| DigitlBlr vs Kazuya | 80–49 | 62.02% |
| DigitlBlr vs Jin | 53–53 | 50.00% |
| DigitlBlr vs Heihachi | 62–44 | 58.49% |
| DigitlBlr vs Reina | 49–48 | 50.52% |
| DigitlBlr vs King | 45–47 | 48.91% |
| DigitlBlr vs Steve | 45–44 | 50.56% |
| DigitlBlr vs Dragunov | 40–48 | 45.45% |
| DigitlBlr vs Bryan | 40–43 | 48.19% |
| DigitlBlr vs Clive | 29–37 | 43.94% |
| DigitlBlr vs Hwoarang | 29–36 | 44.62% |
| DigitlBlr vs Azucena | 32–24 | 57.14% |
| DigitlBlr vs Lili | 24–27 | 47.06% |
| DigitlBlr vs Nina | 19–31 | 38.00% |
| DigitlBlr vs Paul | 27–22 | 55.10% |
| DigitlBlr vs Law | 22–27 | 44.90% |
| DigitlBlr vs Lee | 17–32 | 34.69% |
| DigitlBlr vs Yoshimitsu | 25–22 | 53.19% |
| DigitlBlr vs Devil Jin | 23–24 | 48.94% |
| DigitlBlr vs Asuka | 22–24 | 47.83% |
| DigitlBlr vs Jun | 27–19 | 58.70% |
| DigitlBlr vs Victor | 19–14 | 57.58% |
| DigitlBlr vs Leo | 20–12 | 62.50% |
| DigitlBlr vs Leroy | 16–14 | 53.33% |
| DigitlBlr vs Claudio | 12–17 | 41.38% |
| DigitlBlr vs Lidia | 18–11 | 62.07% |
| DigitlBlr vs Xiaoyu | 10–16 | 38.46% |
| DigitlBlr vs Raven | 14–12 | 53.85% |
| DigitlBlr vs Alisa | 13–11 | 54.17% |
| DigitlBlr vs Armor King | 17–6 | 73.91% |
| DigitlBlr vs Lars | 11–8 | 57.89% |
| DigitlBlr vs Eddy | 5–14 | 26.32% |
| DigitlBlr vs Jack-8 | 5–11 | 31.25% |
| DigitlBlr vs Kuma | 11–5 | 68.75% |
| DigitlBlr vs Feng | 6–9 | 40.00% |
| DigitlBlr vs Fahkumram | 5–10 | 33.33% |
| DigitlBlr vs Shaheen | 8–3 | 72.73% |
| DigitlBlr vs Zafina | 6–1 | 85.71% |
| DigitlBlr vs Anna | 3–0 | 100.00% |
| DigitlBlr vs Panda | 0–2 | 0.00% |
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.