| Mtell22 vs Eddy | 9–13 | 40.91% |
| Mtell22 vs King | 7–2 | 77.78% |
| Mtell22 vs Jin | 4–5 | 44.44% |
| Mtell22 vs Reina | 3–6 | 33.33% |
| Mtell22 vs Law | 6–1 | 85.71% |
| Mtell22 vs Kazuya | 5–1 | 83.33% |
| Mtell22 vs Alisa | 3–3 | 50.00% |
| Mtell22 vs Asuka | 3–1 | 75.00% |
| Mtell22 vs Lee | 4–0 | 100.00% |
| Mtell22 vs Jun | 3–1 | 75.00% |
| Mtell22 vs Steve | 1–2 | 33.33% |
| Mtell22 vs Feng | 2–1 | 66.67% |
| Mtell22 vs Victor | 3–0 | 100.00% |
| Mtell22 vs Paul | 2–0 | 100.00% |
| Mtell22 vs Lili | 2–0 | 100.00% |
| Mtell22 vs Claudio | 0–2 | 0.00% |
| Mtell22 vs Kuma | 0–2 | 0.00% |
| Mtell22 vs Hwoarang | 1–0 | 100.00% |
| Mtell22 vs Nina | 1–0 | 100.00% |
| Mtell22 vs Panda | 1–0 | 100.00% |
| Mtell22 vs Azucena | 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.