Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

NixlFeim vs Kazuya 95–69 57.93%
NixlFeim vs Jin 90–54 62.50%
NixlFeim vs Bryan 78–58 57.35%
NixlFeim vs King 82–52 61.19%
NixlFeim vs Reina 73–36 66.97%
NixlFeim vs Hwoarang 45–49 47.87%
NixlFeim vs Dragunov 45–47 48.91%
NixlFeim vs Law 61–28 68.54%
NixlFeim vs Devil Jin 45–43 51.14%
NixlFeim vs Paul 44–43 50.57%
NixlFeim vs Heihachi 44–42 51.16%
NixlFeim vs Steve 43–35 55.13%
NixlFeim vs Yoshimitsu 43–32 57.33%
NixlFeim vs Anna 43–29 59.72%
NixlFeim vs Lili 41–26 61.19%
NixlFeim vs Lars 30–20 60.00%
NixlFeim vs Asuka 23–23 50.00%
NixlFeim vs Jun 30–16 65.22%
NixlFeim vs Lee 12–33 26.67%
NixlFeim vs Claudio 28–15 65.12%
NixlFeim vs Azucena 25–18 58.14%
NixlFeim vs Miary Zo 19–23 45.24%
NixlFeim vs Feng 24–17 58.54%
NixlFeim vs Armor King 19–19 50.00%
NixlFeim vs Alisa 24–10 70.59%
NixlFeim vs Jack-8 15–18 45.45%
NixlFeim vs Nina 19–14 57.58%
NixlFeim vs Victor 15–18 45.45%
NixlFeim vs Leo 10–21 32.26%
NixlFeim vs Lidia 14–15 48.28%
NixlFeim vs Clive 19–7 73.08%
NixlFeim vs Xiaoyu 14–9 60.87%
NixlFeim vs Leroy 9–14 39.13%
NixlFeim vs Eddy 14–9 60.87%
NixlFeim vs Raven 10–10 50.00%
NixlFeim vs Zafina 4–15 21.05%
NixlFeim vs Kuma 12–5 70.59%
NixlFeim vs Fahkumram 7–10 41.18%
NixlFeim vs Shaheen 4–8 33.33%
NixlFeim vs Panda 3–4 42.86%

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.