Marisa
Updated 7 days agoCrossPlatformCrossPlatformJapanJapanClub · MasterYourGreedM100%

父(マリーザ)、長男(ルーク)

Let's Do This
Rank 36MR 1,500#245,338
Last 105–5-28Last 2010–8-28
Winrate
56%
10W · 8L · 18 stored
Ranked matches
18
selected mode
Wins
10
Ranked
Losses
8
Ranked
Peak MR
1,500
Marisa

Ranked MR · Marisa

4 local · 0 imported · 4 on chart · 105 battles stored

Latest game

DefeatRanked

Replay not requested
Marisa
父(マリーザ)、長男(ルーク) · Marisa
M. Bison
Opponent · M. Bisonhosik

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
父(マリーザ)、長男(ルーク)’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父(マリーザ)、長男(ルーク)LegendsDifference LessLegendsMore
Drive Rush (cancel)1.9%29.3%-27.5%
SA244.4%18.1%+26.3%
SA117.3%41.8%-24.5%
Drive Arts37.7%19.0%+18.8%
SA325.9%32.8%-6.9%
CA12.3%7.3%+5.0%
Drive Rush (parry)12.7%8.9%+3.8%
Corner pressure8.5010.02-1.52
Drive Parry0.201.56-1.36
Got thrown3.402.20+1.20
Throws1.202.03-0.83
Drive Guard15.2%14.5%+0.7%
Perfect Parry0.000.59-0.59
Time cornered8.407.86+0.54
Drive Impact gauge2.1%1.8%+0.3%
Throw parries0.100.28-0.18
Drive Impact0.100.20-0.10
Stuns landed0.000.09-0.09
Got Punish Countered0.200.11+0.09
Got stunned0.100.03+0.07
Drive Reversal0.400.33+0.07
Throw techs0.600.54+0.06
Punish Counters landed0.100.11-0.01
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

    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 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
    • Got Punish Countered: profile 0.2 · reference 0.11
    • Punish Counters landed: profile 0.1 · reference 0.12
  2. Review close-range choices

    Throws: profile 1.2 · reference 2.13

    Look at five close-range exchanges. Separate throw opportunities, throw attempts and defensive choices; the aggregate counts cannot show which option was correct.

    Try this

    Replay 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
    • Throws: profile 1.2 · reference 2.13
    • Got thrown: profile 3.4 · reference 2.3
    • Throw techs: profile 0.6 · reference 0.52
  3. Give each meter spend a purpose

    SA2: profile 44.4% · 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 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 44.4% · reference 20.9%
    • SA1: profile 17.3% · reference 35.7%
    • Drive Arts: profile 37.7% · reference 18.5%

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 8, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Test the Drive Impact tendency

    Drive Impact: profile 0.1 · 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 0.1 · reference 0.2
    • Drive Impact gauge: profile 2.1% · reference 1.9%
  2. Probe defense before committing

    Drive Parry: profile 0.2 · 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 this

    Try 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 0.2 · reference 1.59
    • Perfect Parry: profile 0 · reference 0.6
    • Drive Reversal: profile 0.4 · reference 0.32
  3. Build pressure without overextending

    Corner pressure: profile 8.5 · reference 10.2

    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 this

    Test 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 8.5 · reference 10.2
    • Time cornered: profile 8.4 · reference 8.39

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 8, 2026 · AI: dots-studio/dots-3-note-preview:free

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