Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

TMB Slang vs King 15–25 37.50%
TMB Slang vs Kazuya 8–13 38.10%
TMB Slang vs Law 5–14 26.32%
TMB Slang vs Steve 14–5 73.68%
TMB Slang vs Reina 8–11 42.11%
TMB Slang vs Hwoarang 7–11 38.89%
TMB Slang vs Jin 6–12 33.33%
TMB Slang vs Jun 5–11 31.25%
TMB Slang vs Alisa 9–5 64.29%
TMB Slang vs Azucena 11–2 84.62%
TMB Slang vs Asuka 4–8 33.33%
TMB Slang vs Dragunov 1–9 10.00%
TMB Slang vs Clive 6–4 60.00%
TMB Slang vs Devil Jin 5–4 55.56%
TMB Slang vs Fahkumram 3–6 33.33%
TMB Slang vs Paul 2–6 25.00%
TMB Slang vs Victor 2–6 25.00%
TMB Slang vs Xiaoyu 1–6 14.29%
TMB Slang vs Lidia 4–2 66.67%
TMB Slang vs Bryan 1–4 20.00%
TMB Slang vs Leo 3–2 60.00%
TMB Slang vs Nina 3–2 60.00%
TMB Slang vs Lee 3–2 60.00%
TMB Slang vs Leroy 1–4 20.00%
TMB Slang vs Miary Zo 1–4 20.00%
TMB Slang vs Zafina 4–0 100.00%
TMB Slang vs Eddy 1–3 25.00%
TMB Slang vs Heihachi 1–3 25.00%
TMB Slang vs Yoshimitsu 1–2 33.33%
TMB Slang vs Shaheen 0–3 0.00%
TMB Slang vs Feng 0–2 0.00%
TMB Slang vs Anna 0–2 0.00%
TMB Slang vs Armor King 0–2 0.00%
TMB Slang vs Lili 0–1 0.00%
TMB Slang vs Lars 0–1 0.00%
TMB Slang vs Kuma 0–1 0.00%
TMB Slang vs Raven 0–1 0.00%

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.