Name history
| ag4l | |
| ight | |
| wickenching | |
| Notmycousin | |
| WickinChing | |
| walmartmanager | |
| bobono |
| ag4l vs Clive | 57–58 | 49.57% |
| ag4l vs Kazuya | 59–49 | 54.63% |
| ag4l vs Reina | 64–28 | 69.57% |
| ag4l vs Jin | 48–35 | 57.83% |
| ag4l vs Bryan | 48–30 | 61.54% |
| ag4l vs King | 38–27 | 58.46% |
| ag4l vs Steve | 38–25 | 60.32% |
| ag4l vs Eddy | 31–24 | 56.36% |
| ag4l vs Law | 26–23 | 53.06% |
| ag4l vs Lars | 36–12 | 75.00% |
| ag4l vs Paul | 25–21 | 54.35% |
| ag4l vs Lili | 31–14 | 68.89% |
| ag4l vs Lee | 23–22 | 51.11% |
| ag4l vs Leo | 17–24 | 41.46% |
| ag4l vs Azucena | 28–13 | 68.29% |
| ag4l vs Yoshimitsu | 22–18 | 55.00% |
| ag4l vs Hwoarang | 26–13 | 66.67% |
| ag4l vs Feng | 14–22 | 38.89% |
| ag4l vs Jun | 25–10 | 71.43% |
| ag4l vs Dragunov | 17–17 | 50.00% |
| ag4l vs Devil Jin | 16–14 | 53.33% |
| ag4l vs Asuka | 10–17 | 37.04% |
| ag4l vs Leroy | 11–12 | 47.83% |
| ag4l vs Lidia | 9–14 | 39.13% |
| ag4l vs Jack-8 | 7–13 | 35.00% |
| ag4l vs Xiaoyu | 12–6 | 66.67% |
| ag4l vs Shaheen | 15–3 | 83.33% |
| ag4l vs Nina | 6–11 | 35.29% |
| ag4l vs Alisa | 5–11 | 31.25% |
| ag4l vs Heihachi | 6–8 | 42.86% |
| ag4l vs Kuma | 7–4 | 63.64% |
| ag4l vs Claudio | 8–2 | 80.00% |
| ag4l vs Victor | 8–2 | 80.00% |
| ag4l vs Raven | 5–5 | 50.00% |
| ag4l vs Panda | 2–0 | 100.00% |
| ag4l 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.