| mubb vs Reina | 53–18 | 74.65% |
| mubb vs Kazuya | 38–28 | 57.58% |
| mubb vs Jin | 26–24 | 52.00% |
| mubb vs Steve | 29–11 | 72.50% |
| mubb vs King | 24–13 | 64.86% |
| mubb vs Lars | 20–16 | 55.56% |
| mubb vs Dragunov | 16–19 | 45.71% |
| mubb vs Heihachi | 26–9 | 74.29% |
| mubb vs Azucena | 25–7 | 78.12% |
| mubb vs Bryan | 16–15 | 51.61% |
| mubb vs Clive | 22–9 | 70.97% |
| mubb vs Hwoarang | 13–16 | 44.83% |
| mubb vs Law | 14–10 | 58.33% |
| mubb vs Lili | 16–8 | 66.67% |
| mubb vs Paul | 12–11 | 52.17% |
| mubb vs Victor | 16–7 | 69.57% |
| mubb vs Lidia | 15–8 | 65.22% |
| mubb vs Devil Jin | 11–6 | 64.71% |
| mubb vs Feng | 7–10 | 41.18% |
| mubb vs Jun | 6–11 | 35.29% |
| mubb vs Asuka | 8–8 | 50.00% |
| mubb vs Lee | 10–6 | 62.50% |
| mubb vs Xiaoyu | 7–8 | 46.67% |
| mubb vs Nina | 8–4 | 66.67% |
| mubb vs Jack-8 | 8–3 | 72.73% |
| mubb vs Alisa | 5–5 | 50.00% |
| mubb vs Eddy | 5–4 | 55.56% |
| mubb vs Anna | 8–1 | 88.89% |
| mubb vs Leo | 4–4 | 50.00% |
| mubb vs Claudio | 2–6 | 25.00% |
| mubb vs Fahkumram | 6–2 | 75.00% |
| mubb vs Yoshimitsu | 4–3 | 57.14% |
| mubb vs Shaheen | 6–0 | 100.00% |
| mubb vs Leroy | 5–0 | 100.00% |
| mubb vs Panda | 2–2 | 50.00% |
| mubb vs Zafina | 1–2 | 33.33% |
| mubb vs Raven | 0–2 | 0.00% |
| mubb vs Kuma | 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.