| inoko9890 vs Kazuya | 114–257 | 30.73% |
| inoko9890 vs Reina | 149–151 | 49.67% |
| inoko9890 vs King | 81–178 | 31.27% |
| inoko9890 vs Paul | 78–143 | 35.29% |
| inoko9890 vs Asuka | 60–158 | 27.52% |
| inoko9890 vs Jin | 61–148 | 29.19% |
| inoko9890 vs Lili | 64–138 | 31.68% |
| inoko9890 vs Hwoarang | 56–140 | 28.57% |
| inoko9890 vs Victor | 63–125 | 33.51% |
| inoko9890 vs Dragunov | 43–143 | 23.12% |
| inoko9890 vs Bryan | 63–115 | 35.39% |
| inoko9890 vs Lidia | 49–129 | 27.53% |
| inoko9890 vs Jun | 55–112 | 32.93% |
| inoko9890 vs Steve | 47–97 | 32.64% |
| inoko9890 vs Yoshimitsu | 30–98 | 23.44% |
| inoko9890 vs Azucena | 33–80 | 29.20% |
| inoko9890 vs Devil Jin | 33–77 | 30.00% |
| inoko9890 vs Law | 24–79 | 23.30% |
| inoko9890 vs Jack-8 | 27–74 | 26.73% |
| inoko9890 vs Nina | 23–76 | 23.23% |
| inoko9890 vs Xiaoyu | 30–68 | 30.61% |
| inoko9890 vs Heihachi | 29–69 | 29.59% |
| inoko9890 vs Fahkumram | 21–72 | 22.58% |
| inoko9890 vs Alisa | 18–67 | 21.18% |
| inoko9890 vs Clive | 21–56 | 27.27% |
| inoko9890 vs Lars | 13–62 | 17.33% |
| inoko9890 vs Claudio | 14–61 | 18.67% |
| inoko9890 vs Anna | 15–57 | 20.83% |
| inoko9890 vs Leo | 16–55 | 22.54% |
| inoko9890 vs Eddy | 18–48 | 27.27% |
| inoko9890 vs Lee | 19–39 | 32.76% |
| inoko9890 vs Leroy | 27–31 | 46.55% |
| inoko9890 vs Miary Zo | 7–40 | 14.89% |
| inoko9890 vs Kuma | 9–34 | 20.93% |
| inoko9890 vs Zafina | 14–27 | 34.15% |
| inoko9890 vs Feng | 4–34 | 10.53% |
| inoko9890 vs Armor King | 14–24 | 36.84% |
| inoko9890 vs Shaheen | 10–21 | 32.26% |
| inoko9890 vs Panda | 3–22 | 12.00% |
| inoko9890 vs Raven | 4–10 | 28.57% |
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.