| NMF-King of STL vs Jin | 10–5 | 66.67% |
| NMF-King of STL vs Steve | 9–4 | 69.23% |
| NMF-King of STL vs King | 9–3 | 75.00% |
| NMF-King of STL vs Heihachi | 10–2 | 83.33% |
| NMF-King of STL vs Leo | 6–5 | 54.55% |
| NMF-King of STL vs Reina | 8–2 | 80.00% |
| NMF-King of STL vs Eddy | 4–6 | 40.00% |
| NMF-King of STL vs Lars | 5–4 | 55.56% |
| NMF-King of STL vs Law | 8–0 | 100.00% |
| NMF-King of STL vs Bryan | 8–0 | 100.00% |
| NMF-King of STL vs Hwoarang | 5–1 | 83.33% |
| NMF-King of STL vs Lili | 4–2 | 66.67% |
| NMF-King of STL vs Azucena | 5–1 | 83.33% |
| NMF-King of STL vs Dragunov | 4–1 | 80.00% |
| NMF-King of STL vs Claudio | 5–0 | 100.00% |
| NMF-King of STL vs Leroy | 4–1 | 80.00% |
| NMF-King of STL vs Paul | 3–1 | 75.00% |
| NMF-King of STL vs Yoshimitsu | 2–2 | 50.00% |
| NMF-King of STL vs Kazuya | 2–2 | 50.00% |
| NMF-King of STL vs Asuka | 3–1 | 75.00% |
| NMF-King of STL vs Clive | 3–0 | 100.00% |
| NMF-King of STL vs Xiaoyu | 2–0 | 100.00% |
| NMF-King of STL vs Feng | 2–0 | 100.00% |
| NMF-King of STL vs Shaheen | 1–1 | 50.00% |
| NMF-King of STL vs Lee | 2–0 | 100.00% |
| NMF-King of STL vs Victor | 1–1 | 50.00% |
| NMF-King of STL vs Jack-8 | 0–1 | 0.00% |
| NMF-King of STL vs Devil Jin | 0–1 | 0.00% |
| NMF-King of STL vs Nina | 1–0 | 100.00% |
| NMF-King of STL vs Kuma | 1–0 | 100.00% |
| NMF-King of STL vs Panda | 0–1 | 0.00% |
| NMF-King of STL vs Zafina | 0–1 | 0.00% |
| NMF-King of STL vs Jun | 1–0 | 100.00% |
| NMF-King of STL vs Raven | 1–0 | 100.00% |
| NMF-King of STL vs Lidia | 0–1 | 0.00% |
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.