| Wiceman100 vs King | 9–16 | 36.00% |
| Wiceman100 vs Kazuya | 7–15 | 31.82% |
| Wiceman100 vs Jin | 4–16 | 20.00% |
| Wiceman100 vs Eddy | 7–13 | 35.00% |
| Wiceman100 vs Steve | 10–8 | 55.56% |
| Wiceman100 vs Reina | 6–11 | 35.29% |
| Wiceman100 vs Hwoarang | 6–10 | 37.50% |
| Wiceman100 vs Lee | 6–8 | 42.86% |
| Wiceman100 vs Law | 3–9 | 25.00% |
| Wiceman100 vs Xiaoyu | 2–10 | 16.67% |
| Wiceman100 vs Dragunov | 4–7 | 36.36% |
| Wiceman100 vs Lili | 4–6 | 40.00% |
| Wiceman100 vs Azucena | 6–4 | 60.00% |
| Wiceman100 vs Alisa | 0–9 | 0.00% |
| Wiceman100 vs Kuma | 2–7 | 22.22% |
| Wiceman100 vs Asuka | 4–4 | 50.00% |
| Wiceman100 vs Devil Jin | 3–5 | 37.50% |
| Wiceman100 vs Lars | 4–4 | 50.00% |
| Wiceman100 vs Yoshimitsu | 7–0 | 100.00% |
| Wiceman100 vs Bryan | 4–3 | 57.14% |
| Wiceman100 vs Jun | 3–4 | 42.86% |
| Wiceman100 vs Jack-8 | 4–2 | 66.67% |
| Wiceman100 vs Leroy | 1–5 | 16.67% |
| Wiceman100 vs Victor | 4–2 | 66.67% |
| Wiceman100 vs Raven | 2–4 | 33.33% |
| Wiceman100 vs Feng | 4–1 | 80.00% |
| Wiceman100 vs Claudio | 4–1 | 80.00% |
| Wiceman100 vs Nina | 3–2 | 60.00% |
| Wiceman100 vs Paul | 2–2 | 50.00% |
| Wiceman100 vs Panda | 2–2 | 50.00% |
| Wiceman100 vs Leo | 0–2 | 0.00% |
| Wiceman100 vs Shaheen | 0–2 | 0.00% |
| Wiceman100 vs Zafina | 0–1 | 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.