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Fiordor

#184

Total Matches: 28

Community: Levante

0 Wins 28 Losses

670

S10 End of Season ELO

1000

S10 Peak ELO

0.0%

Win Rate

ELO History

Match Outcome Constellation

✨

⭐

🌟

✨

💫

◯

Wins

Losses

Draws

⭐ Star size = ELO impact

Tournament Performance Profile

Performance Metrics

Consistency Rating

0.0%

ELO Growth -330

Tournament Dominance 0/8

Recent Matches

vs Quick_Kangaroo_3815

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

LOSS

-6

vs Elvira

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

LOSS

-6

vs Jess

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

LOSS

-6

vs Clares

LIGA SIMBA 29/01/2025 - 18:30H • Jan 29, 2026

LOSS

-3

vs Tenedor

LIGA SIMBA 15/01/2026 • Jan 15, 2026

LOSS

-5

vs paulisknowsbest

LIGA SIMBA 15/01/2026 • Jan 15, 2026

LOSS

-11

vs Txusi

LIGA SIMBA 15/01/2026 • Jan 15, 2026

LOSS

-5

vs Clares

Liga Simba • Jan 08, 2026

LOSS

-6

vs Mizuki

Liga Simba • Jan 08, 2026

LOSS

-10

vs Jotaeme

Liga Simba • Jan 08, 2026

LOSS

-8

Tournament History

LIGA SIMBA 29/01/2025 - 18:30H NR

La Escotilla • Jan 29, 2026

Record: 0-4-0 • 14 players • Avg ELO: 1004

LIGA SIMBA 15/01/2026 NR

La Escotilla • Jan 15, 2026

Record: 0-3-0 • 11 players • Avg ELO: 999

Liga Simba NR

La Escotilla • Jan 08, 2026

Record: 0-4-0 • 12 players • Avg ELO: 1002

Liga Simba - Viernes Afternoon Weekly Play (Constructed) NR

La Escotilla • Jan 02, 2026

Record: 0-3-0 • 11 players • Avg ELO: 1008

SIMBA 23/12/2025 NR

La Escotilla • Dec 23, 2025

Record: 0-4-0 • 10 players • Avg ELO: 1018

Liga Simba NR

La Escotilla • Dec 11, 2025

Record: 0-4-0 • 12 players • Avg ELO: 1048

LIGA SIMBA 4/12 NR

La Escotilla • Dec 04, 2025

Record: 0-3-0 • 9 players • Avg ELO: 1032

Liga Simba 27 de Noviembre 18:30h NR

La Escotilla • Nov 27, 2025

Record: 0-3-0 • 9 players • Avg ELO: 1021

Player Insights

Max Win Streak

Max Loss Streak

-330

ELO Gained

330

ELO Range

Strong Tournaments (60%+ WR)

Different Stores

Tournaments Played

Advanced Analytics

⚔️

Giant Killer Analysis

Upset Victories: 0/18

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: 28 Losses

Recent Form:

Recent Achievements

1 achievements earned

✨

Fabled Debut

Play 1 match in Season 9.

🎮 Achievement Categories

0-3

0% win rate

🤝 Occasional Opponent

❄️

Current Streak

Losses

📊

45%

ELO Percentile

vs All Players

📅

This Month

Matches Played

⚡

-12

Avg ELO Change

Per Match

Stores Played

La Escotilla

8 tournaments

Most Faced Opponents

Opponent	Matches	Losses	Win Rate
Elvira	4	4	0%
Mizuki	4	4	0%
Clares	3	3	0%
paulisknowsbest	3	3	0%
Yisus	3	3	0%
Tenedor	2	2	0%
Txusi	2	2	0%
Quick_Kangaroo_3815	1	1	0%
Jess	1	1	0%
Jotaeme	1	1	0%

Elvira

Matches

Wins

Losses

Draws

Win Rate

Mizuki

Matches

Wins

Losses

Draws

Win Rate

Clares

Matches

Wins

Losses

Draws

Win Rate

paulisknowsbest

Matches

Wins

Losses

Draws

Win Rate

Yisus

Matches

Wins

Losses

Draws

Win Rate

Tenedor

Matches

Wins

Losses

Draws

Win Rate

Txusi

Matches

Wins

Losses

Draws

Win Rate

Quick_Kangaroo_3815

Matches

Wins

Losses

Draws

Win Rate

Jess

Matches

Wins

Losses

Draws

Win Rate

Jotaeme

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

Fiordor

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

Elvira

Mizuki

Clares

paulisknowsbest

Yisus

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

🏆 Fiordor's Achievements

Season 9 - Fabled