| LN_FN vs King | 20–11 | 64.52% |
| LN_FN vs Jin | 19–11 | 63.33% |
| LN_FN vs Jun | 19–8 | 70.37% |
| LN_FN vs Steve | 18–7 | 72.00% |
| LN_FN vs Reina | 19–5 | 79.17% |
| LN_FN vs Lili | 19–4 | 82.61% |
| LN_FN vs Kazuya | 16–6 | 72.73% |
| LN_FN vs Yoshimitsu | 13–7 | 65.00% |
| LN_FN vs Hwoarang | 14–6 | 70.00% |
| LN_FN vs Xiaoyu | 7–10 | 41.18% |
| LN_FN vs Eddy | 12–5 | 70.59% |
| LN_FN vs Asuka | 11–5 | 68.75% |
| LN_FN vs Kuma | 13–3 | 81.25% |
| LN_FN vs Bryan | 12–2 | 85.71% |
| LN_FN vs Law | 6–7 | 46.15% |
| LN_FN vs Devil Jin | 8–5 | 61.54% |
| LN_FN vs Paul | 9–2 | 81.82% |
| LN_FN vs Dragunov | 10–1 | 90.91% |
| LN_FN vs Shaheen | 7–4 | 63.64% |
| LN_FN vs Azucena | 6–4 | 60.00% |
| LN_FN vs Victor | 6–4 | 60.00% |
| LN_FN vs Claudio | 6–3 | 66.67% |
| LN_FN vs Lee | 1–8 | 11.11% |
| LN_FN vs Feng | 6–2 | 75.00% |
| LN_FN vs Leroy | 4–4 | 50.00% |
| LN_FN vs Jack-8 | 6–1 | 85.71% |
| LN_FN vs Alisa | 6–1 | 85.71% |
| LN_FN vs Nina | 2–4 | 33.33% |
| LN_FN vs Panda | 4–2 | 66.67% |
| LN_FN vs Raven | 5–1 | 83.33% |
| LN_FN vs Armor King | 4–2 | 66.67% |
| LN_FN vs Zafina | 2–3 | 40.00% |
| LN_FN vs Fahkumram | 2–1 | 66.67% |
| LN_FN vs Lars | 2–0 | 100.00% |
| LN_FN vs Lidia | 2–0 | 100.00% |
| LN_FN vs Heihachi | 2–0 | 100.00% |
| LN_FN vs Leo | 1–0 | 100.00% |
| LN_FN vs Clive | 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.