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MA
LUMAUpdated 6 days ago
CrossPlatform
JapanClub · AsadoreNGDaikonC100%
CrossPlatformJapanClub · AsadoreNGDaikonC100%Buriri_Daikon
RISE ABOVE
MR 1,605#75,945Last 107–3+31Last 2012–8+32
Winrate
53%
34W · 30L · 64 stored
Ranked matches
64
selected mode
Wins
34
Ranked
Losses
30
Ranked
Peak MR
1,605
Marisa
Ranked MR · Marisa
61 local · 0 imported · 61 on chart · 153 battles stored
Replay not requested
MALUPlaystyle 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 | Buriri_Daikon | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA3 | 25.4% | 32.8% | -7.4% | |
| CA | 11.9% | 7.3% | +4.6% | |
| Drive Arts | 16.6% | 19.0% | -2.4% | |
| Time cornered | 10.00 | 7.86 | +2.14 | |
| Drive Rush (cancel) | 27.8% | 29.3% | -1.6% | |
| SA1 | 43.3% | 41.8% | +1.5% | |
| SA2 | 19.4% | 18.1% | +1.3% | |
| Throws | 2.60 | 2.03 | +0.57 | |
| Drive Impact gauge | 1.3% | 1.8% | -0.6% | |
| Corner pressure | 9.50 | 10.02 | -0.52 | |
| Got thrown | 2.70 | 2.20 | +0.50 | |
| Drive Rush (parry) | 8.6% | 8.9% | -0.3% | |
| Drive Guard | 14.7% | 14.5% | +0.2% | |
| Throw parries | 0.40 | 0.28 | +0.12 | |
| Perfect Parry | 0.70 | 0.59 | +0.11 | |
| Drive Impact | 0.10 | 0.20 | -0.10 | |
| Drive Parry | 1.50 | 1.56 | -0.06 | |
| Throw techs | 0.50 | 0.54 | -0.04 | |
| Drive Reversal | 0.30 | 0.33 | -0.03 | |
| Got stunned | 0.00 | 0.03 | -0.03 | |
| Got Punish Countered | 0.10 | 0.11 | -0.01 | |
| 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
Study a recurring matchup situation
vs Luke: 41 wins in 62 games
Use the cited matchup record to choose footage to review. Look for a repeated decision across several losses, and compare it with a win before drawing a conclusion.
Try thisPick one recurring situation against that character. Recreate it in training, verify an alternative response, and track that decision across the next five matches.
Supporting stats
- vs Luke: 41 wins in 62 games
- vs Akuma: 34 wins in 47 games
- vs Yasmine: 16 wins in 31 games
Compare decisions across wins and losses
Recent stored ranked sample: 19 wins in 32 games
Choose two wins and two losses from the recent stored sample. Find one decision that changes between them; the record alone cannot explain why results changed.
Try thisWrite down one specific decision to test in your next five games. Review whether you executed it and what happened, rather than judging the drill only by wins.
Supporting stats
- Recent stored ranked sample: 19 wins in 32 games
Review defensive decisions
Drive Parry: profile 1.5 · reference 1.59
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 Parry: profile 1.5 · reference 1.59
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 9, 2026 · AI: nex-agi/nex-n2.5-mini:free
How to beat this player
Use matchup records as scouting leads
vs Luke: 41 wins in 62 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 Luke: 41 wins in 62 games
- vs Akuma: 34 wins in 47 games
- vs Yasmine: 16 wins in 31 games
Separate a tendency from a one-off event
Recent stored ranked sample: 19 wins in 32 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: 19 wins in 32 games
Probe defense before committing
Drive Parry: profile 1.5 · reference 1.59
Test one familiar pressure situation and observe the actual response. Use that observation to vary your next choice; do not infer a success rate from event counts.
Try thisTry your usual strike/throw decision in a situation you understand. Repeat only if the response is consistent; if they adapt, vary your timing or reset to neutral.
Supporting stats
- Drive Parry: profile 1.5 · reference 1.59
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 9, 2026 · AI: nex-agi/nex-n2.5-mini:free