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DefeatRanked
DE
JPDEUpdated 6 days ago
Steam
NepalClub · ShotaconFTclubM100%
SteamNepalClub · ShotaconFTclubM100%テクノブレイク飯田
Let's Do This
MR 1,863#4,353Last 103–7-32Last 2010–10-6
Winrate
51%
23W · 22L · 45 stored
Ranked matches
45
selected mode
Wins
23
Ranked
Losses
22
Ranked
Peak MR
1,863
Dee Jay
Ranked MR · Dee Jay
45 local · 0 imported · 45 on chart · 45 battles stored
Replay not requested
DEJPPlaystyle reference
Habits vs top 30 Dee Jay
Benchmark refreshed Sep 11, 2026, 10:15 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
DELargest absolute differences first23 habits
| Habit | テクノブレイク飯田 | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA1 | 13.3% | 36.2% | -22.9% | |
| SA3 | 49.4% | 33.8% | +15.6% | |
| Drive Arts | 36.8% | 24.7% | +12.1% | |
| Drive Rush (cancel) | 13.2% | 23.0% | -9.7% | |
| SA2 | 28.9% | 21.3% | +7.6% | |
| Drive Guard | 13.4% | 15.1% | -1.7% | |
| Time cornered | 10.00 | 9.11 | +0.89 | |
| Drive Rush (parry) | 8.4% | 8.9% | -0.6% | |
| Throw techs | 0.80 | 0.43 | +0.37 | |
| Corner pressure | 12.60 | 12.23 | +0.37 | |
| Drive Impact gauge | 2.1% | 1.8% | +0.3% | |
| CA | 8.4% | 8.7% | -0.3% | |
| Got Punish Countered | 0.30 | 0.09 | +0.21 | |
| Throws | 2.20 | 2.38 | -0.18 | |
| Perfect Parry | 0.40 | 0.57 | -0.17 | |
| Got thrown | 2.30 | 2.20 | +0.10 | |
| Punish Counters landed | 0.20 | 0.13 | +0.07 | |
| Drive Impact | 0.30 | 0.24 | +0.06 | |
| Drive Parry | 1.70 | 1.76 | -0.06 | |
| Throw parries | 0.20 | 0.25 | -0.05 | |
| Stuns landed | 0.10 | 0.07 | +0.03 | |
| Got stunned | 0.10 | 0.07 | +0.03 | |
| Drive Reversal | 0.20 | 0.19 | +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.
Dee Jay · Latest 100
What to improve
Find the cause of punish events
Got Punish Countered: profile 0.3 · 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 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 0.3 · reference 0.12
- Punish Counters landed: profile 0.2 · reference 0.12
Make Drive Impact a deliberate choice
Drive Impact: profile 0.3 · reference 0.22
Review five Drive Impacts and record the situation and outcome. Keep effective uses; investigate repeated failures rather than aiming for the reference frequency.
Try thisRecord 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 0.22
- Drive Impact gauge: profile 2.1% · reference 1.8%
Give each meter spend a purpose
SA3: profile 49.4% · reference 33.7%
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
- SA3: profile 49.4% · reference 33.7%
- SA1: profile 13.3% · reference 35.1%
- SA2: profile 28.9% · reference 22%
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
Look for a repeatable punish opportunity
Got Punish Countered: profile 0.3 · reference 0.12
Use the stats as a scouting lead. Watch for an action you have already verified as punishable at that spacing; do not assume every apparent opening is unsafe.
Try thisTest one confirmed response when that action appears. If it stops appearing, return to your normal spacing instead of forcing the punish.
Supporting stats
- Got Punish Countered: profile 0.3 · reference 0.12
Test the Drive Impact tendency
Drive Impact: profile 0.3 · reference 0.22
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 0.3 · reference 0.22
- Drive Impact gauge: profile 2.1% · reference 1.8%
Test the close-range pattern
Throw techs: profile 0.8 · reference 0.44
Observe actual strike, throw and defensive choices at close range. Change one part of your familiar mix only after a tendency appears.
Try thisIf the same response repeats twice, try a different option in that situation. If the player changes their response, return to varied choices instead of assuming the pattern is permanent.
Supporting stats
- Throw techs: profile 0.8 · reference 0.44
- Throws: profile 2.2 · reference 2.49
- Got thrown: profile 2.3 · reference 2.12
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