| 10연승하면끔 vs Kazuya | 70–121 | 36.65% |
| 10연승하면끔 vs Dragunov | 70–107 | 39.55% |
| 10연승하면끔 vs Reina | 70–105–1 | 40.00% |
| 10연승하면끔 vs Hwoarang | 44–109 | 28.76% |
| 10연승하면끔 vs King | 49–93 | 34.51% |
| 10연승하면끔 vs Paul | 50–90 | 35.71% |
| 10연승하면끔 vs Jin | 41–87 | 32.03% |
| 10연승하면끔 vs Bryan | 39–84 | 31.71% |
| 10연승하면끔 vs Asuka | 35–79 | 30.70% |
| 10연승하면끔 vs Lili | 42–71 | 37.17% |
| 10연승하면끔 vs Lidia | 37–73 | 33.64% |
| 10연승하면끔 vs Jun | 34–69 | 33.01% |
| 10연승하면끔 vs Victor | 29–67 | 30.21% |
| 10연승하면끔 vs Azucena | 33–59 | 35.87% |
| 10연승하면끔 vs Steve | 33–55 | 37.50% |
| 10연승하면끔 vs Law | 25–52 | 32.47% |
| 10연승하면끔 vs Yoshimitsu | 24–53 | 31.17% |
| 10연승하면끔 vs Alisa | 14–55 | 20.29% |
| 10연승하면끔 vs Xiaoyu | 17–49 | 25.76% |
| 10연승하면끔 vs Lars | 26–37 | 41.27% |
| 10연승하면끔 vs Feng | 14–44 | 24.14% |
| 10연승하면끔 vs Devil Jin | 19–37 | 33.93% |
| 10연승하면끔 vs Eddy | 8–44 | 15.38% |
| 10연승하면끔 vs Heihachi | 13–37 | 26.00% |
| 10연승하면끔 vs Claudio | 12–34 | 26.09% |
| 10연승하면끔 vs Leroy | 12–31 | 27.91% |
| 10연승하면끔 vs Nina | 7–31 | 18.42% |
| 10연승하면끔 vs Jack-8 | 11–24 | 31.43% |
| 10연승하면끔 vs Lee | 17–18 | 48.57% |
| 10연승하면끔 vs Leo | 16–18 | 47.06% |
| 10연승하면끔 vs Kuma | 3–18 | 14.29% |
| 10연승하면끔 vs Shaheen | 9–7 | 56.25% |
| 10연승하면끔 vs Raven | 6–8 | 42.86% |
| 10연승하면끔 vs Zafina | 7–6 | 53.85% |
| 10연승하면끔 vs Panda | 4–8 | 33.33% |
| 10연승하면끔 vs Clive | 1–8 | 11.11% |
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.