Latest game
VictoryRanked
MA
LUMAUpdated 7 days ago
Steam
JapanClub · BarZinMAMAC100%
SteamJapanClub · BarZinMAMAC100%SKR｜MizuPINK
A Wolf Out For Vengeance
MR 1,822#6,408Last 109–1+60Last 2017–3+103
Winrate
53%
38W · 34L · 72 stored
Ranked matches
72
selected mode
Wins
38
Ranked
Losses
34
Ranked
Peak MR
1,863
Manon
Ranked MR · Manon
72 local · 0 imported · 72 on chart · 72 battles stored
Replay not requested
MALUPlaystyle reference
Habits vs top 30 Manon
Benchmark refreshed Sep 7, 2026, 7:24 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
MALargest absolute differences first23 habits
| Habit | SKR｜MizuPINK | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA2 | 61.3% | 32.1% | +29.2% | |
| SA1 | 12.9% | 25.4% | -12.5% | |
| SA3 | 20.4% | 32.9% | -12.4% | |
| Drive Rush (cancel) | 48.8% | 43.0% | +5.8% | |
| Drive Arts | 6.5% | 11.3% | -4.8% | |
| CA | 5.4% | 9.7% | -4.3% | |
| Corner pressure | 4.90 | 8.16 | -3.26 | |
| Drive Guard | 8.8% | 11.3% | -2.5% | |
| Drive Rush (parry) | 3.2% | 5.0% | -1.8% | |
| Time cornered | 9.30 | 8.72 | +0.58 | |
| Drive Impact gauge | 1.4% | 1.8% | -0.4% | |
| Throws | 2.20 | 2.53 | -0.33 | |
| Perfect Parry | 0.40 | 0.64 | -0.24 | |
| Drive Parry | 1.60 | 1.80 | -0.20 | |
| Throw parries | 0.00 | 0.20 | -0.20 | |
| Got thrown | 2.40 | 2.28 | +0.12 | |
| Drive Reversal | 0.40 | 0.30 | +0.10 | |
| Stuns landed | 0.00 | 0.07 | -0.07 | |
| Got stunned | 0.00 | 0.06 | -0.06 | |
| Throw techs | 0.50 | 0.56 | -0.06 | |
| Punish Counters landed | 0.10 | 0.14 | -0.04 | |
| Drive Impact | 0.20 | 0.22 | -0.02 | |
| Got Punish Countered | 0.10 | 0.11 | -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.
Manon · Latest 100
What to improve
Review close-range choices
Throw techs: profile 0.5 · reference 0.56
Look at five close-range exchanges. Separate throw opportunities, throw attempts and defensive choices; the aggregate counts cannot show which option was correct.
Try thisReplay one recurring situation in training with both a strike and a throw recorded. Practice your chosen responses, then check how often you make that choice deliberately in matches.
Supporting stats
- Throw techs: profile 0.5 · reference 0.56
- Got thrown: profile 2.4 · reference 2.28
Give each meter spend a purpose
SA2: profile 61.3% · reference 32.1%
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 61.3% · reference 32.1%
- SA3: profile 20.4% · reference 32.9%
- SA1: profile 12.9% · reference 25.4%
Find the cause of punish events
Punish Counters landed: profile 0.1 · reference 0.14
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
- Punish Counters landed: profile 0.1 · reference 0.14
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 Luke: 85 wins in 181 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: 85 wins in 181 games
- vs Dee Jay: 147 wins in 177 games
- vs Alex: 57 wins in 138 games
Separate a tendency from a one-off event
Recent stored ranked sample: 32 wins in 65 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: 32 wins in 65 games
Build pressure without overextending
Corner pressure: profile 4.9 · reference 8.16
Look for chances to gain space with familiar options. Once the opponent is cornered, observe how they actually try to leave before selecting an adjustment.
Try thisTest one pressure sequence you know well. If an escape repeats, rehearse an answer to that exact option; if they vary their defense, avoid committing to a single read.
Supporting stats
- Corner pressure: profile 4.9 · reference 8.16
- Time cornered: profile 9.3 · reference 8.72
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