| PIMPxEASTWOOD vs Kazuya | 25–27 | 48.08% |
| PIMPxEASTWOOD vs Jin | 19–27 | 41.30% |
| PIMPxEASTWOOD vs King | 22–23 | 48.89% |
| PIMPxEASTWOOD vs Reina | 19–14 | 57.58% |
| PIMPxEASTWOOD vs Yoshimitsu | 13–14 | 48.15% |
| PIMPxEASTWOOD vs Bryan | 14–13 | 51.85% |
| PIMPxEASTWOOD vs Eddy | 10–17 | 37.04% |
| PIMPxEASTWOOD vs Steve | 13–11 | 54.17% |
| PIMPxEASTWOOD vs Asuka | 9–14 | 39.13% |
| PIMPxEASTWOOD vs Jun | 18–3 | 85.71% |
| PIMPxEASTWOOD vs Law | 11–9 | 55.00% |
| PIMPxEASTWOOD vs Hwoarang | 9–9 | 50.00% |
| PIMPxEASTWOOD vs Paul | 9–8 | 52.94% |
| PIMPxEASTWOOD vs Raven | 5–9 | 35.71% |
| PIMPxEASTWOOD vs Armor King | 8–6 | 57.14% |
| PIMPxEASTWOOD vs Lili | 5–8 | 38.46% |
| PIMPxEASTWOOD vs Feng | 4–8 | 33.33% |
| PIMPxEASTWOOD vs Victor | 5–7 | 41.67% |
| PIMPxEASTWOOD vs Nina | 6–5 | 54.55% |
| PIMPxEASTWOOD vs Azucena | 8–3 | 72.73% |
| PIMPxEASTWOOD vs Panda | 6–3 | 66.67% |
| PIMPxEASTWOOD vs Devil Jin | 6–2 | 75.00% |
| PIMPxEASTWOOD vs Dragunov | 6–2 | 75.00% |
| PIMPxEASTWOOD vs Leo | 4–4 | 50.00% |
| PIMPxEASTWOOD vs Lars | 4–4 | 50.00% |
| PIMPxEASTWOOD vs Lee | 6–2 | 75.00% |
| PIMPxEASTWOOD vs Xiaoyu | 4–3 | 57.14% |
| PIMPxEASTWOOD vs Leroy | 2–5 | 28.57% |
| PIMPxEASTWOOD vs Lidia | 2–3 | 40.00% |
| PIMPxEASTWOOD vs Jack-8 | 0–4 | 0.00% |
| PIMPxEASTWOOD vs Claudio | 3–1 | 75.00% |
| PIMPxEASTWOOD vs Clive | 2–2 | 50.00% |
| PIMPxEASTWOOD vs Shaheen | 0–3 | 0.00% |
| PIMPxEASTWOOD vs Heihachi | 1–2 | 33.33% |
| PIMPxEASTWOOD vs Fahkumram | 3–0 | 100.00% |
| PIMPxEASTWOOD vs Alisa | 0–2 | 0.00% |
| PIMPxEASTWOOD vs Kuma | 0–2 | 0.00% |
| PIMPxEASTWOOD vs Anna | 1–0 | 100.00% |
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.