| nyangoon vs Jin | 24–25 | 48.98% |
| nyangoon vs Paul | 26–22 | 54.17% |
| nyangoon vs Reina | 28–19 | 59.57% |
| nyangoon vs Bryan | 14–21 | 40.00% |
| nyangoon vs Hwoarang | 21–13 | 61.76% |
| nyangoon vs King | 15–14 | 51.72% |
| nyangoon vs Yoshimitsu | 12–16 | 42.86% |
| nyangoon vs Kazuya | 13–14 | 48.15% |
| nyangoon vs Steve | 14–11 | 56.00% |
| nyangoon vs Dragunov | 13–11 | 54.17% |
| nyangoon vs Lars | 10–11 | 47.62% |
| nyangoon vs Leroy | 11–10 | 52.38% |
| nyangoon vs Jun | 11–9 | 55.00% |
| nyangoon vs Lili | 7–12 | 36.84% |
| nyangoon vs Claudio | 9–10 | 47.37% |
| nyangoon vs Victor | 12–7 | 63.16% |
| nyangoon vs Asuka | 9–8 | 52.94% |
| nyangoon vs Law | 6–8 | 42.86% |
| nyangoon vs Azucena | 8–6 | 57.14% |
| nyangoon vs Alisa | 6–6 | 50.00% |
| nyangoon vs Jack-8 | 2–9 | 18.18% |
| nyangoon vs Feng | 2–8 | 20.00% |
| nyangoon vs Lee | 6–3 | 66.67% |
| nyangoon vs Zafina | 3–5 | 37.50% |
| nyangoon vs Xiaoyu | 3–3 | 50.00% |
| nyangoon vs Devil Jin | 2–4 | 33.33% |
| nyangoon vs Shaheen | 2–4 | 33.33% |
| nyangoon vs Nina | 2–4 | 33.33% |
| nyangoon vs Kuma | 4–2 | 66.67% |
| nyangoon vs Clive | 2–4 | 33.33% |
| nyangoon vs Fahkumram | 1–4 | 20.00% |
| nyangoon vs Leo | 2–2 | 50.00% |
| nyangoon vs Eddy | 0–4 | 0.00% |
| nyangoon vs Heihachi | 2–1 | 66.67% |
| nyangoon vs Raven | 1–1 | 50.00% |
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.