| mangnani vs Armor King | 53–52 | 50.48% |
| mangnani vs Bryan | 65–36 | 64.36% |
| mangnani vs Dragunov | 50–46 | 52.08% |
| mangnani vs Hwoarang | 42–42 | 50.00% |
| mangnani vs Kazuya | 49–31 | 61.25% |
| mangnani vs Jin | 47–30 | 61.04% |
| mangnani vs Reina | 31–41 | 43.06% |
| mangnani vs Steve | 37–32 | 53.62% |
| mangnani vs Miary Zo | 27–42 | 39.13% |
| mangnani vs Asuka | 39–26 | 60.00% |
| mangnani vs Paul | 42–22 | 65.62% |
| mangnani vs Law | 23–31 | 42.59% |
| mangnani vs Heihachi | 20–29 | 40.82% |
| mangnani vs Fahkumram | 30–19 | 61.22% |
| mangnani vs Lili | 33–14 | 70.21% |
| mangnani vs Victor | 24–21 | 53.33% |
| mangnani vs Devil Jin | 21–23 | 47.73% |
| mangnani vs Clive | 14–28 | 33.33% |
| mangnani vs Yoshimitsu | 24–13 | 64.86% |
| mangnani vs Azucena | 16–20 | 44.44% |
| mangnani vs Xiaoyu | 13–20 | 39.39% |
| mangnani vs King | 20–12 | 62.50% |
| mangnani vs Jack-8 | 17–13 | 56.67% |
| mangnani vs Leo | 12–16 | 42.86% |
| mangnani vs Feng | 14–13 | 51.85% |
| mangnani vs Jun | 13–14 | 48.15% |
| mangnani vs Leroy | 15–11 | 57.69% |
| mangnani vs Claudio | 8–17 | 32.00% |
| mangnani vs Lidia | 10–15 | 40.00% |
| mangnani vs Raven | 13–11 | 54.17% |
| mangnani vs Alisa | 10–13 | 43.48% |
| mangnani vs Eddy | 4–9 | 30.77% |
| mangnani vs Lars | 1–9 | 10.00% |
| mangnani vs Nina | 5–5 | 50.00% |
| mangnani vs Lee | 4–6 | 40.00% |
| mangnani vs Shaheen | 4–5 | 44.44% |
| mangnani vs Zafina | 2–7 | 22.22% |
| mangnani vs Kuma | 3–5 | 37.50% |
| mangnani vs Anna | 4–4 | 50.00% |
| mangnani vs Panda | 1–1 | 50.00% |
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.