| AppleFlan vs King | 100–206 | 32.68% |
| AppleFlan vs Jin | 57–219 | 20.65% |
| AppleFlan vs Steve | 86–185 | 31.73% |
| AppleFlan vs Reina | 95–168 | 36.12% |
| AppleFlan vs Kazuya | 39–172 | 18.48% |
| AppleFlan vs Dragunov | 45–155 | 22.50% |
| AppleFlan vs Law | 43–145 | 22.87% |
| AppleFlan vs Hwoarang | 38–146 | 20.65% |
| AppleFlan vs Bryan | 53–126 | 29.61% |
| AppleFlan vs Lili | 42–104 | 28.77% |
| AppleFlan vs Heihachi | 26–101 | 20.47% |
| AppleFlan vs Yoshimitsu | 35–89 | 28.23% |
| AppleFlan vs Jun | 25–84 | 22.94% |
| AppleFlan vs Alisa | 28–79 | 26.17% |
| AppleFlan vs Lidia | 25–82 | 23.36% |
| AppleFlan vs Asuka | 37–68 | 35.24% |
| AppleFlan vs Clive | 22–80 | 21.57% |
| AppleFlan vs Nina | 29–65 | 30.85% |
| AppleFlan vs Eddy | 16–78 | 17.02% |
| AppleFlan vs Fahkumram | 16–69 | 18.82% |
| AppleFlan vs Paul | 18–66 | 21.43% |
| AppleFlan vs Devil Jin | 24–55 | 30.38% |
| AppleFlan vs Victor | 19–58 | 24.68% |
| AppleFlan vs Azucena | 19–57 | 25.00% |
| AppleFlan vs Lars | 12–58 | 17.14% |
| AppleFlan vs Anna | 20–48 | 29.41% |
| AppleFlan vs Feng | 17–49 | 25.76% |
| AppleFlan vs Lee | 18–48 | 27.27% |
| AppleFlan vs Armor King | 13–51 | 20.31% |
| AppleFlan vs Leo | 8–54 | 12.90% |
| AppleFlan vs Claudio | 11–51 | 17.74% |
| AppleFlan vs Xiaoyu | 9–51 | 15.00% |
| AppleFlan vs Jack-8 | 11–38 | 22.45% |
| AppleFlan vs Leroy | 8–28 | 22.22% |
| AppleFlan vs Zafina | 6–24 | 20.00% |
| AppleFlan vs Raven | 6–23 | 20.69% |
| AppleFlan vs Shaheen | 6–19 | 24.00% |
| AppleFlan vs Kuma | 1–19 | 5.00% |
| AppleFlan vs Panda | 3–17 | 15.00% |
| AppleFlan vs Miary Zo | 3–13 | 18.75% |
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.