Latest game
VictoryRanked
SA
AKSAUpdated 4 days ago
Steam
JapanC100%
SteamJapanC100%kotetsu
Let's Do This
MR 1,542#146,445Last 107–3+33Last 2011–9+21
Winrate
53%
24W · 21L · 45 stored
Ranked matches
45
selected mode
Wins
24
Ranked
Losses
21
Ranked
Peak MR
1,542
Sagat
Ranked MR · Sagat
45 local · 0 imported · 45 on chart · 45 battles stored
Replay not requested
SAAKPlaystyle reference
Habits vs top 30 Sagat
Benchmark refreshed Sep 13, 2026, 10:18 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
SALargest absolute differences first23 habits
| Habit | kotetsu | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| CA | 27.8% | 9.1% | +18.7% | |
| SA2 | 13.9% | 26.4% | -12.5% | |
| SA1 | 16.7% | 24.6% | -7.9% | |
| Drive Guard | 9.8% | 14.2% | -4.3% | |
| Drive Arts | 13.9% | 16.0% | -2.2% | |
| SA3 | 41.7% | 39.9% | +1.7% | |
| Drive Parry | 0.50 | 1.81 | -1.31 | |
| Drive Rush (cancel) | 32.8% | 34.0% | -1.2% | |
| Corner pressure | 11.30 | 12.43 | -1.13 | |
| Perfect Parry | 0.00 | 0.74 | -0.74 | |
| Drive Rush (parry) | 7.8% | 8.4% | -0.6% | |
| Drive Impact gauge | 1.7% | 1.3% | +0.4% | |
| Throw techs | 0.10 | 0.46 | -0.36 | |
| Throws | 1.90 | 2.23 | -0.33 | |
| Drive Reversal | 0.00 | 0.24 | -0.24 | |
| Throw parries | 0.40 | 0.25 | +0.15 | |
| Got thrown | 2.10 | 2.21 | -0.11 | |
| Got Punish Countered | 0.20 | 0.09 | +0.11 | |
| Got stunned | 0.00 | 0.05 | -0.05 | |
| Drive Impact | 0.20 | 0.18 | +0.02 | |
| Stuns landed | 0.10 | 0.08 | +0.02 | |
| Time cornered | 8.90 | 8.88 | +0.02 | |
| Punish Counters landed | 0.10 | 0.11 | -0.01 |
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.
Sagat · Latest 100
What to improve
Find the cause of punish events
Got Punish Countered: profile 0.2 · reference 0.09
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
- Got Punish Countered: profile 0.2 · reference 0.09
- Punish Counters landed: profile 0.1 · reference 0.1
Review close-range choices
Throw techs: profile 0.1 · reference 0.43
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
- Throw techs: profile 0.1 · reference 0.43
- Got thrown: profile 2.1 · reference 2.15
Give each meter spend a purpose
CA: profile 27.8% · reference 9.3%
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 27.8% · reference 9.3%
- SA3: profile 41.7% · reference 41.5%
- SA1: profile 16.7% · reference 24.1%
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
Probe defense before committing
Drive Parry: profile 0.5 · reference 1.58
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 0.5 · reference 1.58
- Perfect Parry: profile 0 · reference 0.68
Test the Drive Impact tendency
Drive Impact: profile 0.2 · reference 0.18
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 thisRevisit 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 0.2 · reference 0.18
- Drive Impact gauge: profile 1.7% · reference 1.3%
Use matchup records as scouting leads
vs Luke: 42 wins in 78 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 Luke: 42 wins in 78 games
- vs Alex: 26 wins in 60 games
- vs Akuma: 50 wins in 70 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