Latest game
VictoryRanked
MA
ZAMAUpdated 17 hours ago
Steam
JapanC100%
SteamJapanC100%Kou_
Angel Devil Kingdom
MR 1,545#148,026Last 104–6-24Last 208–12-39
Winrate
44%
66W · 83L · 149 stored
Ranked matches
149
selected mode
Wins
66
Ranked
Losses
83
Ranked
Peak MR
1,607
Marisa
Ranked MR · Marisa
149 local · 125 imported · 244 on chart · 149 battles stored
Replay not requested
MAZAPlaystyle reference
Habits vs top 30 Marisa
Benchmark refreshed Sep 12, 2026, 4:25 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
MALargest absolute differences first23 habits
| Habit | Kou_ | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| Drive Rush (cancel) | 9.7% | 29.3% | -19.6% | |
| CA | 21.6% | 7.3% | +14.2% | |
| SA2 | 3.9% | 18.1% | -14.2% | |
| Drive Arts | 26.2% | 19.0% | +7.2% | |
| Corner pressure | 6.50 | 10.02 | -3.52 | |
| Drive Rush (parry) | 12.2% | 8.9% | +3.3% | |
| Drive Guard | 16.7% | 14.5% | +2.1% | |
| Time cornered | 8.60 | 7.86 | +0.74 | |
| SA1 | 41.2% | 41.8% | -0.6% | |
| SA3 | 33.3% | 32.8% | +0.6% | |
| Perfect Parry | 0.20 | 0.59 | -0.39 | |
| Throw techs | 0.90 | 0.54 | +0.36 | |
| Drive Reversal | 0.60 | 0.33 | +0.27 | |
| Drive Parry | 1.30 | 1.56 | -0.26 | |
| Got thrown | 2.40 | 2.20 | +0.20 | |
| Throws | 2.20 | 2.03 | +0.17 | |
| Drive Impact | 0.10 | 0.20 | -0.10 | |
| Got Punish Countered | 0.20 | 0.11 | +0.09 | |
| Drive Impact gauge | 1.8% | 1.8% | -0.1% | |
| Got stunned | 0.10 | 0.03 | +0.07 | |
| Throw parries | 0.30 | 0.28 | +0.02 | |
| Punish Counters landed | 0.10 | 0.11 | -0.01 | |
| Stuns landed | 0.10 | 0.09 | +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.
Checking for a saved match plan…
Uses public profile stats with OpenRouter’s free AI models. Plans are shared and saved for reuse. Suggestions are hypotheses, not replay analysis.Saved match plans
Previously generated AI plans, with their original supporting stats and data dates. Expand a plan to read both perspectives.
Marisa · Latest 100
What to improve
Review defensive decisions
Drive Reversal: profile 0.9 · reference 0.32
Compare five defensive situations: what did the opponent do, what did you choose, and what happened? Low parry or throw-tech counts alone do not establish a weakness.
Try thisRecord two different options from one troublesome situation. Practice identifying them and choosing a response, then review whether the same decision improves in your next set.
Supporting stats
- Drive Reversal: profile 0.9 · reference 0.32
- Perfect Parry: profile 0.2 · reference 0.6
Find the cause of punish events
Got Punish Countered: profile 0.2 · reference 0.11
Review five Punish Counters received and five landed. Separate whiffed attacks from unsafe actions on block before choosing what to practice.
Try thisRecreate one repeated situation in training. Check the spacing and frame meter, then practice a safer choice or a punish that actually connects.
Supporting stats
- Got Punish Countered: profile 0.2 · reference 0.11
- Punish Counters landed: profile 0.1 · reference 0.12
Give each meter spend a purpose
SA2: profile 6% · reference 20.9%
Review five resource decisions with the actual gauge visible. Note what the spend gained and what options remained; usage shares alone cannot measure efficiency.
Try thisPractice a familiar sequence with a resource spend and a conservation alternative. Compare the outcome and remaining gauge before deciding which situation calls for each.
Supporting stats
- SA2: profile 6% · reference 20.9%
- CA: profile 14% · reference 9%
AI selects and prioritizes reviewed practice plans from the cited stats. Habits cover the whole profile; character records and recent samples have separate scopes. These are ideas to test, not confirmed weaknesses or video analysis. Latest reported trends across the last 100 matches, not lifetime habit averages.
Data saved Sep 7, 2026 · AI: dots-studio/dots-3-note-preview:free
How to beat this player
Use matchup records as scouting leads
vs Ken: 7 wins in 20 games
A lower win rate suggests footage to examine, not a guaranteed counterpick. Check whether the same difficult situation appears in multiple matches.
Try thisIf you play the cited character, test one familiar situation from that footage. If the player handles it well, abandon the assumption and adapt to what they show.
Supporting stats
- vs Ken: 7 wins in 20 games
- vs Akuma: 9 wins in 20 games
- vs Ryu: 41 wins in 73 games
Separate a tendency from a one-off event
Recent stored ranked sample: 16 wins in 31 games
Scout several recent matches and compare wins with losses. Prepare around a repeated situation rather than one memorable mistake.
Try thisUse the first round to check one scouting hypothesis. If it repeats, apply your prepared adjustment; if it does not, discard it and observe a new pattern.
Supporting stats
- Recent stored ranked sample: 16 wins in 31 games
AI selects and prioritizes reviewed practice plans from the cited stats. Habits cover the whole profile; character records and recent samples have separate scopes. These are ideas to test, not confirmed weaknesses or video analysis. Latest reported trends across the last 100 matches, not lifetime habit averages.
Data saved Sep 7, 2026 · AI: dots-studio/dots-3-note-preview:free