Marisa
Updated 4 days agoSteamSteamJapanJapanClub · StrawberryCreamM97%

モスキートハンドクラッシャー狛

That Sumo Idiot
Rank 36MR 1,604#79,738
Last 107–3+39Last 2010–10-2
Winrate
50%
30W · 30L · 60 stored
Ranked matches
60
selected mode
Wins
30
Ranked
Losses
30
Ranked
Peak MR
1,604
Marisa

Ranked MR · Marisa

57 local · 0 imported · 57 on chart · 60 battles stored

Latest game

DefeatRanked

Replay not requested
E. Honda
モスキートハンドクラッシャー狛 · E. Honda
Ryu
Opponent · RyuJuketsu

Playstyle 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

Marisa
モスキートハンドクラッシャー狛’s Marisa benchmark

Compared with the average habits of the top 30 sampled Marisa players.

Tucker Ducker 2225 · karura 2205 · jjnj 2164 · kurobuchi_b09 2158 · 紺外郎/Kon_Uiro 2129 · +25 others

Largest absolute differences first23 habits
Habitモスキートハンドクラッシャー狛LegendsDifference LessLegendsMore
CA25.4%7.3%+18.0%
Drive Rush (cancel)16.3%29.3%-13.0%
SA29.9%18.1%-8.3%
SA133.8%41.8%-8.0%
Drive Rush (parry)0.9%8.9%-8.0%
Drive Arts26.7%19.0%+7.7%
Drive Guard9.6%14.5%-4.9%
Drive Impact gauge5.0%1.8%+3.2%
Throws4.302.03+2.27
Got thrown4.202.20+2.00
SA331.0%32.8%-1.8%
Throw techs2.000.54+1.46
Corner pressure11.0010.02+0.98
Drive Parry2.301.56+0.74
Time cornered8.507.86+0.64
Drive Reversal0.000.33-0.33
Drive Impact0.400.20+0.20
Punish Counters landed0.300.11+0.19
Got Punish Countered0.300.11+0.19
Throw parries0.400.28+0.12
Stuns landed0.200.09+0.11
Perfect Parry0.500.59-0.09
Got stunned0.000.03-0.03
FROM STATS TO PRACTICE

Match plan

Latest 100

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

  1. Find the cause of punish events

    Punish Counters landed: profile 0.3 · 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 this

    Recreate 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 0.3 · reference 0.11
    • Got Punish Countered: profile 0.3 · reference 0.11
  2. Review defensive decisions

    Throw techs: profile 2 · reference 0.54

    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 this

    Record 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
    • Throw techs: profile 2 · reference 0.54
  3. Give each meter spend a purpose

    SA2: profile 9.9% · reference 18.1%

    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 this

    Practice 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 9.9% · reference 18.1%
    • SA3: profile 31% · reference 32.8%

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: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Use matchup records as scouting leads

    vs Char 253: 272 wins in 553 games

    A lower win rate suggests footage to examine, not a guaranteed counterpick. Check whether the same difficult situation appears in multiple matches.

    Try this

    If 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 Char 253: 272 wins in 553 games
  2. Test the Drive Impact tendency

    Drive Impact: profile 0.4 · reference 0.2

    Observe whether Drive Impact repeats in a particular situation. Prepare a response you have verified in training, while respecting range, recovery and available gauge.

    Try this

    Revisit that situation with a less committal approach. If the Impact appears, use your practiced response; if it does not, resume your usual game plan.

    Supporting stats
    • Drive Impact: profile 0.4 · reference 0.2
    • Drive Impact gauge: profile 5% · reference 1.8%
  3. Test the close-range pattern

    Throws: profile 4.3 · reference 2.03

    Observe actual strike, throw and defensive choices at close range. Change one part of your familiar mix only after a tendency appears.

    Try this

    If the same response repeats twice, try a different option in that situation. If the player changes their response, return to varied choices instead of assuming the pattern is permanent.

    Supporting stats
    • Throws: profile 4.3 · reference 2.03
    • Got thrown: profile 4.2 · reference 2.2

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: dots-studio/dots-3-note-preview:free

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