| simsim vs Kazuya | 51–67 | 43.22% |
| simsim vs Jin | 42–48 | 46.67% |
| simsim vs King | 42–40 | 51.22% |
| simsim vs Bryan | 39–30 | 56.52% |
| simsim vs Steve | 35–28 | 55.56% |
| simsim vs Heihachi | 33–29 | 53.23% |
| simsim vs Hwoarang | 20–31 | 39.22% |
| simsim vs Dragunov | 26–25 | 50.98% |
| simsim vs Reina | 22–27 | 44.90% |
| simsim vs Yoshimitsu | 21–16 | 56.76% |
| simsim vs Law | 13–21 | 38.24% |
| simsim vs Jun | 10–23 | 30.30% |
| simsim vs Paul | 9–13 | 40.91% |
| simsim vs Devil Jin | 14–6 | 70.00% |
| simsim vs Feng | 8–12 | 40.00% |
| simsim vs Alisa | 9–9 | 50.00% |
| simsim vs Victor | 7–10 | 41.18% |
| simsim vs Asuka | 7–9 | 43.75% |
| simsim vs Lars | 9–6 | 60.00% |
| simsim vs Raven | 5–10 | 33.33% |
| simsim vs Lili | 10–4 | 71.43% |
| simsim vs Clive | 5–9 | 35.71% |
| simsim vs Eddy | 6–7 | 46.15% |
| simsim vs Nina | 7–5 | 58.33% |
| simsim vs Lee | 7–5 | 58.33% |
| simsim vs Leo | 5–5 | 50.00% |
| simsim vs Claudio | 1–9 | 10.00% |
| simsim vs Azucena | 2–7 | 22.22% |
| simsim vs Jack-8 | 3–4 | 42.86% |
| simsim vs Kuma | 4–3 | 57.14% |
| simsim vs Leroy | 2–5 | 28.57% |
| simsim vs Xiaoyu | 2–4 | 33.33% |
| simsim vs Shaheen | 2–3 | 40.00% |
| simsim vs Lidia | 2–3 | 40.00% |
| simsim vs Zafina | 1–3 | 25.00% |
| simsim vs Anna | 2–1 | 66.67% |
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.