| DjangoFTL vs Kazuya | 130–136 | 48.87% |
| DjangoFTL vs King | 97–134 | 41.99% |
| DjangoFTL vs Reina | 78–111 | 41.27% |
| DjangoFTL vs Bryan | 65–100 | 39.39% |
| DjangoFTL vs Jin | 86–72 | 54.43% |
| DjangoFTL vs Heihachi | 61–74 | 45.19% |
| DjangoFTL vs Steve | 56–75–1 | 42.75% |
| DjangoFTL vs Paul | 66–59 | 52.80% |
| DjangoFTL vs Dragunov | 47–62 | 43.12% |
| DjangoFTL vs Lili | 53–54 | 49.53% |
| DjangoFTL vs Hwoarang | 51–52 | 49.51% |
| DjangoFTL vs Law | 58–40 | 59.18% |
| DjangoFTL vs Armor King | 40–57 | 41.24% |
| DjangoFTL vs Lee | 44–46 | 48.89% |
| DjangoFTL vs Fahkumram | 32–49 | 39.51% |
| DjangoFTL vs Jun | 41–37 | 52.56% |
| DjangoFTL vs Yoshimitsu | 30–47 | 38.96% |
| DjangoFTL vs Azucena | 38–33 | 53.52% |
| DjangoFTL vs Leo | 31–32 | 49.21% |
| DjangoFTL vs Xiaoyu | 23–33 | 41.07% |
| DjangoFTL vs Victor | 18–34 | 34.62% |
| DjangoFTL vs Anna | 26–26 | 50.00% |
| DjangoFTL vs Clive | 25–26 | 49.02% |
| DjangoFTL vs Asuka | 23–26 | 46.94% |
| DjangoFTL vs Lidia | 28–20 | 58.33% |
| DjangoFTL vs Nina | 16–24 | 40.00% |
| DjangoFTL vs Lars | 18–21 | 46.15% |
| DjangoFTL vs Claudio | 17–22 | 43.59% |
| DjangoFTL vs Feng | 15–23 | 39.47% |
| DjangoFTL vs Jack-8 | 13–22 | 37.14% |
| DjangoFTL vs Leroy | 19–16 | 54.29% |
| DjangoFTL vs Raven | 14–20 | 41.18% |
| DjangoFTL vs Eddy | 14–19 | 42.42% |
| DjangoFTL vs Devil Jin | 11–18 | 37.93% |
| DjangoFTL vs Alisa | 12–9 | 57.14% |
| DjangoFTL vs Kuma | 4–16 | 20.00% |
| DjangoFTL vs Miary Zo | 4–10 | 28.57% |
| DjangoFTL vs Zafina | 3–10 | 23.08% |
| DjangoFTL vs Shaheen | 5–6 | 45.45% |
| DjangoFTL vs Panda | 3–6 | 33.33% |
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.