Wavu Wank

TEKKEN® 8 glicko2 Ratings &
Online Ranked Statistics
MikefromSTL

Ratings

MikefromSTL vs Jin 136–113 54.62%
MikefromSTL vs Hwoarang 112–87 56.28%
MikefromSTL vs Law 117–64 64.64%
MikefromSTL vs King 112–62 64.37%
MikefromSTL vs Reina 88–81 52.07%
MikefromSTL vs Dragunov 89–76 53.94%
MikefromSTL vs Kazuya 101–61 62.35%
MikefromSTL vs Lili 79–83 48.77%
MikefromSTL vs Bryan 100–59 62.89%
MikefromSTL vs Lars 91–61 59.87%
MikefromSTL vs Jun 85–67 55.92%
MikefromSTL vs Steve 99–52 65.56%
MikefromSTL vs Lee 89–61 59.33%
MikefromSTL vs Victor 77–67 53.47%
MikefromSTL vs Xiaoyu 74–54 57.81%
MikefromSTL vs Yoshimitsu 57–69 45.24%
MikefromSTL vs Paul 87–35 71.31%
MikefromSTL vs Leo 71–49 59.17%
MikefromSTL vs Eddy 57–63 47.50%
MikefromSTL vs Alisa 56–55 50.45%
MikefromSTL vs Azucena 54–57 48.65%
MikefromSTL vs Devil Jin 73–37 66.36%
MikefromSTL vs Nina 63–44 58.88%
MikefromSTL vs Feng 65–36 64.36%
MikefromSTL vs Asuka 62–33 65.26%
MikefromSTL vs Raven 47–32 59.49%
MikefromSTL vs Jack-8 56–17 76.71%
MikefromSTL vs Kuma 40–31 56.34%
MikefromSTL vs Zafina 43–27 61.43%
MikefromSTL vs Leroy 35–34 50.72%
MikefromSTL vs Shaheen 35–27 56.45%
MikefromSTL vs Lidia 26–36 41.94%
MikefromSTL vs Heihachi 30–32 48.39%
MikefromSTL vs Claudio 28–24 53.85%
MikefromSTL vs Panda 16–16 50.00%
MikefromSTL vs Clive 15–13 53.57%

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.