| Noodles vs Kazuya | 18–20 | 47.37% |
| Noodles vs Jin | 16–14 | 53.33% |
| Noodles vs Reina | 13–15 | 46.43% |
| Noodles vs King | 21–6 | 77.78% |
| Noodles vs Hwoarang | 12–15 | 44.44% |
| Noodles vs Dragunov | 19–8 | 70.37% |
| Noodles vs Law | 22–4 | 84.62% |
| Noodles vs Lee | 16–10 | 61.54% |
| Noodles vs Eddy | 9–15 | 37.50% |
| Noodles vs Lili | 11–12 | 47.83% |
| Noodles vs Lidia | 15–7 | 68.18% |
| Noodles vs Heihachi | 11–11 | 50.00% |
| Noodles vs Xiaoyu | 11–10 | 52.38% |
| Noodles vs Steve | 18–3 | 85.71% |
| Noodles vs Victor | 13–7 | 65.00% |
| Noodles vs Lars | 9–10 | 47.37% |
| Noodles vs Azucena | 10–8 | 55.56% |
| Noodles vs Bryan | 9–6 | 60.00% |
| Noodles vs Jun | 8–6 | 57.14% |
| Noodles vs Kuma | 9–4 | 69.23% |
| Noodles vs Zafina | 4–9 | 30.77% |
| Noodles vs Paul | 8–4 | 66.67% |
| Noodles vs Devil Jin | 9–3 | 75.00% |
| Noodles vs Yoshimitsu | 4–7 | 36.36% |
| Noodles vs Jack-8 | 7–4 | 63.64% |
| Noodles vs Raven | 2–9 | 18.18% |
| Noodles vs Asuka | 3–6 | 33.33% |
| Noodles vs Leo | 5–4 | 55.56% |
| Noodles vs Feng | 4–4 | 50.00% |
| Noodles vs Leroy | 5–3 | 62.50% |
| Noodles vs Claudio | 3–3 | 50.00% |
| Noodles vs Shaheen | 1–4 | 20.00% |
| Noodles vs Nina | 4–1 | 80.00% |
| Noodles vs Panda | 4–1 | 80.00% |
| Noodles vs Alisa | 2–0 | 100.00% |
| Noodles vs Clive | 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.