Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics
unbalance

Ratings

Name history

unbalance
hi 777
unbalance vs Dragunov 116–177 39.59%
unbalance vs Kazuya 125–143 46.64%
unbalance vs Paul 118–116 50.43%
unbalance vs Reina 88–122 41.90%
unbalance vs Hwoarang 104–93 52.79%
unbalance vs Bryan 75–109 40.76%
unbalance vs Jin 74–93 44.31%
unbalance vs King 57–99 36.54%
unbalance vs Lili 75–80 48.39%
unbalance vs Asuka 64–89 41.83%
unbalance vs Steve 51–91 35.92%
unbalance vs Victor 42–74 36.21%
unbalance vs Jun 58–57 50.43%
unbalance vs Devil Jin 48–56 46.15%
unbalance vs Azucena 44–55 44.44%
unbalance vs Heihachi 34–63 35.05%
unbalance vs Nina 37–51 42.05%
unbalance vs Law 23–61 27.38%
unbalance vs Lidia 38–40 48.72%
unbalance vs Leo 33–41 44.59%
unbalance vs Feng 29–44 39.73%
unbalance vs Yoshimitsu 34–38 47.22%
unbalance vs Leroy 30–42 41.67%
unbalance vs Xiaoyu 20–41 32.79%
unbalance vs Alisa 20–41 32.79%
unbalance vs Clive 24–36 40.00%
unbalance vs Claudio 28–30 48.28%
unbalance vs Lars 12–36 25.00%
unbalance vs Lee 16–31 34.04%
unbalance vs Jack-8 22–20 52.38%
unbalance vs Eddy 14–26 35.00%
unbalance vs Shaheen 8–28 22.22%
unbalance vs Zafina 16–19 45.71%
unbalance vs Kuma 13–19 40.62%
unbalance vs Raven 13–14 48.15%
unbalance vs Panda 10–8 55.56%

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.