| SmackdownLayer vs Jin | 31–5 | 86.11% |
| SmackdownLayer vs Reina | 26–6 | 81.25% |
| SmackdownLayer vs Bryan | 23–6 | 79.31% |
| SmackdownLayer vs Kazuya | 15–13 | 53.57% |
| SmackdownLayer vs King | 17–7 | 70.83% |
| SmackdownLayer vs Heihachi | 15–9 | 62.50% |
| SmackdownLayer vs Lili | 13–9 | 59.09% |
| SmackdownLayer vs Hwoarang | 12–5 | 70.59% |
| SmackdownLayer vs Steve | 12–5 | 70.59% |
| SmackdownLayer vs Armor King | 14–3 | 82.35% |
| SmackdownLayer vs Jun | 10–6 | 62.50% |
| SmackdownLayer vs Dragunov | 11–4 | 73.33% |
| SmackdownLayer vs Paul | 9–4 | 69.23% |
| SmackdownLayer vs Yoshimitsu | 11–2 | 84.62% |
| SmackdownLayer vs Raven | 6–4 | 60.00% |
| SmackdownLayer vs Law | 8–1 | 88.89% |
| SmackdownLayer vs Feng | 8–1 | 88.89% |
| SmackdownLayer vs Nina | 2–7 | 22.22% |
| SmackdownLayer vs Azucena | 6–3 | 66.67% |
| SmackdownLayer vs Xiaoyu | 5–2–1 | 71.43% |
| SmackdownLayer vs Jack-8 | 5–3 | 62.50% |
| SmackdownLayer vs Victor | 7–1 | 87.50% |
| SmackdownLayer vs Lidia | 5–3 | 62.50% |
| SmackdownLayer vs Devil Jin | 6–1 | 85.71% |
| SmackdownLayer vs Asuka | 5–1 | 83.33% |
| SmackdownLayer vs Lars | 5–1 | 83.33% |
| SmackdownLayer vs Lee | 4–2 | 66.67% |
| SmackdownLayer vs Eddy | 4–2 | 66.67% |
| SmackdownLayer vs Kuma | 5–0 | 100.00% |
| SmackdownLayer vs Leo | 4–0 | 100.00% |
| SmackdownLayer vs Alisa | 3–1 | 75.00% |
| SmackdownLayer vs Fahkumram | 4–0 | 100.00% |
| SmackdownLayer vs Zafina | 1–2 | 33.33% |
| SmackdownLayer vs Claudio | 1–1 | 50.00% |
| SmackdownLayer vs Shaheen | 2–0 | 100.00% |
| SmackdownLayer vs Leroy | 1–1 | 50.00% |
| SmackdownLayer vs Clive | 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.