Max Loss Streak

-31

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

🎯

Jaescry

3 matches played

0-1-2

0% win rate

🤝 Occasional Opponent

🎯

Alcote

2 matches played

0-2

0% win rate

🤝 Occasional Opponent

🏆

Tokipa

1 matches played

1-0

100% win rate

🤝 Occasional Opponent

🎯

Israelpr98

1 matches played

0-1

0% win rate

🤝 Occasional Opponent

⚔️

Azulito Sielva

1 matches played

0-0-1

0% win rate

🤝 Occasional Opponent

❄️

Current Streak

Losses

📊

65%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

-2

Avg ELO Change

Per Match

Stores Played

Saruman Games SC

4 tournaments

Most Faced Opponents

Opponent	Matches	Wins	Losses	Draws	Win Rate
Jaescry	3	0	1	2	0%
Alcote	2	0	2	0	0%
Tokipa	1	1	0	0	100%
Israelpr98	1	0	1	0	0%
Azulito Sielva	1	0	0	1	0%
Dok	1	1	0	0	100%
Agus	1	0	1	0	0%
Richimi5	1	0	1	0	0%
Parra	1	1	0	0	100%
Leyre_	1	1	0	0	100%

Jaescry

Matches

Wins

Losses

Draws

Win Rate

Alcote

Matches

Wins

Losses

Draws

Win Rate

Tokipa

Matches

Wins

Losses

Draws

Win Rate

100%

Israelpr98

Matches

Wins

Losses

Draws

Win Rate

Azulito Sielva

Matches

Wins

Losses

Draws

Win Rate

Dok

Matches

Wins

Losses

Draws

Win Rate

100%

Agus

Matches

Wins

Losses

Draws

Win Rate

Richimi5

Matches

Wins

Losses

Draws

Win Rate

Parra

Matches

Wins

Losses

Draws

Win Rate

100%

Leyre_

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

Miguel

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

Jaescry

Alcote

Tokipa

Israelpr98

Azulito Sielva

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

🏆 Miguel's Achievements

Season 9 - Fabled