| NvLe vs Kazuya | 100–78–1 | 56.18% |
| NvLe vs Heihachi | 87–65 | 57.24% |
| NvLe vs Jin | 53–70 | 43.09% |
| NvLe vs Hwoarang | 46–72 | 38.98% |
| NvLe vs Clive | 69–46 | 60.00% |
| NvLe vs Bryan | 54–59 | 47.79% |
| NvLe vs Reina | 60–53 | 53.10% |
| NvLe vs King | 41–48 | 46.07% |
| NvLe vs Paul | 41–46 | 47.13% |
| NvLe vs Law | 38–49 | 43.68% |
| NvLe vs Steve | 39–41 | 48.75% |
| NvLe vs Lili | 40–39 | 50.63% |
| NvLe vs Devil Jin | 38–37 | 50.67% |
| NvLe vs Dragunov | 32–38 | 45.71% |
| NvLe vs Lidia | 33–27 | 55.00% |
| NvLe vs Azucena | 36–23 | 61.02% |
| NvLe vs Jun | 22–35 | 38.60% |
| NvLe vs Asuka | 30–22 | 57.69% |
| NvLe vs Yoshimitsu | 14–36 | 28.00% |
| NvLe vs Lars | 19–27 | 41.30% |
| NvLe vs Nina | 21–22 | 48.84% |
| NvLe vs Feng | 21–20 | 51.22% |
| NvLe vs Lee | 17–22 | 43.59% |
| NvLe vs Alisa | 11–26 | 29.73% |
| NvLe vs Victor | 18–18 | 50.00% |
| NvLe vs Eddy | 15–21 | 41.67% |
| NvLe vs Xiaoyu | 21–13 | 61.76% |
| NvLe vs Kuma | 14–12 | 53.85% |
| NvLe vs Jack-8 | 14–10 | 58.33% |
| NvLe vs Leo | 5–16 | 23.81% |
| NvLe vs Leroy | 8–13 | 38.10% |
| NvLe vs Raven | 6–14 | 30.00% |
| NvLe vs Fahkumram | 10–10 | 50.00% |
| NvLe vs Shaheen | 12–5 | 70.59% |
| NvLe vs Claudio | 7–9 | 43.75% |
| NvLe vs Zafina | 3–5 | 37.50% |
| NvLe vs Panda | 0–4 | 0.00% |
| NvLe vs Anna | 1–3 | 25.00% |
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.