| Scam_Likely vs Miary Zo | 9–19 | 32.14% |
| Scam_Likely vs King | 10–9 | 52.63% |
| Scam_Likely vs Steve | 11–6 | 64.71% |
| Scam_Likely vs Jin | 3–9 | 25.00% |
| Scam_Likely vs Leo | 1–10 | 9.09% |
| Scam_Likely vs Reina | 4–7 | 36.36% |
| Scam_Likely vs Yoshimitsu | 3–7 | 30.00% |
| Scam_Likely vs Bryan | 4–6 | 40.00% |
| Scam_Likely vs Kazuya | 3–7 | 30.00% |
| Scam_Likely vs Lidia | 3–7 | 30.00% |
| Scam_Likely vs Hwoarang | 2–7 | 22.22% |
| Scam_Likely vs Eddy | 1–8 | 11.11% |
| Scam_Likely vs Xiaoyu | 3–5 | 37.50% |
| Scam_Likely vs Lili | 2–6 | 25.00% |
| Scam_Likely vs Dragunov | 2–6 | 25.00% |
| Scam_Likely vs Jun | 5–3 | 62.50% |
| Scam_Likely vs Fahkumram | 3–5 | 37.50% |
| Scam_Likely vs Asuka | 1–6 | 14.29% |
| Scam_Likely vs Armor King | 1–6 | 14.29% |
| Scam_Likely vs Azucena | 0–6 | 0.00% |
| Scam_Likely vs Victor | 2–4 | 33.33% |
| Scam_Likely vs Law | 1–4 | 20.00% |
| Scam_Likely vs Lars | 2–3 | 40.00% |
| Scam_Likely vs Leroy | 2–3 | 40.00% |
| Scam_Likely vs Clive | 1–4 | 20.00% |
| Scam_Likely vs Lee | 2–2 | 50.00% |
| Scam_Likely vs Claudio | 0–3 | 0.00% |
| Scam_Likely vs Nina | 2–1 | 66.67% |
| Scam_Likely vs Anna | 1–2 | 33.33% |
| Scam_Likely vs Shaheen | 0–2 | 0.00% |
| Scam_Likely vs Zafina | 0–2 | 0.00% |
| Scam_Likely vs Heihachi | 0–2 | 0.00% |
| Scam_Likely vs Panda | 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.