JP
Updated 1 day agoSteamSteamJapanJapanC100%

magogosora

Hellshake Yano
Rank 36MR 1,513#207,609
Last 103–7-30Last 207–11-34
Winrate
39%
7W · 11L · 18 stored
Ranked matches
18
selected mode
Wins
7
Ranked
Losses
11
Ranked
Peak MR
1,536
JP

Ranked MR · JP

18 local · 35 imported · 53 on chart · 63 battles stored

Latest game

VictoryRanked

Replay not requested
JP
magogosora · JP
Elena
Opponent · Elenaミリーゼ

Playstyle reference

Habits vs top 30 JP

Benchmark refreshed Sep 3, 2026, 4:26 PM

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

JP
magogosora’s JP benchmark

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

takepi 2276 · 三田JP 2142 · あーるゆーおー 2134 · -DingChunQiu- 2121 · Nth Oniki 2110 · +25 others

Largest absolute differences first23 habits
HabitmagogosoraLegendsDifference LessLegendsMore
SA227.8%56.6%-28.9%
SA343.3%19.2%+24.2%
Drive Rush (cancel)41.9%23.1%+18.8%
Drive Arts14.3%32.1%-17.9%
CA10.0%5.0%+5.0%
Drive Guard7.9%12.8%-4.9%
Corner pressure6.1010.77-4.67
Time cornered14.3012.04+2.26
Drive Parry0.902.07-1.17
Drive Rush (parry)5.6%6.5%-0.9%
Perfect Parry0.000.79-0.79
Drive Impact gauge2.7%2.1%+0.6%
Drive Reversal0.600.13+0.47
SA118.9%19.2%-0.3%
Throw parries0.600.41+0.19
Punish Counters landed0.300.13+0.17
Drive Impact0.500.34+0.16
Got thrown2.002.13-0.13
Got Punish Countered0.200.08+0.12
Stuns landed0.000.09-0.09
Throw techs0.300.39-0.09
Got stunned0.100.04+0.06
Throws2.001.97+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.

JP · Latest 100

What to improve

  1. Review defensive decisions

    Drive Reversal: profile 0.4 · reference 0.13

    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
    • Drive Reversal: profile 0.4 · reference 0.13
    • Drive Parry: profile 0.5 · reference 2.07
    • Perfect Parry: profile 0.2 · reference 0.79
  2. Review close-range choices

    Throw techs: profile 0.7 · reference 0.39

    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 0.7 · reference 0.39
    • Throws: profile 1.8 · reference 1.97
    • Got thrown: profile 2.8 · reference 2.13
  3. Give each meter spend a purpose

    SA3: profile 48.5% · reference 19.2%

    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
    • SA3: profile 48.5% · reference 19.2%
    • SA1: profile 6.1% · reference 19.2%
    • CA: profile 12.1% · reference 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 10, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Use matchup records as scouting leads

    vs Char 253: 142 wins in 279 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: 142 wins in 279 games
    • vs Akuma: 11 wins in 37 games
    • vs Jamie: 9 wins in 22 games
  2. Test the Drive Impact tendency

    Drive Impact: profile 0.3 · reference 0.34

    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 0.3 · reference 0.34
    • Drive Impact gauge: profile 1.9% · reference 2.1%
  3. Build pressure without overextending

    Corner pressure: profile 4.7 · reference 10.77

    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 4.7 · reference 10.77
    • Time cornered: profile 14.4 · reference 12.04

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 10, 2026 · AI: dots-studio/dots-3-note-preview:free

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