| X_Seawolff_X vs King | 20–11 | 64.52% |
| X_Seawolff_X vs Reina | 19–3 | 86.36% |
| X_Seawolff_X vs Bryan | 8–7 | 53.33% |
| X_Seawolff_X vs Jun | 12–3 | 80.00% |
| X_Seawolff_X vs Devil Jin | 7–6 | 53.85% |
| X_Seawolff_X vs Eddy | 11–2 | 84.62% |
| X_Seawolff_X vs Kazuya | 10–2 | 83.33% |
| X_Seawolff_X vs Jin | 8–3 | 72.73% |
| X_Seawolff_X vs Asuka | 9–2 | 81.82% |
| X_Seawolff_X vs Lars | 7–3 | 70.00% |
| X_Seawolff_X vs Hwoarang | 6–3 | 66.67% |
| X_Seawolff_X vs Lili | 5–4 | 55.56% |
| X_Seawolff_X vs Nina | 7–2 | 77.78% |
| X_Seawolff_X vs Law | 2–6 | 25.00% |
| X_Seawolff_X vs Steve | 6–2 | 75.00% |
| X_Seawolff_X vs Xiaoyu | 4–3 | 57.14% |
| X_Seawolff_X vs Lee | 6–1 | 85.71% |
| X_Seawolff_X vs Victor | 6–1 | 85.71% |
| X_Seawolff_X vs Jack-8 | 3–3 | 50.00% |
| X_Seawolff_X vs Paul | 2–3 | 40.00% |
| X_Seawolff_X vs Yoshimitsu | 5–0 | 100.00% |
| X_Seawolff_X vs Dragunov | 3–2 | 60.00% |
| X_Seawolff_X vs Alisa | 1–4 | 20.00% |
| X_Seawolff_X vs Claudio | 3–2 | 60.00% |
| X_Seawolff_X vs Shaheen | 2–2 | 50.00% |
| X_Seawolff_X vs Azucena | 2–2 | 50.00% |
| X_Seawolff_X vs Lidia | 2–2 | 50.00% |
| X_Seawolff_X vs Heihachi | 2–2 | 50.00% |
| X_Seawolff_X vs Clive | 2–1 | 66.67% |
| X_Seawolff_X vs Panda | 2–0 | 100.00% |
| X_Seawolff_X vs Raven | 1–0 | 100.00% |
| X_Seawolff_X vs Fahkumram | 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.