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KEKEMACHA/天地魔闘 — Street Fighter 6 Stats
Ranked analytics on SF6 Stats · main Ken · peak MR 2,001. MR and LP charts, match history, matchups, rivals, and habits vs Legends.
KEUpdated 2 hours ago
Steam
JapanClub · TENCHIMATOHC100%
SteamJapanClub · TENCHIMATOHC100%MACHA/天地魔闘
Ever Improving
MR 2,001#1,414Last 105–5+6Last 208–12-21
Winrate
42%
10W · 14L · 24 stored
Ranked matches
24
selected mode
Wins
10
Ranked
Losses
14
Ranked
Peak MR
2,001
Ken
Ranked MR · Ken
24 local · 0 imported · 24 on chart · 53 battles stored
Replay not requested
KEKEPlaystyle reference
Habits vs top 30 Ken
Benchmark refreshed Sep 11, 2026, 7:22 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
KELargest absolute differences first23 habits
| Habit | MACHA/天地魔闘 | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA2 | 42.6% | 25.9% | +16.7% | |
| SA3 | 27.0% | 35.8% | -8.7% | |
| Drive Rush (cancel) | 44.3% | 38.2% | +6.1% | |
| SA1 | 21.3% | 27.3% | -6.0% | |
| Drive Arts | 20.1% | 14.9% | +5.2% | |
| Corner pressure | 18.10 | 13.12 | +4.98 | |
| Drive Guard | 8.4% | 12.7% | -4.3% | |
| Time cornered | 5.50 | 8.95 | -3.45 | |
| Drive Rush (parry) | 4.0% | 6.8% | -2.8% | |
| CA | 9.0% | 11.0% | -2.0% | |
| Drive Impact gauge | 2.1% | 1.4% | +0.7% | |
| Got thrown | 1.70 | 2.26 | -0.56 | |
| Perfect Parry | 0.40 | 0.84 | -0.44 | |
| Drive Parry | 1.70 | 1.89 | -0.19 | |
| Throws | 2.40 | 2.57 | -0.17 | |
| Throw techs | 0.30 | 0.44 | -0.14 | |
| Drive Reversal | 0.10 | 0.23 | -0.13 | |
| Got Punish Countered | 0.20 | 0.08 | +0.12 | |
| Punish Counters landed | 0.20 | 0.10 | +0.10 | |
| Got stunned | 0.00 | 0.05 | -0.05 | |
| Stuns landed | 0.10 | 0.07 | +0.03 | |
| Throw parries | 0.20 | 0.21 | -0.01 | |
| Drive Impact | 0.20 | 0.19 | +0.01 |
FROM STATS TO PRACTICE
Latest 100Match plan
Turn this profile’s habits and results into ideas to test. Habits cover all characters; the selected character sets the comparison group.
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Uses public profile stats with OpenRouter’s free AI models. Plans are shared and saved for reuse. Suggestions are hypotheses, not replay analysis.