Lily
Updated 2 days agoSteamSteamJapanJapanClub · SIRICLUBM100%

倉持由香

Summit Guide
Rank 36MR 1,601#92,957
Last 108–2+43Last 2013–7+43
Winrate
52%
46W · 42L · 88 stored
Ranked matches
88
selected mode
Wins
46
Ranked
Losses
42
Ranked
Peak MR
1,601
Lily

Ranked MR · Lily

53 local · 1099 imported · 1152 on chart · 90 battles stored

Latest game

VictoryRanked

Replay not requested
Lily
倉持由香 · Lily
JP
Opponent · JPYujin

Playstyle reference

Habits vs top 30 Lily

Benchmark refreshed Sep 12, 2026, 1:25 AM

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

Lily
倉持由香’s Lily benchmark

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

シュラリス 2230 · SBI_Hibiki 2207 · Mira 2176 · 干し柿_ 2119 · ついっぎー 2114 · +25 others

Largest absolute differences first23 habits
Habit倉持由香LegendsDifference LessLegendsMore
SA116.7%43.8%-27.2%
SA347.4%25.7%+21.7%
Drive Rush (cancel)19.4%31.1%-11.6%
SA226.9%22.0%+4.9%
Drive Arts25.3%21.7%+3.6%
Drive Rush (parry)4.2%5.7%-1.5%
Got thrown3.402.32+1.08
Time cornered9.6010.41-0.81
Drive Parry2.701.96+0.74
Drive Guard12.5%12.0%+0.5%
CA9.0%8.4%+0.5%
Throws2.102.61-0.51
Throw techs0.800.48+0.32
Perfect Parry0.300.60-0.30
Drive Reversal0.600.33+0.27
Corner pressure9.609.83-0.23
Drive Impact gauge1.9%2.1%-0.2%
Stuns landed0.000.08-0.08
Throw parries0.200.26-0.06
Drive Impact0.200.25-0.05
Punish Counters landed0.200.16+0.04
Got stunned0.000.04-0.04
Got Punish Countered0.100.12-0.02
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.

Lily · Latest 100

What to improve

  1. Review close-range choices

    Got thrown: profile 3.4 · reference 2.32

    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
    • Got thrown: profile 3.4 · reference 2.32
    • Throws: profile 2.1 · reference 2.61
    • Throw techs: profile 0.8 · reference 0.48
  2. Find the cause of punish events

    Got Punish Countered: 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
    • Got Punish Countered: profile 0.1 · reference 0.12
    • Punish Counters landed: profile 0.2 · reference 0.16
  3. Give each meter spend a purpose

    SA3: profile 47.4% · reference 25.7%

    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 47.4% · reference 25.7%
    • SA1: profile 16.7% · reference 43.8%
    • Drive Arts: profile 25.3% · reference 21.7%

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 12, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Probe defense before committing

    Drive Reversal: profile 0.6 · reference 0.33

    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 0.6 · reference 0.33
    • Throw techs: profile 0.8 · reference 0.48
    • Drive Parry: profile 2.7 · reference 1.96
  2. Test the Drive Impact tendency

    Drive Impact: profile 0.2 · reference 0.25

    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 0.25
    • Drive Impact gauge: profile 1.9% · reference 2.1%
  3. Use matchup records as scouting leads

    vs Char 253: 163 wins in 314 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: 163 wins in 314 games
    • vs Luke: 18 wins in 42 games
    • vs Yasmine: 20 wins in 39 games

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 12, 2026 · AI: dots-studio/dots-3-note-preview:free

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