Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

Lard King vs Kazuya 79–54 59.40%
Lard King vs Bryan 73–56 56.59%
Lard King vs Hwoarang 70–48 59.32%
Lard King vs Jin 59–42 58.42%
Lard King vs Reina 60–34 63.83%
Lard King vs King 44–47 48.35%
Lard King vs Law 53–35 60.23%
Lard King vs Heihachi 45–24 65.22%
Lard King vs Yoshimitsu 30–34 46.88%
Lard King vs Lee 32–31 50.79%
Lard King vs Steve 38–23 62.30%
Lard King vs Paul 29–24 54.72%
Lard King vs Lili 28–24 53.85%
Lard King vs Nina 27–19 58.70%
Lard King vs Asuka 30–14 68.18%
Lard King vs Devil Jin 27–17 61.36%
Lard King vs Feng 24–20 54.55%
Lard King vs Dragunov 20–23 46.51%
Lard King vs Jun 25–17 59.52%
Lard King vs Lars 20–20 50.00%
Lard King vs Victor 11–23 32.35%
Lard King vs Leo 14–19 42.42%
Lard King vs Alisa 17–16 51.52%
Lard King vs Raven 15–16 48.39%
Lard King vs Azucena 18–11 62.07%
Lard King vs Clive 11–15 42.31%
Lard King vs Xiaoyu 10–14 41.67%
Lard King vs Shaheen 7–17 29.17%
Lard King vs Lidia 11–10 52.38%
Lard King vs Zafina 10–10 50.00%
Lard King vs Jack-8 8–9 47.06%
Lard King vs Leroy 10–7 58.82%
Lard King vs Eddy 9–8 52.94%
Lard King vs Claudio 5–9 35.71%
Lard King vs Fahkumram 5–8 38.46%
Lard King vs Miary Zo 9–2 81.82%
Lard King vs Kuma 5–5 50.00%
Lard King vs Anna 4–4 50.00%
Lard King vs Armor King 3–0 100.00%

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.