milo

What to improve

1. 01

   Find the cause of punish events

   Punish Counters landed: profile 0.2 · reference 0.07

   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 0.2 · reference 0.07
   • Got Punish Countered: profile 0.2 · reference 0.08
2. 02

   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 1.8% · reference 1.5%
3. 03

   Review defensive decisions

   Drive Parry: profile 4.1 · reference 1.7

   Compare five defensive situations: what did the opponent do, what did you choose, and what happened? Low parry or throw-tech counts alone do not establish a weakness.

   Try this

   Record two different options from one troublesome situation. Practice identifying them and choosing a response, then review whether the same decision improves in your next set.

   Supporting stats

   • Drive Parry: profile 4.1 · reference 1.7
   • Perfect Parry: profile 1.5 · reference 0.6
   • Drive Reversal: profile 0 · reference 0.24

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 8, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

1. 01

   Use matchup records as scouting leads

   vs Marisa: 24 wins in 38 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 Marisa: 24 wins in 38 games
   • vs Char 253: 619 wins in 1,227 games
2. 02

   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 1.8% · reference 1.5%
3. 03

   Probe defense before committing

   Drive Parry: profile 4.1 · reference 1.7

   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 4.1 · reference 1.7
   • Perfect Parry: profile 1.5 · reference 0.6
   • Drive Reversal: profile 0 · reference 0.24

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 8, 2026 · AI: dots-studio/dots-3-note-preview:free