| JjinKhangJoon vs Kazuya | 16–15 | 51.61% |
| JjinKhangJoon vs Reina | 15–11 | 57.69% |
| JjinKhangJoon vs Lili | 10–13 | 43.48% |
| JjinKhangJoon vs Dragunov | 11–10 | 52.38% |
| JjinKhangJoon vs Paul | 6–11 | 35.29% |
| JjinKhangJoon vs King | 8–9 | 47.06% |
| JjinKhangJoon vs Steve | 6–11 | 35.29% |
| JjinKhangJoon vs Azucena | 10–6 | 62.50% |
| JjinKhangJoon vs Law | 4–10 | 28.57% |
| JjinKhangJoon vs Xiaoyu | 10–4 | 71.43% |
| JjinKhangJoon vs Asuka | 7–6 | 53.85% |
| JjinKhangJoon vs Alisa | 3–10 | 23.08% |
| JjinKhangJoon vs Clive | 4–9 | 30.77% |
| JjinKhangJoon vs Yoshimitsu | 6–5 | 54.55% |
| JjinKhangJoon vs Jin | 5–5 | 50.00% |
| JjinKhangJoon vs Kuma | 2–7 | 22.22% |
| JjinKhangJoon vs Lidia | 3–6 | 33.33% |
| JjinKhangJoon vs Victor | 3–5 | 37.50% |
| JjinKhangJoon vs Armor King | 1–7 | 12.50% |
| JjinKhangJoon vs Fahkumram | 0–7 | 0.00% |
| JjinKhangJoon vs Hwoarang | 4–2 | 66.67% |
| JjinKhangJoon vs Bryan | 0–6 | 0.00% |
| JjinKhangJoon vs Nina | 3–3 | 50.00% |
| JjinKhangJoon vs Jun | 2–4 | 33.33% |
| JjinKhangJoon vs Heihachi | 4–2 | 66.67% |
| JjinKhangJoon vs Feng | 1–4 | 20.00% |
| JjinKhangJoon vs Leroy | 1–4 | 20.00% |
| JjinKhangJoon vs Claudio | 0–4 | 0.00% |
| JjinKhangJoon vs Eddy | 3–1 | 75.00% |
| JjinKhangJoon vs Lee | 2–1 | 66.67% |
| JjinKhangJoon vs Panda | 1–2 | 33.33% |
| JjinKhangJoon vs Jack-8 | 0–2 | 0.00% |
| JjinKhangJoon vs Devil Jin | 1–1 | 50.00% |
| JjinKhangJoon vs Anna | 0–2 | 0.00% |
| JjinKhangJoon vs Leo | 1–0 | 100.00% |
| JjinKhangJoon vs Zafina | 0–1 | 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.