| NINA LUV vs Hwoarang | 27–5 | 84.38% |
| NINA LUV vs Kazuya | 29–3 | 90.62% |
| NINA LUV vs Heihachi | 21–5 | 80.77% |
| NINA LUV vs Bryan | 18–5 | 78.26% |
| NINA LUV vs King | 20–2 | 90.91% |
| NINA LUV vs Yoshimitsu | 17–2 | 89.47% |
| NINA LUV vs Clive | 16–3 | 84.21% |
| NINA LUV vs Lili | 15–3 | 83.33% |
| NINA LUV vs Alisa | 15–3 | 83.33% |
| NINA LUV vs Lee | 16–2 | 88.89% |
| NINA LUV vs Armor King | 11–7 | 61.11% |
| NINA LUV vs Jin | 17–0 | 100.00% |
| NINA LUV vs Dragunov | 14–3 | 82.35% |
| NINA LUV vs Law | 11–5 | 68.75% |
| NINA LUV vs Steve | 16–0 | 100.00% |
| NINA LUV vs Asuka | 12–2 | 85.71% |
| NINA LUV vs Nina | 13–0 | 100.00% |
| NINA LUV vs Paul | 12–0 | 100.00% |
| NINA LUV vs Reina | 11–1 | 91.67% |
| NINA LUV vs Feng | 7–4 | 63.64% |
| NINA LUV vs Leroy | 8–2 | 80.00% |
| NINA LUV vs Lars | 7–2 | 77.78% |
| NINA LUV vs Victor | 7–2 | 77.78% |
| NINA LUV vs Lidia | 7–1 | 87.50% |
| NINA LUV vs Jack-8 | 3–4 | 42.86% |
| NINA LUV vs Eddy | 6–1 | 85.71% |
| NINA LUV vs Jun | 4–2 | 66.67% |
| NINA LUV vs Azucena | 4–2 | 66.67% |
| NINA LUV vs Kuma | 5–0 | 100.00% |
| NINA LUV vs Zafina | 5–0 | 100.00% |
| NINA LUV vs Devil Jin | 4–0 | 100.00% |
| NINA LUV vs Leo | 1–3 | 25.00% |
| NINA LUV vs Shaheen | 4–0 | 100.00% |
| NINA LUV vs Claudio | 2–1 | 66.67% |
| NINA LUV vs Fahkumram | 2–1 | 66.67% |
| NINA LUV vs Xiaoyu | 2–0 | 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.