Latest game
VictoryRanked
AKAKAKUpdated 1 week ago
Steam
JapanC100%
SteamJapanC100%Epbonus
GG
MR 1,234#572,922Last 106–4+8Last 2010–10-10
Winrate
45%
50W · 60L · 110 stored
Ranked matches
110
selected mode
Wins
50
Ranked
Losses
60
Ranked
Peak MR
1,293
Akuma
Ranked MR · Akuma
110 local · 0 imported · 110 on chart · 110 battles stored
Replay not requested
AKAKPlaystyle reference
Habits vs top 30 Akuma
Benchmark refreshed Sep 13, 2026, 7:27 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
AKLargest absolute differences first23 habits
| Habit | Epbonus | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| CA | 31.4% | 9.9% | +21.5% | |
| Drive Rush (cancel) | 47.8% | 32.7% | +15.1% | |
| SA2 | 14.3% | 22.8% | -8.5% | |
| Drive Guard | 5.7% | 13.1% | -7.4% | |
| SA3 | 31.4% | 38.7% | -7.2% | |
| SA1 | 22.9% | 28.6% | -5.8% | |
| Drive Rush (parry) | 1.8% | 7.4% | -5.6% | |
| Drive Arts | 15.4% | 19.2% | -3.9% | |
| Throws | 1.40 | 2.74 | -1.34 | |
| Corner pressure | 10.20 | 11.47 | -1.27 | |
| Perfect Parry | 0.10 | 0.77 | -0.67 | |
| Drive Parry | 1.00 | 1.65 | -0.65 | |
| Time cornered | 7.90 | 8.55 | -0.65 | |
| Got thrown | 2.60 | 2.09 | +0.51 | |
| Drive Impact gauge | 1.1% | 1.5% | -0.4% | |
| Drive Reversal | 0.00 | 0.20 | -0.20 | |
| Throw parries | 0.10 | 0.27 | -0.17 | |
| Got Punish Countered | 0.20 | 0.09 | +0.11 | |
| Punish Counters landed | 0.20 | 0.13 | +0.07 | |
| Throw techs | 0.40 | 0.45 | -0.05 | |
| Got stunned | 0.00 | 0.04 | -0.04 | |
| Stuns landed | 0.00 | 0.03 | -0.03 | |
| Drive Impact | 0.20 | 0.20 | -0.00 |
FROM STATS TO PRACTICE
Latest 100Match plan
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.
Akuma · Latest 100
What to improve
Give each meter spend a purpose
CA: profile 31.4% · reference 10.5%
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 thisPractice 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
- CA: profile 31.4% · reference 10.5%
- SA3: profile 31.4% · reference 35.7%
- SA1: profile 22.9% · reference 29.6%
Review close-range choices
Throws: profile 1.4 · reference 2.66
Look at five close-range exchanges. Separate throw opportunities, throw attempts and defensive choices; the aggregate counts cannot show which option was correct.
Try thisReplay 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
- Throws: profile 1.4 · reference 2.66
- Got thrown: profile 2.6 · reference 2.04
- Throw techs: profile 0.4 · reference 0.38
Find the cause of punish events
Punish Counters landed: profile 0.2 · reference 0.13
Review five Punish Counters received and five landed. Separate whiffed attacks from unsafe actions on block before choosing what to practice.
Try thisRecreate 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 0.13
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
Use matchup records as scouting leads
vs Juri: 35 wins in 74 games
A lower win rate suggests footage to examine, not a guaranteed counterpick. Check whether the same difficult situation appears in multiple matches.
Try thisIf 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 Juri: 35 wins in 74 games
- vs Jamie: 31 wins in 70 games
- vs Alex: 23 wins in 61 games
Separate a tendency from a one-off event
Recent stored ranked sample: 45 wins in 100 games
Scout several recent matches and compare wins with losses. Prepare around a repeated situation rather than one memorable mistake.
Try thisUse the first round to check one scouting hypothesis. If it repeats, apply your prepared adjustment; if it does not, discard it and observe a new pattern.
Supporting stats
- Recent stored ranked sample: 45 wins in 100 games
Probe defense before committing
Drive Parry: profile 1 · reference 1.8
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 thisTry 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 1 · reference 1.8
- Perfect Parry: profile 0.1 · reference 0.85
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