Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

nether vs Eddy 19–43 30.65%
nether vs King 17–11 60.71%
nether vs Reina 13–15 46.43%
nether vs Jin 9–12 42.86%
nether vs Dragunov 6–14 30.00%
nether vs Yoshimitsu 7–12 36.84%
nether vs Kazuya 5–12 29.41%
nether vs Lars 9–7 56.25%
nether vs Nina 6–9 40.00%
nether vs Kuma 6–8 42.86%
nether vs Xiaoyu 6–7 46.15%
nether vs Feng 5–8 38.46%
nether vs Hwoarang 8–4 66.67%
nether vs Steve 4–8 33.33%
nether vs Azucena 5–7 41.67%
nether vs Asuka 8–3 72.73%
nether vs Jun 1–10 9.09%
nether vs Claudio 4–5 44.44%
nether vs Lee 4–5 44.44%
nether vs Bryan 1–7 12.50%
nether vs Lili 3–5 37.50%
nether vs Jack-8 1–6 14.29%
nether vs Alisa 5–2 71.43%
nether vs Victor 4–3 57.14%
nether vs Zafina 0–6 0.00%
nether vs Leroy 4–2 66.67%
nether vs Law 4–1 80.00%
nether vs Paul 1–3 25.00%
nether vs Leo 4–0 100.00%
nether vs Shaheen 2–2 50.00%
nether vs Devil Jin 0–2 0.00%
nether vs Panda 1–1 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.