| gakdonald vs Kazuya | 101–124 | 44.89% |
| gakdonald vs Paul | 97–81 | 54.49% |
| gakdonald vs Reina | 95–83 | 53.37% |
| gakdonald vs Jin | 65–111 | 36.93% |
| gakdonald vs Hwoarang | 74–101 | 42.29% |
| gakdonald vs Dragunov | 83–89 | 48.26% |
| gakdonald vs King | 69–86 | 44.52% |
| gakdonald vs Bryan | 69–83 | 45.39% |
| gakdonald vs Asuka | 60–74 | 44.78% |
| gakdonald vs Lili | 63–66 | 48.84% |
| gakdonald vs Law | 59–60 | 49.58% |
| gakdonald vs Armor King | 51–54 | 48.57% |
| gakdonald vs Azucena | 46–54 | 46.00% |
| gakdonald vs Yoshimitsu | 46–51 | 47.42% |
| gakdonald vs Steve | 47–47 | 50.00% |
| gakdonald vs Heihachi | 42–40 | 51.22% |
| gakdonald vs Devil Jin | 37–41 | 47.44% |
| gakdonald vs Jun | 36–42 | 46.15% |
| gakdonald vs Lee | 31–46 | 40.26% |
| gakdonald vs Victor | 33–43 | 43.42% |
| gakdonald vs Nina | 35–35 | 50.00% |
| gakdonald vs Miary Zo | 25–43 | 36.76% |
| gakdonald vs Leroy | 26–32 | 44.83% |
| gakdonald vs Xiaoyu | 28–28 | 50.00% |
| gakdonald vs Claudio | 28–28 | 50.00% |
| gakdonald vs Fahkumram | 24–28 | 46.15% |
| gakdonald vs Jack-8 | 26–25 | 50.98% |
| gakdonald vs Lars | 19–29 | 39.58% |
| gakdonald vs Alisa | 23–25 | 47.92% |
| gakdonald vs Feng | 21–26 | 44.68% |
| gakdonald vs Lidia | 17–26 | 39.53% |
| gakdonald vs Leo | 17–22 | 43.59% |
| gakdonald vs Raven | 16–22 | 42.11% |
| gakdonald vs Eddy | 17–15 | 53.12% |
| gakdonald vs Clive | 19–13 | 59.38% |
| gakdonald vs Shaheen | 16–15 | 51.61% |
| gakdonald vs Zafina | 14–17 | 45.16% |
| gakdonald vs Kuma | 10–11 | 47.62% |
| gakdonald vs Anna | 6–12 | 33.33% |
| gakdonald vs Panda | 3–11 | 21.43% |
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.