| TLM Random vs King | 56–62 | 47.46% |
| TLM Random vs Jin | 50–45 | 52.63% |
| TLM Random vs Steve | 51–34 | 60.00% |
| TLM Random vs Eddy | 38–46 | 45.24% |
| TLM Random vs Law | 33–40 | 45.21% |
| TLM Random vs Kazuya | 25–42 | 37.31% |
| TLM Random vs Jun | 33–27 | 55.00% |
| TLM Random vs Asuka | 29–29 | 50.00% |
| TLM Random vs Hwoarang | 34–16 | 68.00% |
| TLM Random vs Fahkumram | 19–30 | 38.78% |
| TLM Random vs Dragunov | 27–16 | 62.79% |
| TLM Random vs Reina | 25–18 | 58.14% |
| TLM Random vs Armor King | 14–29 | 32.56% |
| TLM Random vs Heihachi | 24–18 | 57.14% |
| TLM Random vs Bryan | 20–15 | 57.14% |
| TLM Random vs Clive | 11–17 | 39.29% |
| TLM Random vs Leo | 14–12 | 53.85% |
| TLM Random vs Lili | 15–10 | 60.00% |
| TLM Random vs Victor | 15–9 | 62.50% |
| TLM Random vs Paul | 13–10 | 56.52% |
| TLM Random vs Xiaoyu | 14–9 | 60.87% |
| TLM Random vs Lars | 14–9 | 60.87% |
| TLM Random vs Azucena | 11–12 | 47.83% |
| TLM Random vs Lidia | 9–12 | 42.86% |
| TLM Random vs Anna | 12–9 | 57.14% |
| TLM Random vs Devil Jin | 6–13 | 31.58% |
| TLM Random vs Lee | 6–12 | 33.33% |
| TLM Random vs Claudio | 9–7 | 56.25% |
| TLM Random vs Jack-8 | 12–2 | 85.71% |
| TLM Random vs Nina | 7–7 | 50.00% |
| TLM Random vs Feng | 3–10 | 23.08% |
| TLM Random vs Leroy | 8–5 | 61.54% |
| TLM Random vs Alisa | 3–9 | 25.00% |
| TLM Random vs Shaheen | 7–4 | 63.64% |
| TLM Random vs Yoshimitsu | 4–6 | 40.00% |
| TLM Random vs Panda | 4–6 | 40.00% |
| TLM Random vs Kuma | 5–3 | 62.50% |
| TLM Random vs Zafina | 3–4 | 42.86% |
| TLM Random vs Miary Zo | 3–0 | 100.00% |
| TLM Random vs Raven | 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.