| BearCool vs Fahkumram | 19–21 | 47.50% |
| BearCool vs Bryan | 11–28 | 28.21% |
| BearCool vs Kazuya | 23–16 | 58.97% |
| BearCool vs King | 16–22 | 42.11% |
| BearCool vs Steve | 18–16 | 52.94% |
| BearCool vs Law | 14–19 | 42.42% |
| BearCool vs Reina | 13–17 | 43.33% |
| BearCool vs Jin | 9–18 | 33.33% |
| BearCool vs Lili | 11–16 | 40.74% |
| BearCool vs Dragunov | 17–9 | 65.38% |
| BearCool vs Eddy | 12–13 | 48.00% |
| BearCool vs Lidia | 15–10 | 60.00% |
| BearCool vs Heihachi | 13–12 | 52.00% |
| BearCool vs Hwoarang | 4–19 | 17.39% |
| BearCool vs Nina | 9–10 | 47.37% |
| BearCool vs Victor | 11–8 | 57.89% |
| BearCool vs Yoshimitsu | 9–9 | 50.00% |
| BearCool vs Lee | 8–10 | 44.44% |
| BearCool vs Lars | 8–9 | 47.06% |
| BearCool vs Azucena | 5–11 | 31.25% |
| BearCool vs Asuka | 6–9 | 40.00% |
| BearCool vs Devil Jin | 10–5 | 66.67% |
| BearCool vs Jack-8 | 6–8 | 42.86% |
| BearCool vs Leroy | 7–7 | 50.00% |
| BearCool vs Paul | 2–11 | 15.38% |
| BearCool vs Feng | 1–11 | 8.33% |
| BearCool vs Kuma | 6–6 | 50.00% |
| BearCool vs Jun | 5–7 | 41.67% |
| BearCool vs Raven | 5–6 | 45.45% |
| BearCool vs Zafina | 2–7 | 22.22% |
| BearCool vs Claudio | 3–5 | 37.50% |
| BearCool vs Xiaoyu | 4–3 | 57.14% |
| BearCool vs Leo | 3–4 | 42.86% |
| BearCool vs Alisa | 0–5 | 0.00% |
| BearCool vs Anna | 0–3 | 0.00% |
| BearCool vs Clive | 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.