| TylraKobo vs Dragunov | 81–53 | 60.45% |
| TylraKobo vs Jin | 71–49 | 59.17% |
| TylraKobo vs Kazuya | 73–34 | 68.22% |
| TylraKobo vs King | 51–43 | 54.26% |
| TylraKobo vs Bryan | 41–40 | 50.62% |
| TylraKobo vs Reina | 43–31 | 58.11% |
| TylraKobo vs Lili | 35–29 | 54.69% |
| TylraKobo vs Yoshimitsu | 31–31 | 50.00% |
| TylraKobo vs Hwoarang | 36–22 | 62.07% |
| TylraKobo vs Victor | 38–18 | 67.86% |
| TylraKobo vs Steve | 39–16 | 70.91% |
| TylraKobo vs Law | 31–20 | 60.78% |
| TylraKobo vs Heihachi | 28–23 | 54.90% |
| TylraKobo vs Devil Jin | 26–20 | 56.52% |
| TylraKobo vs Lee | 25–20 | 55.56% |
| TylraKobo vs Jun | 23–18 | 56.10% |
| TylraKobo vs Lars | 19–17 | 52.78% |
| TylraKobo vs Lidia | 16–18 | 47.06% |
| TylraKobo vs Claudio | 17–16 | 51.52% |
| TylraKobo vs Paul | 23–9 | 71.88% |
| TylraKobo vs Asuka | 14–16 | 46.67% |
| TylraKobo vs Nina | 17–13 | 56.67% |
| TylraKobo vs Alisa | 15–14 | 51.72% |
| TylraKobo vs Leo | 15–11 | 57.69% |
| TylraKobo vs Xiaoyu | 10–15 | 40.00% |
| TylraKobo vs Feng | 18–7 | 72.00% |
| TylraKobo vs Fahkumram | 10–13 | 43.48% |
| TylraKobo vs Shaheen | 7–15 | 31.82% |
| TylraKobo vs Jack-8 | 11–10 | 52.38% |
| TylraKobo vs Raven | 10–11 | 47.62% |
| TylraKobo vs Clive | 10–9 | 52.63% |
| TylraKobo vs Eddy | 13–4 | 76.47% |
| TylraKobo vs Leroy | 10–5 | 66.67% |
| TylraKobo vs Azucena | 8–6 | 57.14% |
| TylraKobo vs Kuma | 7–4 | 63.64% |
| TylraKobo vs Zafina | 5–2 | 71.43% |
| TylraKobo vs Anna | 2–4 | 33.33% |
| TylraKobo vs Armor King | 1–4 | 20.00% |
| TylraKobo vs Miary Zo | 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.