Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics

Ratings

Monster vs Kazuya 195–234 45.45%
Monster vs King 175–246 41.57%
Monster vs Jin 128–233 35.46%
Monster vs Steve 153–199 43.47%
Monster vs Reina 135–199 40.42%
Monster vs Lidia 155–175 46.97%
Monster vs Bryan 105–208 33.55%
Monster vs Law 117–183 39.00%
Monster vs Hwoarang 107–159 40.23%
Monster vs Heihachi 125–138 47.53%
Monster vs Clive 95–138 40.77%
Monster vs Dragunov 84–137 38.01%
Monster vs Eddy 60–147 28.99%
Monster vs Asuka 84–120 41.18%
Monster vs Azucena 85–113 42.93%
Monster vs Jun 82–115 41.62%
Monster vs Lili 83–111 42.78%
Monster vs Paul 75–102 42.37%
Monster vs Victor 76–100 43.18%
Monster vs Lee 71–103 40.80%
Monster vs Yoshimitsu 81–92 46.82%
Monster vs Lars 57–102 35.85%
Monster vs Nina 57–100 36.31%
Monster vs Feng 54–79 40.60%
Monster vs Xiaoyu 58–74 43.94%
Monster vs Leo 57–74 43.51%
Monster vs Leroy 50–73 40.65%
Monster vs Devil Jin 44–71 38.26%
Monster vs Jack-8 44–68 39.29%
Monster vs Alisa 30–66 31.25%
Monster vs Claudio 34–60 36.17%
Monster vs Zafina 31–50 38.27%
Monster vs Raven 41–36 53.25%
Monster vs Kuma 26–46 36.11%
Monster vs Armor King 21–47 30.88%
Monster vs Miary Zo 26–42 38.24%
Monster vs Fahkumram 32–33 49.23%
Monster vs Shaheen 21–40 34.43%
Monster vs Panda 18–23 43.90%
Monster vs Anna 15–20 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.