| GYATSLAYER vs Jin | 42–38 | 52.50% |
| GYATSLAYER vs Bryan | 38–30 | 55.88% |
| GYATSLAYER vs Kazuya | 30–36 | 45.45% |
| GYATSLAYER vs Dragunov | 33–29 | 53.23% |
| GYATSLAYER vs King | 28–33 | 45.90% |
| GYATSLAYER vs Reina | 29–28 | 50.88% |
| GYATSLAYER vs Steve | 37–16 | 69.81% |
| GYATSLAYER vs Hwoarang | 27–25 | 51.92% |
| GYATSLAYER vs Lili | 26–20 | 56.52% |
| GYATSLAYER vs Heihachi | 12–27 | 30.77% |
| GYATSLAYER vs Lars | 14–24 | 36.84% |
| GYATSLAYER vs Yoshimitsu | 20–17 | 54.05% |
| GYATSLAYER vs Devil Jin | 24–13 | 64.86% |
| GYATSLAYER vs Law | 19–15 | 55.88% |
| GYATSLAYER vs Victor | 14–12 | 53.85% |
| GYATSLAYER vs Xiaoyu | 12–13 | 48.00% |
| GYATSLAYER vs Nina | 6–17 | 26.09% |
| GYATSLAYER vs Lidia | 11–11 | 50.00% |
| GYATSLAYER vs Claudio | 9–12 | 42.86% |
| GYATSLAYER vs Asuka | 8–12 | 40.00% |
| GYATSLAYER vs Clive | 12–8 | 60.00% |
| GYATSLAYER vs Anna | 12–8 | 60.00% |
| GYATSLAYER vs Lee | 8–10 | 44.44% |
| GYATSLAYER vs Paul | 3–14 | 17.65% |
| GYATSLAYER vs Jun | 7–10 | 41.18% |
| GYATSLAYER vs Eddy | 8–7 | 53.33% |
| GYATSLAYER vs Feng | 5–9 | 35.71% |
| GYATSLAYER vs Kuma | 7–6 | 53.85% |
| GYATSLAYER vs Fahkumram | 7–6 | 53.85% |
| GYATSLAYER vs Alisa | 6–6 | 50.00% |
| GYATSLAYER vs Leroy | 7–5 | 58.33% |
| GYATSLAYER vs Raven | 5–6 | 45.45% |
| GYATSLAYER vs Panda | 4–4 | 50.00% |
| GYATSLAYER vs Shaheen | 5–2 | 71.43% |
| GYATSLAYER vs Azucena | 3–4 | 42.86% |
| GYATSLAYER vs Armor King | 5–2 | 71.43% |
| GYATSLAYER vs Jack-8 | 3–3 | 50.00% |
| GYATSLAYER vs Leo | 3–2 | 60.00% |
| GYATSLAYER vs Zafina | 1–4 | 20.00% |
| GYATSLAYER vs Miary Zo | 2–1 | 66.67% |
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.