| txikxi vs Kazuya | 128–125 | 50.59% |
| txikxi vs Jin | 74–110 | 40.22% |
| txikxi vs Bryan | 97–79 | 55.11% |
| txikxi vs Lidia | 75–81 | 48.08% |
| txikxi vs Heihachi | 68–69 | 49.64% |
| txikxi vs Reina | 59–50 | 54.13% |
| txikxi vs Paul | 53–54 | 49.53% |
| txikxi vs Steve | 41–62 | 39.81% |
| txikxi vs King | 42–49 | 46.15% |
| txikxi vs Dragunov | 41–47 | 46.59% |
| txikxi vs Devil Jin | 36–42 | 46.15% |
| txikxi vs Law | 26–49 | 34.67% |
| txikxi vs Hwoarang | 25–49 | 33.78% |
| txikxi vs Lee | 28–43 | 39.44% |
| txikxi vs Jun | 35–34 | 50.72% |
| txikxi vs Yoshimitsu | 29–39 | 42.65% |
| txikxi vs Azucena | 33–28 | 54.10% |
| txikxi vs Feng | 29–29 | 50.00% |
| txikxi vs Lili | 20–33 | 37.74% |
| txikxi vs Nina | 26–26 | 50.00% |
| txikxi vs Asuka | 27–18 | 60.00% |
| txikxi vs Victor | 20–20 | 50.00% |
| txikxi vs Jack-8 | 11–23 | 32.35% |
| txikxi vs Leroy | 20–14 | 58.82% |
| txikxi vs Claudio | 13–20 | 39.39% |
| txikxi vs Kuma | 14–17 | 45.16% |
| txikxi vs Alisa | 15–14 | 51.72% |
| txikxi vs Lars | 13–15 | 46.43% |
| txikxi vs Raven | 19–7 | 73.08% |
| txikxi vs Xiaoyu | 15–9 | 62.50% |
| txikxi vs Leo | 8–10 | 44.44% |
| txikxi vs Shaheen | 6–11 | 35.29% |
| txikxi vs Eddy | 4–12 | 25.00% |
| txikxi vs Panda | 4–9 | 30.77% |
| txikxi vs Zafina | 4–5 | 44.44% |
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.