| lam马东锡 vs Armor King | 33–50 | 39.76% |
| lam马东锡 vs Dragunov | 37–44 | 45.68% |
| lam马东锡 vs Jin | 50–30 | 62.50% |
| lam马东锡 vs Paul | 32–46 | 41.03% |
| lam马东锡 vs Kazuya | 35–41 | 46.05% |
| lam马东锡 vs Asuka | 37–32 | 53.62% |
| lam马东锡 vs Lili | 33–35 | 48.53% |
| lam马东锡 vs King | 31–36 | 46.27% |
| lam马东锡 vs Hwoarang | 36–30 | 54.55% |
| lam马东锡 vs Reina | 36–21 | 63.16% |
| lam马东锡 vs Bryan | 26–30 | 46.43% |
| lam马东锡 vs Law | 28–25 | 52.83% |
| lam马东锡 vs Miary Zo | 25–22 | 53.19% |
| lam马东锡 vs Xiaoyu | 24–20 | 54.55% |
| lam马东锡 vs Steve | 33–10 | 76.74% |
| lam马东锡 vs Heihachi | 20–22 | 47.62% |
| lam马东锡 vs Fahkumram | 26–13 | 66.67% |
| lam马东锡 vs Azucena | 13–24 | 35.14% |
| lam马东锡 vs Lars | 21–15 | 58.33% |
| lam马东锡 vs Jun | 17–18 | 48.57% |
| lam马东锡 vs Kuma | 19–13 | 59.38% |
| lam马东锡 vs Eddy | 11–21 | 34.38% |
| lam马东锡 vs Yoshimitsu | 16–13 | 55.17% |
| lam马东锡 vs Lidia | 11–18 | 37.93% |
| lam马东锡 vs Nina | 12–16 | 42.86% |
| lam马东锡 vs Devil Jin | 12–15 | 44.44% |
| lam马东锡 vs Lee | 13–14 | 48.15% |
| lam马东锡 vs Victor | 9–18 | 33.33% |
| lam马东锡 vs Clive | 12–15 | 44.44% |
| lam马东锡 vs Alisa | 13–10 | 56.52% |
| lam马东锡 vs Zafina | 12–11 | 52.17% |
| lam马东锡 vs Leo | 11–11 | 50.00% |
| lam马东锡 vs Leroy | 7–15 | 31.82% |
| lam马东锡 vs Raven | 7–14 | 33.33% |
| lam马东锡 vs Jack-8 | 10–9 | 52.63% |
| lam马东锡 vs Feng | 4–14 | 22.22% |
| lam马东锡 vs Panda | 10–6 | 62.50% |
| lam马东锡 vs Anna | 10–5 | 66.67% |
| lam马东锡 vs Claudio | 4–10 | 28.57% |
| lam马东锡 vs Shaheen | 2–0 | 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.