SF6Statsv0.20.15
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Saved match plans

Previously generated AI plans, with their original supporting stats and data dates. Expand a plan to read both perspectives.

Marisa · Latest 100

What to improve

  1. Find the cause of punish events

    Got Punish Countered: profile 0.3 · 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 0.3 · reference 0.11
    • Punish Counters landed: profile 0.2 · reference 0.12

  2. Make Drive Impact a deliberate choice

    Drive Impact: profile 0.3 · 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 0.3 · reference 0.2
    • Drive Impact gauge: profile 3.1% · reference 1.9%

  3. Trace how you lose or gain space

    Corner pressure: profile 6.7 · reference 10.2

    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 6.7 · reference 10.2
    • Time cornered: profile 8.7 · reference 8.39

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 Ryu: 50 wins in 107 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 Ryu: 50 wins in 107 games
    • vs Yasmine: 52 wins in 96 games
    • vs Luke: 44 wins in 86 games

  2. Look for a repeatable punish opportunity

    Got Punish Countered: profile 0.3 · reference 0.11

    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
    • Got Punish Countered: profile 0.3 · reference 0.11

  3. Probe defense before committing

    Drive Reversal: profile 0.6 · reference 0.32

    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 0.32
    • Drive Parry: profile 1.6 · reference 1.59
    • Perfect Parry: profile 0.2 · reference 0.6

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