TF_Willboxer vs King | 9–16 | 36.00% |
TF_Willboxer vs Reina | 16–9 | 64.00% |
TF_Willboxer vs Jin | 12–7 | 63.16% |
TF_Willboxer vs Asuka | 8–11 | 42.11% |
TF_Willboxer vs Eddy | 7–7 | 50.00% |
TF_Willboxer vs Law | 4–8 | 33.33% |
TF_Willboxer vs Clive | 8–4 | 66.67% |
TF_Willboxer vs Hwoarang | 3–8 | 27.27% |
TF_Willboxer vs Bryan | 3–8 | 27.27% |
TF_Willboxer vs Kazuya | 5–6 | 45.45% |
TF_Willboxer vs Xiaoyu | 2–8 | 20.00% |
TF_Willboxer vs Devil Jin | 5–4 | 55.56% |
TF_Willboxer vs Dragunov | 0–8 | 0.00% |
TF_Willboxer vs Nina | 2–5 | 28.57% |
TF_Willboxer vs Yoshimitsu | 5–1 | 83.33% |
TF_Willboxer vs Jack-8 | 1–4 | 20.00% |
TF_Willboxer vs Lili | 2–3 | 40.00% |
TF_Willboxer vs Azucena | 4–1 | 80.00% |
TF_Willboxer vs Lars | 2–2 | 50.00% |
TF_Willboxer vs Alisa | 2–2 | 50.00% |
TF_Willboxer vs Jun | 2–2 | 50.00% |
TF_Willboxer vs Raven | 2–2 | 50.00% |
TF_Willboxer vs Lidia | 0–4 | 0.00% |
TF_Willboxer vs Steve | 1–2 | 33.33% |
TF_Willboxer vs Feng | 1–2 | 33.33% |
TF_Willboxer vs Lee | 1–2 | 33.33% |
TF_Willboxer vs Heihachi | 2–1 | 66.67% |
TF_Willboxer vs Paul | 0–2 | 0.00% |
TF_Willboxer vs Claudio | 0–2 | 0.00% |
TF_Willboxer vs Shaheen | 0–2 | 0.00% |
TF_Willboxer vs Zafina | 1–1 | 50.00% |
TF_Willboxer vs Leroy | 0–2 | 0.00% |
TF_Willboxer vs Victor | 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.