| BAP|Decoy vs Dragunov | 49–58 | 45.79% |
| BAP|Decoy vs Kazuya | 54–46 | 54.00% |
| BAP|Decoy vs King | 49–45 | 52.13% |
| BAP|Decoy vs Jin | 55–38 | 59.14% |
| BAP|Decoy vs Law | 47–31 | 60.26% |
| BAP|Decoy vs Bryan | 47–29 | 61.84% |
| BAP|Decoy vs Victor | 18–54 | 25.00% |
| BAP|Decoy vs Azucena | 41–24 | 63.08% |
| BAP|Decoy vs Asuka | 34–26 | 56.67% |
| BAP|Decoy vs Yoshimitsu | 34–21 | 61.82% |
| BAP|Decoy vs Steve | 34–21 | 61.82% |
| BAP|Decoy vs Jun | 30–22 | 57.69% |
| BAP|Decoy vs Lee | 34–16 | 68.00% |
| BAP|Decoy vs Lars | 25–17 | 59.52% |
| BAP|Decoy vs Hwoarang | 26–15 | 63.41% |
| BAP|Decoy vs Alisa | 13–27 | 32.50% |
| BAP|Decoy vs Lili | 18–19 | 48.65% |
| BAP|Decoy vs Reina | 25–12 | 67.57% |
| BAP|Decoy vs Paul | 16–20 | 44.44% |
| BAP|Decoy vs Feng | 17–9 | 65.38% |
| BAP|Decoy vs Claudio | 14–12 | 53.85% |
| BAP|Decoy vs Leroy | 16–8 | 66.67% |
| BAP|Decoy vs Jack-8 | 12–11 | 52.17% |
| BAP|Decoy vs Devil Jin | 6–16 | 27.27% |
| BAP|Decoy vs Nina | 12–8 | 60.00% |
| BAP|Decoy vs Zafina | 11–9 | 55.00% |
| BAP|Decoy vs Xiaoyu | 7–12 | 36.84% |
| BAP|Decoy vs Eddy | 10–8 | 55.56% |
| BAP|Decoy vs Heihachi | 11–7 | 61.11% |
| BAP|Decoy vs Raven | 10–7 | 58.82% |
| BAP|Decoy vs Anna | 9–8 | 52.94% |
| BAP|Decoy vs Leo | 8–7 | 53.33% |
| BAP|Decoy vs Lidia | 10–4 | 71.43% |
| BAP|Decoy vs Clive | 9–3 | 75.00% |
| BAP|Decoy vs Fahkumram | 7–4 | 63.64% |
| BAP|Decoy vs Panda | 3–3 | 50.00% |
| BAP|Decoy vs Shaheen | 2–1 | 66.67% |
| BAP|Decoy vs Kuma | 1–2 | 33.33% |
| BAP|Decoy vs Armor King | 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.