| Harsh_Legend vs Bryan | 25–7 | 78.12% |
| Harsh_Legend vs King | 15–7 | 68.18% |
| Harsh_Legend vs Kazuya | 17–4 | 80.95% |
| Harsh_Legend vs Reina | 14–5 | 73.68% |
| Harsh_Legend vs Hwoarang | 12–5 | 70.59% |
| Harsh_Legend vs Jin | 12–5 | 70.59% |
| Harsh_Legend vs Clive | 12–5 | 70.59% |
| Harsh_Legend vs Law | 9–4 | 69.23% |
| Harsh_Legend vs Asuka | 8–3 | 72.73% |
| Harsh_Legend vs Devil Jin | 7–2 | 77.78% |
| Harsh_Legend vs Steve | 7–1 | 87.50% |
| Harsh_Legend vs Lars | 6–2 | 75.00% |
| Harsh_Legend vs Xiaoyu | 6–1 | 85.71% |
| Harsh_Legend vs Lili | 7–0 | 100.00% |
| Harsh_Legend vs Leroy | 1–6 | 14.29% |
| Harsh_Legend vs Jun | 6–1 | 85.71% |
| Harsh_Legend vs Heihachi | 7–0 | 100.00% |
| Harsh_Legend vs Yoshimitsu | 3–3 | 50.00% |
| Harsh_Legend vs Feng | 3–3 | 50.00% |
| Harsh_Legend vs Leo | 4–2 | 66.67% |
| Harsh_Legend vs Jack-8 | 3–2 | 60.00% |
| Harsh_Legend vs Dragunov | 5–0 | 100.00% |
| Harsh_Legend vs Nina | 4–1 | 80.00% |
| Harsh_Legend vs Lee | 3–2 | 60.00% |
| Harsh_Legend vs Paul | 2–2 | 50.00% |
| Harsh_Legend vs Azucena | 4–0 | 100.00% |
| Harsh_Legend vs Victor | 4–0 | 100.00% |
| Harsh_Legend vs Lidia | 2–2 | 50.00% |
| Harsh_Legend vs Anna | 2–2 | 50.00% |
| Harsh_Legend vs Alisa | 2–1 | 66.67% |
| Harsh_Legend vs Raven | 1–2 | 33.33% |
| Harsh_Legend vs Fahkumram | 2–0 | 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.