Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

Name history

mmmll
KNEE
JPMonkey killer
일본숭이 머리 부수기
LOllll
hi ccccc
뉴비 부수기
뭘쳐다보노
BYungsin game
ISLAM
뉴비 분쇄기
lgbt
ㅋㅋ쉽노
부캐 브러지 줘패기
Japan = monkey
녹단 분쇄기
mmmll vs Dragunov 67–6 91.78%
mmmll vs Kazuya 61–1 98.39%
mmmll vs Reina 56–5 91.80%
mmmll vs Paul 50–4 92.59%
mmmll vs Bryan 52–1 98.11%
mmmll vs Victor 50–3 94.34%
mmmll vs Jin 45–6 88.24%
mmmll vs King 43–3 93.48%
mmmll vs Hwoarang 40–2 95.24%
mmmll vs Lili 40–0 100.00%
mmmll vs Steve 38–1 97.44%
mmmll vs Yoshimitsu 34–2 94.44%
mmmll vs Asuka 29–4 87.88%
mmmll vs Lars 24–2 92.31%
mmmll vs Eddy 13–13 50.00%
mmmll vs Azucena 24–1 96.00%
mmmll vs Claudio 21–1 95.45%
mmmll vs Jun 21–1 95.45%
mmmll vs Lidia 21–1 95.45%
mmmll vs Devil Jin 21–0 100.00%
mmmll vs Nina 18–2 90.00%
mmmll vs Lee 15–2 88.24%
mmmll vs Kuma 14–2 87.50%
mmmll vs Law 15–0 100.00%
mmmll vs Leroy 15–0 100.00%
mmmll vs Feng 13–1 92.86%
mmmll vs Alisa 13–1 92.86%
mmmll vs Jack-8 11–1 91.67%
mmmll vs Shaheen 6–3 66.67%
mmmll vs Xiaoyu 7–1 87.50%
mmmll vs Leo 7–1 87.50%
mmmll vs Zafina 7–1 87.50%
mmmll vs Raven 6–2 75.00%
mmmll vs Panda 3–0 100.00%

Limitations

This data is often requested to give insight into which characters you have more trouble with than others, but it is not particularly helpful for that. The main issue is that it is heavily skewed by how strong the opponents you play are.

For example, this data suggests my worst matchup is clearly vs Reina, but that's just because most of those games are vs Yagami.

There is a way to account for this being worked on. The central idea is to assign each matchup a rating vs you which adjusts based on the result, much like the regular rating but also based on the rating of each player. With this, it would give a better summary of how well you perform vs each character.

In the meantime, this page is here to present the data as requested.