Rashid
Updated 1 day agoSteamSteamJapanJapanC75%

でぃーこん

One Handed Swiper
Rank 36MR 1,424#494,983
Last 105–50Last 2010–100
Winrate
44%
44W · 56L · 100 stored
Ranked matches
100
selected mode
Wins
44
Ranked
Losses
56
Ranked
Peak MR
1,473
Rashid

Ranked MR · Rashid

51 local · 0 imported · 51 on chart · 118 battles stored

Latest game

VictoryRanked

Replay not requested
Rashid
でぃーこん · Rashid
Sagat
Opponent · Sagatshirasu

Playstyle reference

Habits vs top 30 Rashid

Benchmark refreshed Sep 12, 2026, 7:15 AM

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

Rashid
でぃーこん’s Rashid benchmark

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

Nth_satoru 2314 · TsuneHERO 2246 · とす__ 2217 · 山田の隣 2148 · Dual_Kevin 2128 · +25 others

Largest absolute differences first23 habits
HabitでぃーこんLegendsDifference LessLegendsMore
SA17.7%22.7%-15.0%
Corner pressure6.5015.02-8.52
SA263.1%56.0%+7.0%
SA323.1%16.6%+6.4%
Drive Rush (parry)4.3%7.4%-3.1%
Drive Arts18.0%20.1%-2.1%
Drive Guard11.4%13.0%-1.6%
CA6.2%4.7%+1.5%
Drive Rush (cancel)30.7%32.1%-1.4%
Time cornered10.909.52+1.38
Drive Impact gauge2.9%2.0%+0.9%
Throws2.302.64-0.34
Drive Reversal0.000.31-0.31
Got thrown2.302.05+0.25
Punish Counters landed0.300.13+0.17
Throw techs0.500.37+0.13
Perfect Parry0.500.61-0.11
Stuns landed0.000.10-0.10
Got Punish Countered0.200.11+0.09
Drive Parry1.701.77-0.07
Drive Impact0.300.25+0.05
Throw parries0.300.28+0.02
Got stunned0.100.08+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.

Rashid · Latest 100

What to improve

  1. Find the cause of punish events

    Punish Counters landed: profile 0.3 · 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 0.3 · reference 0.12
    • Got Punish Countered: profile 0.3 · reference 0.11
  2. Make Drive Impact a deliberate choice

    Drive Impact: profile 0.4 · reference 0.25

    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 0.4 · reference 0.25
    • Drive Impact gauge: profile 2.9% · reference 2%
  3. Give each meter spend a purpose

    Drive Guard: profile 12.2% · reference 12.9%

    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
    • Drive Guard: profile 12.2% · reference 12.9%

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 9, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Probe defense before committing

    Drive Parry: profile 2.4 · reference 1.73

    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 2.4 · reference 1.73
    • Perfect Parry: profile 0.6 · reference 0.63
  2. Test the close-range pattern

    Throws: profile 3.1 · reference 2.74

    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 3.1 · reference 2.74
    • Throw techs: profile 0.9 · reference 0.38
    • Got thrown: profile 3 · reference 2.12
  3. Build pressure without overextending

    Corner pressure: profile 6.2 · reference 14.79

    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 6.2 · reference 14.79
    • Time cornered: profile 9.2 · reference 9.54

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 9, 2026 · AI: dots-studio/dots-3-note-preview:free

JP · Latest 100

What to improve

  1. Find the cause of punish events

    Got Punish Countered: profile 0.3 · reference 0.08

    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 0.08
    • Punish Counters landed: profile 0.3 · reference 0.13
  2. Review close-range choices

    Throws: profile 3.1 · reference 1.97

    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 3.1 · reference 1.97
    • Throw techs: profile 0.9 · reference 0.39
    • Got thrown: profile 3 · reference 2.13
  3. Make Drive Impact a deliberate choice

    Drive Impact: profile 0.4 · reference 0.34

    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 0.4 · reference 0.34
    • Drive Impact gauge: profile 2.9% · reference 2.1%

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 9, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Test the close-range pattern

    Throws: profile 3.1 · reference 1.97

    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 3.1 · reference 1.97
    • Got thrown: profile 3 · reference 2.13
    • Throw techs: profile 0.9 · reference 0.39
  2. Look for a repeatable punish opportunity

    Punish Counters landed: profile 0.3 · reference 0.13

    Use the stats as a scouting lead. Watch for an action you have already verified as punishable at that spacing; do not assume every apparent opening is unsafe.

    Try this

    Test one confirmed response when that action appears. If it stops appearing, return to your normal spacing instead of forcing the punish.

    Supporting stats
    • Punish Counters landed: profile 0.3 · reference 0.13
    • Got Punish Countered: profile 0.3 · reference 0.08
  3. Test the Drive Impact tendency

    Drive Impact: profile 0.4 · 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 0.4 · reference 0.34
    • Drive Impact gauge: profile 2.9% · reference 2.1%

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 9, 2026 · AI: dots-studio/dots-3-note-preview:free

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