| 北斗@Lyco vs Paul | 73–52 | 58.40% |
| 北斗@Lyco vs Lidia | 59–53 | 52.68% |
| 北斗@Lyco vs Kazuya | 60–48 | 55.56% |
| 北斗@Lyco vs Dragunov | 62–41 | 60.19% |
| 北斗@Lyco vs King | 66–34 | 66.00% |
| 北斗@Lyco vs Bryan | 54–41 | 56.84% |
| 北斗@Lyco vs Reina | 44–43 | 50.57% |
| 北斗@Lyco vs Jin | 49–35 | 58.33% |
| 北斗@Lyco vs Lili | 53–23 | 69.74% |
| 北斗@Lyco vs Hwoarang | 42–33 | 56.00% |
| 北斗@Lyco vs Heihachi | 29–42 | 40.85% |
| 北斗@Lyco vs Asuka | 34–32 | 51.52% |
| 北斗@Lyco vs Alisa | 25–32 | 43.86% |
| 北斗@Lyco vs Yoshimitsu | 29–26 | 52.73% |
| 北斗@Lyco vs Victor | 24–30 | 44.44% |
| 北斗@Lyco vs Feng | 24–27 | 47.06% |
| 北斗@Lyco vs Jack-8 | 21–28 | 42.86% |
| 北斗@Lyco vs Law | 25–23 | 52.08% |
| 北斗@Lyco vs Azucena | 22–24 | 47.83% |
| 北斗@Lyco vs Steve | 23–22 | 51.11% |
| 北斗@Lyco vs Leo | 34–11 | 75.56% |
| 北斗@Lyco vs Leroy | 30–14 | 68.18% |
| 北斗@Lyco vs Jun | 20–24 | 45.45% |
| 北斗@Lyco vs Eddy | 26–17 | 60.47% |
| 北斗@Lyco vs Nina | 19–23 | 45.24% |
| 北斗@Lyco vs Lars | 17–23 | 42.50% |
| 北斗@Lyco vs Devil Jin | 13–21 | 38.24% |
| 北斗@Lyco vs Lee | 14–20 | 41.18% |
| 北斗@Lyco vs Claudio | 27–6 | 81.82% |
| 北斗@Lyco vs Xiaoyu | 19–12 | 61.29% |
| 北斗@Lyco vs Zafina | 13–13 | 50.00% |
| 北斗@Lyco vs Kuma | 13–11 | 54.17% |
| 北斗@Lyco vs Shaheen | 14–8 | 63.64% |
| 北斗@Lyco vs Raven | 9–12 | 42.86% |
| 北斗@Lyco vs Panda | 7–5 | 58.33% |
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.