Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics
unbalance

Ratings

unbalance vs Kazuya 162–185 46.69%
unbalance vs Dragunov 137–207 39.83%
unbalance vs Paul 151–146 50.84%
unbalance vs Bryan 112–163 40.73%
unbalance vs Hwoarang 144–121 54.34%
unbalance vs Jin 103–138 42.74%
unbalance vs Reina 100–137 42.19%
unbalance vs King 87–141 38.16%
unbalance vs Asuka 90–113 44.33%
unbalance vs Lili 102–94 52.04%
unbalance vs Steve 72–116 38.30%
unbalance vs Victor 55–89 38.19%
unbalance vs Jun 72–67 51.80%
unbalance vs Heihachi 51–87 36.96%
unbalance vs Law 38–88 30.16%
unbalance vs Azucena 57–69 45.24%
unbalance vs Devil Jin 56–65 46.28%
unbalance vs Nina 48–65 42.48%
unbalance vs Lidia 55–48 53.40%
unbalance vs Yoshimitsu 51–51 50.00%
unbalance vs Leo 45–53 45.92%
unbalance vs Xiaoyu 34–62 35.42%
unbalance vs Leroy 42–53 44.21%
unbalance vs Feng 36–51 41.38%
unbalance vs Clive 31–52 37.35%
unbalance vs Alisa 23–52 30.67%
unbalance vs Claudio 37–37 50.00%
unbalance vs Lars 18–53 25.35%
unbalance vs Lee 24–43 35.82%
unbalance vs Eddy 21–38 35.59%
unbalance vs Jack-8 26–29 47.27%
unbalance vs Shaheen 11–38 22.45%
unbalance vs Zafina 21–24 46.67%
unbalance vs Kuma 16–28 36.36%
unbalance vs Raven 14–16 46.67%
unbalance vs Panda 12–11 52.17%
unbalance vs Anna 12–8 60.00%

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.