| KefeUfa vs Bryan | 33–32 | 50.77% |
| KefeUfa vs Jin | 34–25 | 57.63% |
| KefeUfa vs Steve | 24–22 | 52.17% |
| KefeUfa vs Kazuya | 24–17 | 58.54% |
| KefeUfa vs Dragunov | 20–17 | 54.05% |
| KefeUfa vs King | 19–17 | 52.78% |
| KefeUfa vs Lee | 14–20 | 41.18% |
| KefeUfa vs Reina | 17–15 | 53.12% |
| KefeUfa vs Paul | 15–16 | 48.39% |
| KefeUfa vs Nina | 16–9 | 64.00% |
| KefeUfa vs Heihachi | 11–13 | 45.83% |
| KefeUfa vs Hwoarang | 17–6 | 73.91% |
| KefeUfa vs Law | 12–10 | 54.55% |
| KefeUfa vs Eddy | 9–13 | 40.91% |
| KefeUfa vs Victor | 10–10 | 50.00% |
| KefeUfa vs Azucena | 11–4 | 73.33% |
| KefeUfa vs Yoshimitsu | 6–8 | 42.86% |
| KefeUfa vs Lili | 9–5 | 64.29% |
| KefeUfa vs Jun | 8–6 | 57.14% |
| KefeUfa vs Jack-8 | 9–4 | 69.23% |
| KefeUfa vs Devil Jin | 6–7 | 46.15% |
| KefeUfa vs Alisa | 5–7 | 41.67% |
| KefeUfa vs Lidia | 9–3 | 75.00% |
| KefeUfa vs Lars | 6–4 | 60.00% |
| KefeUfa vs Asuka | 8–1 | 88.89% |
| KefeUfa vs Claudio | 5–3 | 62.50% |
| KefeUfa vs Kuma | 4–4 | 50.00% |
| KefeUfa vs Anna | 3–5 | 37.50% |
| KefeUfa vs Xiaoyu | 2–5 | 28.57% |
| KefeUfa vs Feng | 6–1 | 85.71% |
| KefeUfa vs Raven | 2–5 | 28.57% |
| KefeUfa vs Clive | 6–1 | 85.71% |
| KefeUfa vs Leo | 2–3 | 40.00% |
| KefeUfa vs Shaheen | 0–4 | 0.00% |
| KefeUfa vs Panda | 3–0 | 100.00% |
| KefeUfa vs Fahkumram | 2–1 | 66.67% |
| KefeUfa vs Leroy | 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.