| KawaHlib vs Jin | 20–22 | 47.62% |
| KawaHlib vs Kazuya | 25–10 | 71.43% |
| KawaHlib vs King | 10–20 | 33.33% |
| KawaHlib vs Bryan | 15–15 | 50.00% |
| KawaHlib vs Steve | 12–13 | 48.00% |
| KawaHlib vs Hwoarang | 11–12 | 47.83% |
| KawaHlib vs Lili | 13–10 | 56.52% |
| KawaHlib vs Devil Jin | 5–16 | 23.81% |
| KawaHlib vs Paul | 13–6 | 68.42% |
| KawaHlib vs Law | 8–11 | 42.11% |
| KawaHlib vs Lee | 10–9 | 52.63% |
| KawaHlib vs Raven | 9–9 | 50.00% |
| KawaHlib vs Feng | 11–6 | 64.71% |
| KawaHlib vs Reina | 4–12–1 | 25.00% |
| KawaHlib vs Azucena | 10–6 | 62.50% |
| KawaHlib vs Dragunov | 6–9 | 40.00% |
| KawaHlib vs Jun | 4–11 | 26.67% |
| KawaHlib vs Yoshimitsu | 8–6 | 57.14% |
| KawaHlib vs Alisa | 6–8 | 42.86% |
| KawaHlib vs Lars | 4–9 | 30.77% |
| KawaHlib vs Lidia | 6–7 | 46.15% |
| KawaHlib vs Asuka | 6–4 | 60.00% |
| KawaHlib vs Xiaoyu | 3–6 | 33.33% |
| KawaHlib vs Eddy | 5–4 | 55.56% |
| KawaHlib vs Nina | 5–3 | 62.50% |
| KawaHlib vs Leo | 4–3 | 57.14% |
| KawaHlib vs Zafina | 2–3 | 40.00% |
| KawaHlib vs Heihachi | 4–1 | 80.00% |
| KawaHlib vs Kuma | 3–1 | 75.00% |
| KawaHlib vs Jack-8 | 1–2 | 33.33% |
| KawaHlib vs Claudio | 3–0 | 100.00% |
| KawaHlib vs Leroy | 3–0 | 100.00% |
| KawaHlib vs Victor | 1–2 | 33.33% |
| KawaHlib vs Shaheen | 2–0 | 100.00% |
| KawaHlib vs Clive | 2–0 | 100.00% |
| KawaHlib vs Panda | 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.