| MiVidaLoca vs Kazuya | 44–66 | 40.00% |
| MiVidaLoca vs Jin | 53–54 | 49.53% |
| MiVidaLoca vs King | 56–40 | 58.33% |
| MiVidaLoca vs Reina | 43–32 | 57.33% |
| MiVidaLoca vs Bryan | 39–24 | 61.90% |
| MiVidaLoca vs Lili | 33–21 | 61.11% |
| MiVidaLoca vs Hwoarang | 26–25 | 50.98% |
| MiVidaLoca vs Dragunov | 33–18 | 64.71% |
| MiVidaLoca vs Steve | 23–21 | 52.27% |
| MiVidaLoca vs Law | 24–18 | 57.14% |
| MiVidaLoca vs Paul | 21–20 | 51.22% |
| MiVidaLoca vs Yoshimitsu | 22–18 | 55.00% |
| MiVidaLoca vs Jun | 18–18 | 50.00% |
| MiVidaLoca vs Azucena | 17–12 | 58.62% |
| MiVidaLoca vs Eddy | 13–15 | 46.43% |
| MiVidaLoca vs Lars | 13–14 | 48.15% |
| MiVidaLoca vs Leroy | 12–14 | 46.15% |
| MiVidaLoca vs Lee | 12–13 | 48.00% |
| MiVidaLoca vs Victor | 15–10 | 60.00% |
| MiVidaLoca vs Nina | 11–13 | 45.83% |
| MiVidaLoca vs Feng | 9–14 | 39.13% |
| MiVidaLoca vs Devil Jin | 12–10 | 54.55% |
| MiVidaLoca vs Heihachi | 9–13 | 40.91% |
| MiVidaLoca vs Xiaoyu | 9–12 | 42.86% |
| MiVidaLoca vs Alisa | 11–9 | 55.00% |
| MiVidaLoca vs Lidia | 9–10 | 47.37% |
| MiVidaLoca vs Asuka | 10–7 | 58.82% |
| MiVidaLoca vs Leo | 7–6 | 53.85% |
| MiVidaLoca vs Claudio | 8–5 | 61.54% |
| MiVidaLoca vs Panda | 8–5 | 61.54% |
| MiVidaLoca vs Jack-8 | 5–7 | 41.67% |
| MiVidaLoca vs Clive | 5–6 | 45.45% |
| MiVidaLoca vs Zafina | 5–5 | 50.00% |
| MiVidaLoca vs Kuma | 3–6 | 33.33% |
| MiVidaLoca vs Raven | 3–5 | 37.50% |
| MiVidaLoca vs Shaheen | 1–4 | 20.00% |
| MiVidaLoca vs Fahkumram | 1–1 | 50.00% |
| MiVidaLoca vs Armor King | 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.