| SlamTown vs Bryan | 52–47 | 52.53% |
| SlamTown vs Kazuya | 45–40 | 52.94% |
| SlamTown vs King | 42–37 | 53.16% |
| SlamTown vs Reina | 31–41 | 43.06% |
| SlamTown vs Eddy | 33–39 | 45.83% |
| SlamTown vs Jin | 31–37 | 45.59% |
| SlamTown vs Steve | 31–36 | 46.27% |
| SlamTown vs Dragunov | 26–35 | 42.62% |
| SlamTown vs Hwoarang | 27–30 | 47.37% |
| SlamTown vs Lee | 28–29 | 49.12% |
| SlamTown vs Law | 27–27 | 50.00% |
| SlamTown vs Lili | 17–34 | 33.33% |
| SlamTown vs Jun | 28–23 | 54.90% |
| SlamTown vs Asuka | 23–18 | 56.10% |
| SlamTown vs Feng | 19–22 | 46.34% |
| SlamTown vs Paul | 24–14 | 63.16% |
| SlamTown vs Devil Jin | 19–17 | 52.78% |
| SlamTown vs Heihachi | 19–15 | 55.88% |
| SlamTown vs Xiaoyu | 17–16 | 51.52% |
| SlamTown vs Victor | 17–16 | 51.52% |
| SlamTown vs Armor King | 17–15 | 53.12% |
| SlamTown vs Yoshimitsu | 11–17 | 39.29% |
| SlamTown vs Lars | 13–14 | 48.15% |
| SlamTown vs Nina | 13–14 | 48.15% |
| SlamTown vs Azucena | 13–11 | 54.17% |
| SlamTown vs Alisa | 13–8 | 61.90% |
| SlamTown vs Leo | 8–12 | 40.00% |
| SlamTown vs Clive | 7–10 | 41.18% |
| SlamTown vs Kuma | 6–10 | 37.50% |
| SlamTown vs Raven | 5–10 | 33.33% |
| SlamTown vs Shaheen | 7–7 | 50.00% |
| SlamTown vs Jack-8 | 6–7 | 46.15% |
| SlamTown vs Lidia | 10–2 | 83.33% |
| SlamTown vs Claudio | 7–4 | 63.64% |
| SlamTown vs Zafina | 3–8 | 27.27% |
| SlamTown vs Leroy | 4–6 | 40.00% |
| SlamTown vs Anna | 3–4 | 42.86% |
| SlamTown vs Fahkumram | 1–5 | 16.67% |
| SlamTown vs Miary Zo | 4–1 | 80.00% |
| SlamTown vs Panda | 2–0 | 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.