| HurryUpNBUY vs King | 31–4 | 88.57% |
| HurryUpNBUY vs Lidia | 34–1 | 97.14% |
| HurryUpNBUY vs Kazuya | 33–1 | 97.06% |
| HurryUpNBUY vs Hwoarang | 29–0 | 100.00% |
| HurryUpNBUY vs Jin | 26–0 | 100.00% |
| HurryUpNBUY vs Reina | 23–2 | 92.00% |
| HurryUpNBUY vs Steve | 20–0 | 100.00% |
| HurryUpNBUY vs Jun | 19–0 | 100.00% |
| HurryUpNBUY vs Victor | 17–0 | 100.00% |
| HurryUpNBUY vs Law | 12–1 | 92.31% |
| HurryUpNBUY vs Lili | 13–0 | 100.00% |
| HurryUpNBUY vs Xiaoyu | 12–0 | 100.00% |
| HurryUpNBUY vs Dragunov | 12–0 | 100.00% |
| HurryUpNBUY vs Azucena | 12–0 | 100.00% |
| HurryUpNBUY vs Eddy | 11–0 | 100.00% |
| HurryUpNBUY vs Lars | 10–0 | 100.00% |
| HurryUpNBUY vs Bryan | 9–0 | 100.00% |
| HurryUpNBUY vs Asuka | 9–0 | 100.00% |
| HurryUpNBUY vs Devil Jin | 8–0 | 100.00% |
| HurryUpNBUY vs Yoshimitsu | 7–0 | 100.00% |
| HurryUpNBUY vs Alisa | 7–0 | 100.00% |
| HurryUpNBUY vs Nina | 7–0 | 100.00% |
| HurryUpNBUY vs Leroy | 4–2 | 66.67% |
| HurryUpNBUY vs Raven | 6–0 | 100.00% |
| HurryUpNBUY vs Jack-8 | 5–0 | 100.00% |
| HurryUpNBUY vs Zafina | 5–0 | 100.00% |
| HurryUpNBUY vs Leo | 4–0 | 100.00% |
| HurryUpNBUY vs Paul | 3–0 | 100.00% |
| HurryUpNBUY vs Lee | 3–0 | 100.00% |
| HurryUpNBUY vs Feng | 2–0 | 100.00% |
| HurryUpNBUY vs Claudio | 2–0 | 100.00% |
| HurryUpNBUY vs Shaheen | 2–0 | 100.00% |
| HurryUpNBUY vs Kuma | 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.