Updated 4 days agoCrossPlatformUnited StatesC100%

azconn

Let's Do This

None

R39
Winrate
0W · 0L · 0 stored
Ranked matches
0
selected mode
Wins
0
Ranked
Losses
0
Ranked
Peak MR

Ranked MR · Marisa

0 local · 0 imported · 0 on chart · 19 battles stored

Not enough ranked MR points in this range yet.

Latest game

DefeatCasual

Replay not requested
azconn · Marisa
Opponent · LilyLewda

Playstyle reference

Habits vs top 30 Marisa

Benchmark refreshed Sep 16, 2026, 1:28 PM

Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details

azconn’s Marisa benchmark

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

Tucker Ducker 2257 · karura 2236 · jjnj 2164 · zeno 2163 · 紺外郎/Kon_Uiro 2158 · +25 others

Largest absolute differences first23 habits
HabitazconnLegendsDifference LessLegendsMore
Drive Arts48.2%19.6%+28.5%
CA37.9%9.6%+28.3%
SA110.3%38.1%-27.8%
Drive Rush (cancel)0.0%27.7%-27.7%
SA23.4%17.8%-14.3%
SA348.3%34.5%+13.8%
Drive Rush (parry)3.4%9.6%-6.2%
Drive Parry3.701.50+2.20
Corner pressure7.609.73-2.13
Throws0.602.01-1.41
Drive Guard16.5%15.1%+1.4%
Time cornered7.308.63-1.33
Throw techs0.000.55-0.55
Perfect Parry0.300.55-0.25
Got thrown2.102.31-0.21
Got Punish Countered0.300.12+0.18
Drive Reversal0.200.32-0.12
Throw parries0.300.25+0.05
Got stunned0.000.04-0.04
Drive Impact gauge2.1%2.0%+0.0%
Punish Counters landed0.100.12-0.02
Stuns landed0.100.11-0.01
Drive Impact0.200.21-0.01
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. Review close-range choices

    Throw techs: profile 0 · reference 0.52

    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
    • Throw techs: profile 0 · reference 0.52
    • Throws: profile 0.6 · reference 2.13
    • Got thrown: profile 2.1 · reference 2.3
  2. Find the cause of punish events

    Got Punish Countered: 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
    • Got Punish Countered: profile 0.3 · reference 0.11
    • Punish Counters landed: profile 0.1 · reference 0.12
  3. Give each meter spend a purpose

    SA2: profile 3.4% · 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 3.4% · reference 20.9%
    • SA1: profile 10.3% · reference 35.7%
    • CA: profile 37.9% · reference 9%

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

  1. Probe defense before committing

    Drive Parry: profile 3.7 · 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 3.7 · reference 1.59
    • Drive Reversal: profile 0.2 · reference 0.32
    • Got thrown: profile 2.1 · reference 2.3
  2. Test the close-range pattern

    Throws: profile 0.6 · reference 2.13

    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 0.6 · reference 2.13
    • Throw techs: profile 0 · reference 0.52
    • Got thrown: profile 2.1 · reference 2.3
  3. Test the Drive Impact tendency

    Drive Impact: profile 0.2 · 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 0.2 · reference 0.2
    • Drive Impact gauge: profile 2.1% · reference 1.9%

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

Public data

Public statistics and datasets

Results from 19 of 19 stored matches. Explore the datasets for the full saved history.

Results in stored match sample

1 row
Wins
11games
Losses
8games
Draws
0games
Games
19games
Win rate (draw = half win)
57.89%
Field definitions 5 fields
Wins
Wins · games. wins
Losses
Losses · games. losses
Draws
Draws · games. draws
Games
Games · games. total
Win rate (draw = half win)
Win rate (draw = half win) · percent. winRate Displayed to two decimal places; JSON retains full precision.

Current saved character ratings

11 rows

Scroll if needed to compare columns. Expand Details for the remaining fields.

Current saved character ratings. 11 rows on page 1; 11 rows total.
CharacterMRMR pointsLPLP pointsDetails
Zangief0-1
Details for Current saved character ratings, row 1
Character ID
6
JP0-1
Details for Current saved character ratings, row 2
Character ID
7
Dhalsim0-1
Details for Current saved character ratings, row 3
Character ID
8
Marisa0-1
Details for Current saved character ratings, row 4
Character ID
17
Ed0-1
Details for Current saved character ratings, row 5
Character ID
19
Akuma0-1
Details for Current saved character ratings, row 6
Character ID
22
Sagat0-1
Details for Current saved character ratings, row 7
Character ID
25
M. Bison0-1
Details for Current saved character ratings, row 8
Character ID
26
Terry0-1
Details for Current saved character ratings, row 9
Character ID
27
Mai0-1
Details for Current saved character ratings, row 10
Character ID
28
Ingrid0-1
Details for Current saved character ratings, row 11
Character ID
32
Field definitions 4 fields
Character ID
Character ID · identifier. characterId
Character
Character · text. character
MR
Master Rating · MR points. mr
LP
League Points · LP points. lp

Last saved update: .

Latest saved profile; local results cover at most the newest 10,000 stored matches across all modes.

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