| Clustercline vs King | 29–23 | 55.77% |
| Clustercline vs Kazuya | 20–23 | 46.51% |
| Clustercline vs Reina | 12–25 | 32.43% |
| Clustercline vs Hwoarang | 22–12 | 64.71% |
| Clustercline vs Steve | 17–14 | 54.84% |
| Clustercline vs Law | 11–17 | 39.29% |
| Clustercline vs Jin | 13–14 | 48.15% |
| Clustercline vs Eddy | 12–14 | 46.15% |
| Clustercline vs Jun | 5–20 | 20.00% |
| Clustercline vs Yoshimitsu | 7–14 | 33.33% |
| Clustercline vs Lee | 6–14 | 30.00% |
| Clustercline vs Victor | 9–11 | 45.00% |
| Clustercline vs Asuka | 8–11 | 42.11% |
| Clustercline vs Leo | 4–14 | 22.22% |
| Clustercline vs Leroy | 9–9 | 50.00% |
| Clustercline vs Bryan | 8–8 | 50.00% |
| Clustercline vs Lars | 7–8 | 46.67% |
| Clustercline vs Alisa | 3–12 | 20.00% |
| Clustercline vs Azucena | 8–7 | 53.33% |
| Clustercline vs Lidia | 9–6 | 60.00% |
| Clustercline vs Dragunov | 4–9 | 30.77% |
| Clustercline vs Nina | 6–7 | 46.15% |
| Clustercline vs Claudio | 6–6 | 50.00% |
| Clustercline vs Heihachi | 5–7 | 41.67% |
| Clustercline vs Xiaoyu | 4–6 | 40.00% |
| Clustercline vs Feng | 8–0 | 100.00% |
| Clustercline vs Lili | 5–3 | 62.50% |
| Clustercline vs Paul | 2–5 | 28.57% |
| Clustercline vs Jack-8 | 1–6 | 14.29% |
| Clustercline vs Raven | 2–5 | 28.57% |
| Clustercline vs Devil Jin | 4–2 | 66.67% |
| Clustercline vs Kuma | 0–6 | 0.00% |
| Clustercline vs Fahkumram | 2–3 | 40.00% |
| Clustercline vs Panda | 1–2 | 33.33% |
| Clustercline vs Zafina | 1–2 | 33.33% |
| Clustercline vs Anna | 2–0 | 100.00% |
| Clustercline vs Clive | 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.