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VictoryRanked
MA
ZAMAUpdated 1 day ago
Steam
JapanClub · WAKIGAKIHOUSEC100%
SteamJapanClub · WAKIGAKIHOUSEC100%伸びしろのたこし
GG
MR 1,659#43,895Last 107–3+28Last 2010–10-7
Winrate
52%
131W · 120L · 252 stored
Ranked matches
252
selected mode
Wins
131
Ranked
Losses
120
Ranked
Peak MR
1,739
Manon
Ranked MR · Manon
252 local · 0 imported · 252 on chart · 322 battles stored
Replay not requested
MAZAPlaystyle 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 | 伸びしろのたこし | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA2 | 64.8% | 32.1% | +32.8% | |
| Drive Rush (cancel) | 68.1% | 43.0% | +25.1% | |
| SA3 | 11.7% | 32.9% | -21.2% | |
| Drive Arts | 1.0% | 11.3% | -10.4% | |
| Drive Guard | 3.5% | 11.3% | -7.8% | |
| CA | 2.3% | 9.7% | -7.3% | |
| Drive Rush (parry) | 0.1% | 5.0% | -4.9% | |
| Corner pressure | 3.80 | 8.16 | -4.36 | |
| SA1 | 21.1% | 25.4% | -4.3% | |
| Time cornered | 10.10 | 8.72 | +1.38 | |
| Drive Parry | 1.00 | 1.80 | -0.80 | |
| Throws | 2.90 | 2.53 | +0.37 | |
| Perfect Parry | 0.30 | 0.64 | -0.34 | |
| Got thrown | 2.60 | 2.28 | +0.32 | |
| Got stunned | 0.20 | 0.06 | +0.14 | |
| Drive Reversal | 0.20 | 0.30 | -0.10 | |
| Got Punish Countered | 0.20 | 0.11 | +0.09 | |
| Stuns landed | 0.00 | 0.07 | -0.07 | |
| Drive Impact gauge | 1.9% | 1.8% | +0.1% | |
| Throw techs | 0.50 | 0.56 | -0.06 | |
| Punish Counters landed | 0.20 | 0.14 | +0.06 | |
| Drive Impact | 0.20 | 0.22 | -0.02 | |
| Throw parries | 0.20 | 0.20 | +0.00 |
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
Make Drive Impact a deliberate choice
Drive Impact: profile 0.1 · reference 0.21
Review five Drive Impacts and record the situation and outcome. Keep effective uses; investigate repeated failures rather than aiming for the reference frequency.
Try thisRecord Drive Impact and an ordinary attack in separate dummy slots. Mix playback and practice recognizing the difference with a response available in your current gauge state.
Supporting stats
- Drive Impact: profile 0.1 · reference 0.21
- Drive Impact gauge: profile 0.8% · reference 1.7%
Review defensive decisions
Drive Parry: profile 1.2 · reference 1.75
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 1.2 · reference 1.75
- Perfect Parry: profile 0.4 · reference 0.63
- Drive Reversal: profile 0.1 · reference 0.29
Trace how you lose or gain space
Corner pressure: profile 2.7 · reference 8
Review five trips into the corner. Identify the earlier decision that gave up space, not just the final escape attempt. Check successful corner pressure too.
Try thisRecreate one recurring position in training. Compare your usual response with a less committal alternative, then track whether you reach the corner less often over the next set.
Supporting stats
- Corner pressure: profile 2.7 · reference 8
- Time cornered: profile 10.9 · reference 8.88
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 6, 2026 · AI: dots-studio/dots-3-note-preview:free
How to beat this player
Use matchup records as scouting leads
vs Luke: 74 wins in 146 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: 74 wins in 146 games
- vs Kimberly: 31 wins in 55 games
- vs Ryu: 58 wins in 108 games
Separate a tendency from a one-off event
Recent stored ranked sample: 55 wins in 100 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: 55 wins in 100 games
Look for a repeatable punish opportunity
Got Punish Countered: profile 0.1 · reference 0.1
Use the stats as a scouting lead. Watch for an action you have already verified as punishable at that spacing; do not assume every apparent opening is unsafe.
Try thisTest one confirmed response when that action appears. If it stops appearing, return to your normal spacing instead of forcing the punish.
Supporting stats
- Got Punish Countered: profile 0.1 · reference 0.1
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 6, 2026 · AI: dots-studio/dots-3-note-preview:free