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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.

Alex · Latest 100

What to improve

  1. Find the cause of punish events

    Got Punish Countered: profile 0.4 · 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 0.4 · reference 0.12
    • Punish Counters landed: profile 0.2 · reference 0.12
  2. Review close-range choices

    Throw techs: profile 0 · reference 0.48

    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 · reference 0.48
    • Throws: profile 1.7 · reference 2.32
  3. Trace how you lose or gain space

    Corner pressure: profile 8.6 · reference 9.01

    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 8.6 · reference 9.01
    • Time cornered: profile 6.7 · reference 9.88

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 4, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Test the Drive Impact tendency

    Drive Impact: profile 0.3 · reference 0.2

    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 0.2
    • Drive Impact gauge: profile 4.4% · reference 1.7%
  2. Probe defense before committing

    Drive Reversal: profile 1.8 · reference 0.47

    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 1.8 · reference 0.47
    • Perfect Parry: profile 0.2 · reference 0.7
  3. Use matchup records as scouting leads

    vs Ryu: 52 wins in 103 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: 52 wins in 103 games
    • vs Luke: 49 wins in 98 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 4, 2026 · AI: dots-studio/dots-3-note-preview:free