やまたつ

What to improve

1. 01

   Find the cause of punish events

   Got Punish Countered: profile 0.2 · 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 0.2 · reference 0.08
   • Punish Counters landed: profile 0.2 · reference 0.11
2. 02

   Give each meter spend a purpose

   SA3: profile 54% · reference 34.6%

   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 54% · reference 34.6%
   • SA2: profile 3.2% · reference 15.8%
   • SA1: profile 22.2% · reference 39.6%
3. 03

   Trace how you lose or gain space

   Corner pressure: profile 5.9 · reference 12

   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 5.9 · reference 12
   • Time cornered: profile 7.4 · reference 9.08

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 7, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

1. 01

   Test the Drive Impact tendency

   Drive Impact: profile 0.4 · 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 0.4 · reference 0.24
   • Drive Impact gauge: profile 4.2% · reference 1.8%
2. 02

   Probe defense before committing

   Drive Reversal: profile 0.4 · reference 0.17

   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 0.4 · reference 0.17
   • Perfect Parry: profile 0.2 · reference 0.64
   • Drive Parry: profile 1.3 · reference 2.01
3. 03

   Use matchup records as scouting leads

   vs Char 253: 37 wins in 125 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: 37 wins in 125 games
   • vs Luke: 4 wins in 39 games
   • vs Ken: 5 wins in 15 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 7, 2026 · AI: dots-studio/dots-3-note-preview:free