| Too Bluunt vs King | 8–13 | 38.10% |
| Too Bluunt vs Kazuya | 11–8 | 57.89% |
| Too Bluunt vs Jin | 8–10 | 44.44% |
| Too Bluunt vs Jun | 7–10 | 41.18% |
| Too Bluunt vs Reina | 7–10 | 41.18% |
| Too Bluunt vs Law | 9–7 | 56.25% |
| Too Bluunt vs Hwoarang | 8–8 | 50.00% |
| Too Bluunt vs Asuka | 9–7 | 56.25% |
| Too Bluunt vs Azucena | 10–6 | 62.50% |
| Too Bluunt vs Lili | 7–7 | 50.00% |
| Too Bluunt vs Steve | 8–2 | 80.00% |
| Too Bluunt vs Lee | 1–9 | 10.00% |
| Too Bluunt vs Bryan | 5–4 | 55.56% |
| Too Bluunt vs Dragunov | 3–6 | 33.33% |
| Too Bluunt vs Yoshimitsu | 4–3 | 57.14% |
| Too Bluunt vs Eddy | 2–5 | 28.57% |
| Too Bluunt vs Zafina | 1–4 | 20.00% |
| Too Bluunt vs Leroy | 3–2 | 60.00% |
| Too Bluunt vs Victor | 3–2 | 60.00% |
| Too Bluunt vs Paul | 0–4 | 0.00% |
| Too Bluunt vs Devil Jin | 1–3 | 25.00% |
| Too Bluunt vs Leo | 2–2 | 50.00% |
| Too Bluunt vs Shaheen | 2–2 | 50.00% |
| Too Bluunt vs Nina | 4–0 | 100.00% |
| Too Bluunt vs Jack-8 | 2–1 | 66.67% |
| Too Bluunt vs Claudio | 0–3 | 0.00% |
| Too Bluunt vs Xiaoyu | 2–0 | 100.00% |
| Too Bluunt vs Feng | 0–2 | 0.00% |
| Too Bluunt vs Lars | 0–2 | 0.00% |
| Too Bluunt vs Alisa | 0–2 | 0.00% |
| Too Bluunt vs Kuma | 2–0 | 100.00% |
| Too Bluunt vs Lidia | 2–0 | 100.00% |
| Too Bluunt vs Anna | 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.