Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

Meat Damage vs Bryan 21–14 60.00%
Meat Damage vs King 20–10 66.67%
Meat Damage vs Xiaoyu 14–9 60.87%
Meat Damage vs Steve 16–7 69.57%
Meat Damage vs Feng 12–10 54.55%
Meat Damage vs Dragunov 14–7 66.67%
Meat Damage vs Law 9–11 45.00%
Meat Damage vs Azucena 16–4 80.00%
Meat Damage vs Lili 13–5 72.22%
Meat Damage vs Lee 11–7 61.11%
Meat Damage vs Reina 9–9 50.00%
Meat Damage vs Victor 11–7 61.11%
Meat Damage vs Paul 9–8 52.94%
Meat Damage vs Hwoarang 8–9 47.06%
Meat Damage vs Jin 12–5 70.59%
Meat Damage vs Kazuya 12–5 70.59%
Meat Damage vs Jun 10–6 62.50%
Meat Damage vs Alisa 9–5 64.29%
Meat Damage vs Nina 11–2 84.62%
Meat Damage vs Kuma 7–6 53.85%
Meat Damage vs Lars 5–7 41.67%
Meat Damage vs Asuka 7–4 63.64%
Meat Damage vs Yoshimitsu 6–4 60.00%
Meat Damage vs Jack-8 4–5 44.44%
Meat Damage vs Devil Jin 5–3 62.50%
Meat Damage vs Heihachi 6–2 75.00%
Meat Damage vs Claudio 4–3 57.14%
Meat Damage vs Raven 3–4 42.86%
Meat Damage vs Zafina 5–1 83.33%
Meat Damage vs Shaheen 2–2 50.00%
Meat Damage vs Panda 1–3 25.00%
Meat Damage vs Clive 1–3 25.00%
Meat Damage vs Anna 3–1 75.00%
Meat Damage vs Leroy 2–1 66.67%
Meat Damage vs Lidia 2–1 66.67%
Meat Damage vs Leo 2–0 100.00%
Meat Damage vs Eddy 2–0 100.00%
Meat Damage vs Fahkumram 2–0 100.00%

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.