| Lærë vs King | 34–37 | 47.89% |
| Lærë vs Jin | 32–29 | 52.46% |
| Lærë vs Kazuya | 21–22 | 48.84% |
| Lærë vs Reina | 17–23 | 42.50% |
| Lærë vs Bryan | 14–24–1 | 36.84% |
| Lærë vs Heihachi | 13–24 | 35.14% |
| Lærë vs Law | 15–21 | 41.67% |
| Lærë vs Steve | 13–23 | 36.11% |
| Lærë vs Hwoarang | 19–14 | 57.58% |
| Lærë vs Jun | 11–19 | 36.67% |
| Lærë vs Jack-8 | 8–15 | 34.78% |
| Lærë vs Dragunov | 8–15 | 34.78% |
| Lærë vs Nina | 8–15 | 34.78% |
| Lærë vs Eddy | 10–13 | 43.48% |
| Lærë vs Lili | 10–10 | 50.00% |
| Lærë vs Yoshimitsu | 8–11 | 42.11% |
| Lærë vs Lars | 7–11 | 38.89% |
| Lærë vs Xiaoyu | 7–9 | 43.75% |
| Lærë vs Devil Jin | 3–13 | 18.75% |
| Lærë vs Azucena | 10–6 | 62.50% |
| Lærë vs Clive | 8–8 | 50.00% |
| Lærë vs Paul | 5–10 | 33.33% |
| Lærë vs Fahkumram | 7–7 | 50.00% |
| Lærë vs Anna | 4–9 | 30.77% |
| Lærë vs Asuka | 1–11 | 8.33% |
| Lærë vs Claudio | 9–3 | 75.00% |
| Lærë vs Victor | 6–6 | 50.00% |
| Lærë vs Alisa | 2–9 | 18.18% |
| Lærë vs Feng | 3–7 | 30.00% |
| Lærë vs Leo | 1–8 | 11.11% |
| Lærë vs Lidia | 5–4 | 55.56% |
| Lærë vs Zafina | 1–7 | 12.50% |
| Lærë vs Kuma | 4–3 | 57.14% |
| Lærë vs Leroy | 3–4 | 42.86% |
| Lærë vs Lee | 2–4 | 33.33% |
| Lærë vs Panda | 2–4 | 33.33% |
| Lærë vs Armor King | 1–4 | 20.00% |
| Lærë vs Shaheen | 4–0 | 100.00% |
| Lærë vs Raven | 0–4 | 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.