Alex
Updated 2 days agoSteamSteamOtherOtherClub · teamDBMC100%

ゴッドアーム鰹

I'm Too Cool!
Rank 36MR 1,895#3,944
Last 106–4+14Last 2010–10-3
Winrate
57%
145W · 111L · 256 stored
Ranked matches
256
selected mode
Wins
145
Ranked
Losses
111
Ranked
Peak MR
1,913
Alex

Ranked MR · Alex

231 local · 0 imported · 231 on chart · 374 battles stored

Latest game

DefeatRanked

Replay not requested
Zangief
ゴッドアーム鰹 · Zangief
Blanka
Opponent · BlankaGe0rge.@フォカヌポゥ

Playstyle reference

Habits vs top 30 Alex

Benchmark refreshed Sep 14, 2026, 4:24 AM

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

Alex
ゴッドアーム鰹’s Alex benchmark

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

きどーー 2201 · cream 2141 · Shinto 2140 · ゆーざー 2129 · ラッシュ中段どわーw 2127 · +25 others

Largest absolute differences first23 habits
Habitゴッドアーム鰹LegendsDifference LessLegendsMore
SA152.6%38.9%+13.7%
SA214.9%27.6%-12.7%
Drive Rush (cancel)27.3%33.2%-5.9%
Drive Rush (parry)10.5%8.2%+2.3%
Time cornered7.609.50-1.90
CA7.0%8.3%-1.3%
Drive Parry0.901.62-0.72
Corner pressure9.4010.07-0.67
Drive Guard14.7%14.0%+0.6%
Drive Impact gauge2.6%2.0%+0.6%
Drive Arts13.6%13.2%+0.4%
SA325.4%25.2%+0.3%
Perfect Parry0.500.64-0.14
Throw techs0.400.51-0.11
Got thrown2.102.18-0.08
Drive Reversal0.500.43+0.07
Throw parries0.200.27-0.07
Punish Counters landed0.200.14+0.06
Throws2.202.24-0.04
Got stunned0.000.04-0.04
Drive Impact0.200.23-0.03
Got Punish Countered0.100.11-0.01
Stuns landed0.100.10+0.00
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.

Alex · Latest 100

What to improve

  1. Make Drive Impact a deliberate choice

    Drive Impact: profile 0.2 · reference 0.2

    Review five Drive Impacts and record the situation and outcome. Keep effective uses; investigate repeated failures rather than aiming for the reference frequency.

    Try this

    Record 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 0.2 · reference 0.2
    • Drive Impact gauge: profile 1.8% · reference 1.7%
  2. Find the cause of punish events

    Punish Counters landed: profile 0.1 · reference 0.12

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

    SA1: profile 62.1% · reference 43%

    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
    • SA1: profile 62.1% · reference 43%
    • SA3: profile 12.9% · reference 22.1%
    • CA: profile 3.4% · reference 6.5%

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 7, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Probe defense before committing

    Drive Reversal: profile 0.7 · reference 0.47

    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 Reversal: profile 0.7 · reference 0.47
    • Perfect Parry: profile 0.6 · reference 0.7
    • Drive Parry: profile 1.1 · reference 1.63
  2. Build pressure without overextending

    Corner pressure: profile 6.9 · reference 9.01

    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 6.9 · reference 9.01
    • Time cornered: profile 10.8 · reference 9.88
  3. Test the close-range pattern

    Throws: profile 2.5 · reference 2.32

    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 2.5 · reference 2.32
    • Got thrown: profile 2.1 · reference 2.12
    • Throw techs: profile 0.4 · reference 0.48

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

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