Rashid
Updated 1 week agoCrossPlatformCrossPlatformJapanJapanC100%

上  司

Master
Rank 36MR 1,800#10,607
Winrate
0W · 0L · 0 stored
Ranked matches
0
selected mode
Wins
0
Ranked
Losses
0
Ranked
Peak MR
1,800
Rashid

Ranked MR · Rashid

0 local · 0 imported · 0 on chart · 164 battles stored

Not enough ranked MR points in this range yet.

Latest game

DefeatCasual

Replay not requested
Rashid
上  司 · Rashid
Dee Jay
Opponent · Dee Jayズーマ@geome

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
上  司’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上  司LegendsDifference LessLegendsMore
SA263.2%56.0%+7.2%
Drive Guard19.1%13.0%+6.1%
SA311.1%16.6%-5.5%
Drive Rush (cancel)27.4%32.1%-4.8%
Corner pressure17.6015.02+2.58
Drive Rush (parry)9.9%7.4%+2.4%
Drive Impact gauge3.6%2.0%+1.7%
CA3.4%4.7%-1.3%
Drive Arts21.0%20.1%+0.9%
Drive Parry2.501.77+0.73
SA122.2%22.7%-0.5%
Perfect Parry0.300.61-0.31
Got thrown2.302.05+0.25
Throws2.402.64-0.24
Time cornered9.309.52-0.22
Throw parries0.400.28+0.12
Drive Reversal0.200.31-0.11
Stuns landed0.200.10+0.10
Got Punish Countered0.200.11+0.09
Throw techs0.300.37-0.07
Drive Impact0.300.25+0.05
Punish Counters landed0.100.13-0.03
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

    Got Punish Countered: profile 0.2 · 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 0.2 · reference 0.11
    • Punish Counters landed: profile 0.1 · reference 0.13
  2. Trace how you lose or gain space

    Corner pressure: profile 17.6 · reference 14.49

    Review five trips into the corner. Identify the earlier decision that gave up space, not just the final escape attempt. Check successful corner pressure too.

    Try this

    Recreate one recurring position in training. Compare your usual response with a less committal alternative, then track whether you reach the corner less often over the next set.

    Supporting stats
    • Corner pressure: profile 17.6 · reference 14.49
    • Time cornered: profile 9.3 · reference 8.96
  3. Give each meter spend a purpose

    SA3: profile 11.1% · reference 16.8%

    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 11.1% · reference 16.8%
    • SA2: profile 63.2% · reference 51%

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 6, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Use matchup records as scouting leads

    vs Char 253: 989 wins in 1,946 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: 989 wins in 1,946 games
    • vs Akuma: 79 wins in 169 games
    • vs Jamie: 74 wins in 140 games
  2. Test the Drive Impact tendency

    Drive Impact: profile 0.3 · reference 0.24

    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 0.24
    • Drive Impact gauge: profile 3.6% · reference 2.1%
  3. Probe defense before committing

    Drive Parry: profile 2.5 · reference 1.66

    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 2.5 · reference 1.66
    • Perfect Parry: profile 0.3 · reference 0.6
    • Drive Reversal: profile 0.2 · reference 0.35

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 6, 2026 · AI: dots-studio/dots-3-note-preview:free