| CHIMP_ vs Jin | 28–42 | 40.00% |
| CHIMP_ vs Bryan | 26–38 | 40.62% |
| CHIMP_ vs King | 26–35 | 42.62% |
| CHIMP_ vs Kazuya | 20–37 | 35.09% |
| CHIMP_ vs Steve | 23–33 | 41.07% |
| CHIMP_ vs Reina | 23–33 | 41.07% |
| CHIMP_ vs Dragunov | 9–45 | 16.67% |
| CHIMP_ vs Clive | 14–31 | 31.11% |
| CHIMP_ vs Hwoarang | 14–25 | 35.90% |
| CHIMP_ vs Law | 9–24 | 27.27% |
| CHIMP_ vs Lars | 8–20 | 28.57% |
| CHIMP_ vs Xiaoyu | 13–14 | 48.15% |
| CHIMP_ vs Claudio | 7–20 | 25.93% |
| CHIMP_ vs Devil Jin | 6–20 | 23.08% |
| CHIMP_ vs Azucena | 7–18 | 28.00% |
| CHIMP_ vs Lili | 6–17 | 26.09% |
| CHIMP_ vs Jun | 8–15 | 34.78% |
| CHIMP_ vs Paul | 8–10 | 44.44% |
| CHIMP_ vs Yoshimitsu | 5–13 | 27.78% |
| CHIMP_ vs Asuka | 8–10 | 44.44% |
| CHIMP_ vs Alisa | 3–15 | 16.67% |
| CHIMP_ vs Kuma | 8–9 | 47.06% |
| CHIMP_ vs Heihachi | 5–12 | 29.41% |
| CHIMP_ vs Victor | 7–9 | 43.75% |
| CHIMP_ vs Lidia | 2–12 | 14.29% |
| CHIMP_ vs Leroy | 6–6 | 50.00% |
| CHIMP_ vs Anna | 3–9 | 25.00% |
| CHIMP_ vs Nina | 2–9 | 18.18% |
| CHIMP_ vs Lee | 3–7 | 30.00% |
| CHIMP_ vs Eddy | 1–9 | 10.00% |
| CHIMP_ vs Leo | 2–6 | 25.00% |
| CHIMP_ vs Panda | 2–4 | 33.33% |
| CHIMP_ vs Raven | 1–5 | 16.67% |
| CHIMP_ vs Jack-8 | 2–3 | 40.00% |
| CHIMP_ vs Shaheen | 1–4 | 20.00% |
| CHIMP_ vs Feng | 0–2 | 0.00% |
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.