| Twease vs Heihachi | 44–22 | 66.67% |
| Twease vs King | 29–28 | 50.88% |
| Twease vs Reina | 34–14 | 70.83% |
| Twease vs Dragunov | 28–19 | 59.57% |
| Twease vs Kazuya | 22–19 | 53.66% |
| Twease vs Jin | 28–12 | 70.00% |
| Twease vs Law | 21–9 | 70.00% |
| Twease vs Yoshimitsu | 18–9 | 66.67% |
| Twease vs Bryan | 10–17 | 37.04% |
| Twease vs Devil Jin | 17–10 | 62.96% |
| Twease vs Victor | 17–9 | 65.38% |
| Twease vs Paul | 17–7 | 70.83% |
| Twease vs Feng | 15–9 | 62.50% |
| Twease vs Steve | 14–9 | 60.87% |
| Twease vs Lars | 15–8 | 65.22% |
| Twease vs Hwoarang | 15–7 | 68.18% |
| Twease vs Clive | 17–5 | 77.27% |
| Twease vs Xiaoyu | 14–7 | 66.67% |
| Twease vs Leroy | 9–8 | 52.94% |
| Twease vs Eddy | 12–5 | 70.59% |
| Twease vs Lee | 9–7 | 56.25% |
| Twease vs Raven | 8–8 | 50.00% |
| Twease vs Asuka | 8–7 | 53.33% |
| Twease vs Lili | 9–5 | 64.29% |
| Twease vs Leo | 7–7 | 50.00% |
| Twease vs Azucena | 9–5 | 64.29% |
| Twease vs Alisa | 12–1 | 92.31% |
| Twease vs Jack-8 | 7–5 | 58.33% |
| Twease vs Kuma | 7–5 | 58.33% |
| Twease vs Claudio | 5–4 | 55.56% |
| Twease vs Shaheen | 4–5 | 44.44% |
| Twease vs Nina | 5–4 | 55.56% |
| Twease vs Jun | 5–4 | 55.56% |
| Twease vs Lidia | 4–4 | 50.00% |
| Twease vs Panda | 3–0 | 100.00% |
| Twease vs Zafina | 1–1 | 50.00% |
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.