| nlnare321 vs Kazuya | 73–45 | 61.86% |
| nlnare321 vs Dragunov | 58–36 | 61.70% |
| nlnare321 vs Bryan | 45–36 | 55.56% |
| nlnare321 vs Heihachi | 47–26 | 64.38% |
| nlnare321 vs Reina | 43–19 | 69.35% |
| nlnare321 vs Jin | 35–23 | 60.34% |
| nlnare321 vs King | 36–19 | 65.45% |
| nlnare321 vs Hwoarang | 35–15 | 70.00% |
| nlnare321 vs Lili | 28–17 | 62.22% |
| nlnare321 vs Yoshimitsu | 29–12 | 70.73% |
| nlnare321 vs Paul | 25–14 | 64.10% |
| nlnare321 vs Jack-8 | 21–18 | 53.85% |
| nlnare321 vs Asuka | 25–9 | 73.53% |
| nlnare321 vs Lee | 20–13 | 60.61% |
| nlnare321 vs Law | 18–14 | 56.25% |
| nlnare321 vs Devil Jin | 24–7 | 77.42% |
| nlnare321 vs Feng | 19–12 | 61.29% |
| nlnare321 vs Leroy | 20–10 | 66.67% |
| nlnare321 vs Jun | 16–14 | 53.33% |
| nlnare321 vs Steve | 20–8 | 71.43% |
| nlnare321 vs Lidia | 13–15 | 46.43% |
| nlnare321 vs Claudio | 17–10 | 62.96% |
| nlnare321 vs Nina | 20–7 | 74.07% |
| nlnare321 vs Victor | 17–10 | 62.96% |
| nlnare321 vs Lars | 17–8 | 68.00% |
| nlnare321 vs Alisa | 15–10 | 60.00% |
| nlnare321 vs Leo | 6–14 | 30.00% |
| nlnare321 vs Zafina | 11–7 | 61.11% |
| nlnare321 vs Xiaoyu | 13–4 | 76.47% |
| nlnare321 vs Azucena | 11–6 | 64.71% |
| nlnare321 vs Eddy | 11–4 | 73.33% |
| nlnare321 vs Shaheen | 5–8 | 38.46% |
| nlnare321 vs Raven | 8–3 | 72.73% |
| nlnare321 vs Clive | 6–4 | 60.00% |
| nlnare321 vs Panda | 4–5 | 44.44% |
| nlnare321 vs Anna | 7–1 | 87.50% |
| nlnare321 vs Kuma | 2–2 | 50.00% |
| nlnare321 vs Miary Zo | 3–0 | 100.00% |
| nlnare321 vs Armor King | 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.