Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics
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Ratings

Name history

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쿠마 못해먹겠네
팬더 못해먹겠네
日本人は一ゲームだけして去る
KUMA
팬더빼고 다 사기케임
*(0ㅅ0)*
팬더참귀여운데표현할방법이없네
백구 ^(-ㅅ-)^
*(0ㅅ0)* ^(-ㅅ-)^
*(oㅅo)* ^(-ㅅ-)^
Mooserwer(-ㅅ-)
^(-ㅅ-)^ *(0ㅅ0)* vs King 69–49 58.47%
^(-ㅅ-)^ *(0ㅅ0)* vs Hwoarang 57–55 50.89%
^(-ㅅ-)^ *(0ㅅ0)* vs Bryan 50–56 47.17%
^(-ㅅ-)^ *(0ㅅ0)* vs Dragunov 40–58 40.82%
^(-ㅅ-)^ *(0ㅅ0)* vs Yoshimitsu 46–40–1 53.49%
^(-ㅅ-)^ *(0ㅅ0)* vs Jin 41–42 49.40%
^(-ㅅ-)^ *(0ㅅ0)* vs Azucena 42–39 51.85%
^(-ㅅ-)^ *(0ㅅ0)* vs Reina 39–38 50.65%
^(-ㅅ-)^ *(0ㅅ0)* vs Kazuya 39–37 51.32%
^(-ㅅ-)^ *(0ㅅ0)* vs Law 42–31 57.53%
^(-ㅅ-)^ *(0ㅅ0)* vs Paul 46–26 63.89%
^(-ㅅ-)^ *(0ㅅ0)* vs Feng 28–37 43.08%
^(-ㅅ-)^ *(0ㅅ0)* vs Asuka 37–24 60.66%
^(-ㅅ-)^ *(0ㅅ0)* vs Nina 30–30 50.00%
^(-ㅅ-)^ *(0ㅅ0)* vs Victor 21–36 36.84%
^(-ㅅ-)^ *(0ㅅ0)* vs Steve 32–21 60.38%
^(-ㅅ-)^ *(0ㅅ0)* vs Lars 28–24 53.85%
^(-ㅅ-)^ *(0ㅅ0)* vs Lili 22–29 43.14%
^(-ㅅ-)^ *(0ㅅ0)* vs Jun 22–26 45.83%
^(-ㅅ-)^ *(0ㅅ0)* vs Jack-8 18–29 38.30%
^(-ㅅ-)^ *(0ㅅ0)* vs Alisa 16–27 37.21%
^(-ㅅ-)^ *(0ㅅ0)* vs Lee 24–16 60.00%
^(-ㅅ-)^ *(0ㅅ0)* vs Devil Jin 23–14 62.16%
^(-ㅅ-)^ *(0ㅅ0)* vs Xiaoyu 19–16 54.29%
^(-ㅅ-)^ *(0ㅅ0)* vs Zafina 21–14 60.00%
^(-ㅅ-)^ *(0ㅅ0)* vs Eddy 16–19 45.71%
^(-ㅅ-)^ *(0ㅅ0)* vs Leo 16–18 47.06%
^(-ㅅ-)^ *(0ㅅ0)* vs Claudio 16–11 59.26%
^(-ㅅ-)^ *(0ㅅ0)* vs Shaheen 15–11 57.69%
^(-ㅅ-)^ *(0ㅅ0)* vs Leroy 15–11 57.69%
^(-ㅅ-)^ *(0ㅅ0)* vs Raven 13–11 54.17%
^(-ㅅ-)^ *(0ㅅ0)* vs Kuma 10–6 62.50%
^(-ㅅ-)^ *(0ㅅ0)* vs Lidia 7–3 70.00%
^(-ㅅ-)^ *(0ㅅ0)* vs Panda 1–3 25.00%
^(-ㅅ-)^ *(0ㅅ0)* vs Heihachi 2–2 50.00%

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.