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DefeatCasual
JU
A.JUUpdated 4 days ago
Steam
JapanM100%
SteamJapanM100%renge
You've Got This, Juri!
MR 1,600#92,611Last 107–3+31Last 2011–9+18
Winrate
57%
21W · 16L · 37 stored
Ranked matches
37
selected mode
Wins
21
Ranked
Losses
16
Ranked
Peak MR
1,600
Juri
Ranked MR · Juri
37 local · 0 imported · 37 on chart · 122 battles stored
Replay not requested
JUA.Playstyle reference
Habits vs top 30 Juri
Benchmark refreshed Sep 12, 2026, 1:26 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
JULargest absolute differences first23 habits
| Habit | renge | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA2 | 0.0% | 19.5% | -19.5% | |
| SA3 | 50.6% | 34.8% | +15.8% | |
| Corner pressure | 8.20 | 12.24 | -4.04 | |
| Drive Rush (parry) | 9.8% | 7.1% | +2.6% | |
| Drive Guard | 15.9% | 13.4% | +2.5% | |
| Drive Arts | 17.0% | 19.4% | -2.4% | |
| SA1 | 38.8% | 36.7% | +2.1% | |
| CA | 10.6% | 8.9% | +1.7% | |
| Drive Rush (cancel) | 33.5% | 31.9% | +1.7% | |
| Throws | 3.40 | 2.65 | +0.75 | |
| Drive Impact gauge | 1.6% | 2.0% | -0.4% | |
| Perfect Parry | 0.30 | 0.64 | -0.34 | |
| Got thrown | 1.80 | 2.13 | -0.33 | |
| Time cornered | 8.90 | 9.20 | -0.30 | |
| Drive Parry | 2.20 | 2.07 | +0.13 | |
| Drive Reversal | 0.10 | 0.20 | -0.10 | |
| Stuns landed | 0.00 | 0.09 | -0.09 | |
| Punish Counters landed | 0.20 | 0.13 | +0.07 | |
| Drive Impact | 0.20 | 0.27 | -0.07 | |
| Got stunned | 0.10 | 0.04 | +0.06 | |
| Throw parries | 0.20 | 0.26 | -0.06 | |
| Throw techs | 0.40 | 0.46 | -0.06 | |
| Got Punish Countered | 0.10 | 0.09 | +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.
Juri · Latest 100
What to improve
Find the cause of punish events
Punish Counters landed: profile 0.2 · reference 0.11
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 0.11
- Got Punish Countered: profile 0.1 · reference 0.08
Trace how you lose or gain space
Corner pressure: profile 8.2 · reference 13.05
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 thisRecreate 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 8.2 · reference 13.05
- Time cornered: profile 8.9 · reference 8.63
Give each meter spend a purpose
SA3: profile 50.6% · reference 33.5%
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
- SA3: profile 50.6% · reference 33.5%
- SA2: profile 0% · reference 20.4%
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 9, 2026 · AI: dots-studio/dots-3-note-preview:free
How to beat this player
Use matchup records as scouting leads
vs Elena: 10 wins in 23 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 Elena: 10 wins in 23 games
- vs Akuma: 41 wins in 75 games
- vs Ken: 28 wins in 55 games
Separate a tendency from a one-off event
Recent stored ranked sample: 21 wins in 37 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: 21 wins in 37 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 9, 2026 · AI: dots-studio/dots-3-note-preview:free