| SlaNaaC vs Kazuya | 200–206 | 49.26% |
| SlaNaaC vs Bryan | 199–128 | 60.86% |
| SlaNaaC vs Jin | 139–137 | 50.36% |
| SlaNaaC vs Reina | 149–101 | 59.60% |
| SlaNaaC vs Fahkumram | 146–98 | 59.84% |
| SlaNaaC vs Dragunov | 118–95 | 55.40% |
| SlaNaaC vs Devil Jin | 99–109 | 47.60% |
| SlaNaaC vs Paul | 104–102 | 50.49% |
| SlaNaaC vs Yoshimitsu | 105–89 | 54.12% |
| SlaNaaC vs Heihachi | 98–94 | 51.04% |
| SlaNaaC vs Hwoarang | 93–94 | 49.73% |
| SlaNaaC vs Law | 95–80 | 54.29% |
| SlaNaaC vs Steve | 92–76 | 54.76% |
| SlaNaaC vs Lili | 77–91 | 45.83% |
| SlaNaaC vs King | 69–79 | 46.62% |
| SlaNaaC vs Azucena | 88–58 | 60.27% |
| SlaNaaC vs Lee | 79–66 | 54.48% |
| SlaNaaC vs Victor | 67–49 | 57.76% |
| SlaNaaC vs Armor King | 62–49 | 55.86% |
| SlaNaaC vs Asuka | 51–59 | 46.36% |
| SlaNaaC vs Alisa | 55–54 | 50.46% |
| SlaNaaC vs Jun | 55–53 | 50.93% |
| SlaNaaC vs Lars | 51–54 | 48.57% |
| SlaNaaC vs Nina | 59–44 | 57.28% |
| SlaNaaC vs Leo | 58–42 | 58.00% |
| SlaNaaC vs Feng | 34–62 | 35.42% |
| SlaNaaC vs Xiaoyu | 53–37 | 58.89% |
| SlaNaaC vs Jack-8 | 37–47 | 44.05% |
| SlaNaaC vs Lidia | 39–40 | 49.37% |
| SlaNaaC vs Claudio | 31–43 | 41.89% |
| SlaNaaC vs Leroy | 40–30 | 57.14% |
| SlaNaaC vs Shaheen | 40–26 | 60.61% |
| SlaNaaC vs Zafina | 29–29 | 50.00% |
| SlaNaaC vs Eddy | 27–28 | 49.09% |
| SlaNaaC vs Raven | 27–27 | 50.00% |
| SlaNaaC vs Clive | 21–32 | 39.62% |
| SlaNaaC vs Kuma | 26–16 | 61.90% |
| SlaNaaC vs Anna | 15–20 | 42.86% |
| SlaNaaC vs Panda | 11–11 | 50.00% |
| SlaNaaC vs Miary Zo | 5–6 | 45.45% |
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.