| ttv_kabirfgc vs Kazuya | 22–19 | 53.66% |
| ttv_kabirfgc vs King | 22–18 | 55.00% |
| ttv_kabirfgc vs Dragunov | 20–15 | 57.14% |
| ttv_kabirfgc vs Paul | 17–9 | 65.38% |
| ttv_kabirfgc vs Jin | 18–7 | 72.00% |
| ttv_kabirfgc vs Fahkumram | 8–12 | 40.00% |
| ttv_kabirfgc vs Bryan | 14–5 | 73.68% |
| ttv_kabirfgc vs Eddy | 10–9 | 52.63% |
| ttv_kabirfgc vs Yoshimitsu | 4–14 | 22.22% |
| ttv_kabirfgc vs Azucena | 11–6 | 64.71% |
| ttv_kabirfgc vs Armor King | 8–9 | 47.06% |
| ttv_kabirfgc vs Steve | 10–6 | 62.50% |
| ttv_kabirfgc vs Nina | 11–5 | 68.75% |
| ttv_kabirfgc vs Heihachi | 10–5 | 66.67% |
| ttv_kabirfgc vs Alisa | 4–10 | 28.57% |
| ttv_kabirfgc vs Claudio | 5–9 | 35.71% |
| ttv_kabirfgc vs Law | 6–4 | 60.00% |
| ttv_kabirfgc vs Hwoarang | 4–6 | 40.00% |
| ttv_kabirfgc vs Lee | 4–6 | 40.00% |
| ttv_kabirfgc vs Kuma | 7–3 | 70.00% |
| ttv_kabirfgc vs Feng | 3–6 | 33.33% |
| ttv_kabirfgc vs Victor | 6–3 | 66.67% |
| ttv_kabirfgc vs Reina | 6–2 | 75.00% |
| ttv_kabirfgc vs Asuka | 3–3 | 50.00% |
| ttv_kabirfgc vs Xiaoyu | 2–2 | 50.00% |
| ttv_kabirfgc vs Devil Jin | 4–0 | 100.00% |
| ttv_kabirfgc vs Lili | 0–4 | 0.00% |
| ttv_kabirfgc vs Leo | 3–1 | 75.00% |
| ttv_kabirfgc vs Lars | 1–3 | 25.00% |
| ttv_kabirfgc vs Raven | 2–2 | 50.00% |
| ttv_kabirfgc vs Lidia | 4–0 | 100.00% |
| ttv_kabirfgc vs Anna | 1–2 | 33.33% |
| ttv_kabirfgc vs Jack-8 | 2–0 | 100.00% |
| ttv_kabirfgc vs Zafina | 0–2 | 0.00% |
| ttv_kabirfgc vs Clive | 2–0 | 100.00% |
| ttv_kabirfgc vs Jun | 0–1 | 0.00% |
| ttv_kabirfgc vs Miary Zo | 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.