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VictoryRanked
JA
EDJAUpdated 1 day ago
Steam
JapanClub · DialogC100%
SteamJapanClub · DialogC100%うちの柴犬はお腹がゆるいです
True Master
MR 1,598#100,761Last 106–4+13Last 2010–10+1
Winrate
49%
38W · 40L · 78 stored
Ranked matches
78
selected mode
Wins
38
Ranked
Losses
40
Ranked
Peak MR
1,635
Jamie
Ranked MR · Jamie
78 local · 0 imported · 78 on chart · 78 battles stored
Replay not requested
JAEDPlaystyle reference
Habits vs top 30 Jamie
Benchmark refreshed Sep 13, 2026, 4:16 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
JALargest absolute differences first23 habits
| Habit | うちの柴犬はお腹がゆるいです | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA1 | 55.9% | 29.0% | +26.9% | |
| SA2 | 4.3% | 21.4% | -17.1% | |
| SA3 | 26.9% | 39.7% | -12.8% | |
| Drive Rush (cancel) | 44.1% | 33.8% | +10.3% | |
| Drive Arts | 16.9% | 23.2% | -6.3% | |
| Corner pressure | 11.00 | 14.89 | -3.89 | |
| CA | 12.9% | 9.8% | +3.1% | |
| Drive Guard | 8.0% | 11.0% | -2.9% | |
| Drive Parry | 0.60 | 1.78 | -1.18 | |
| Drive Impact gauge | 1.9% | 1.4% | +0.5% | |
| Perfect Parry | 0.20 | 0.67 | -0.47 | |
| Drive Rush (parry) | 6.1% | 5.7% | +0.4% | |
| Time cornered | 8.30 | 8.56 | -0.26 | |
| Got thrown | 2.30 | 2.15 | +0.15 | |
| Got Punish Countered | 0.20 | 0.06 | +0.14 | |
| Stuns landed | 0.20 | 0.08 | +0.12 | |
| Throw techs | 0.50 | 0.40 | +0.10 | |
| Throws | 2.30 | 2.40 | -0.10 | |
| Drive Reversal | 0.20 | 0.26 | -0.06 | |
| Got stunned | 0.10 | 0.06 | +0.04 | |
| Punish Counters landed | 0.10 | 0.07 | +0.03 | |
| Drive Impact | 0.20 | 0.21 | -0.01 | |
| Throw parries | 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.
Jamie · Latest 100
What to improve
Find the cause of punish events
Punish Counters landed: profile 0.1 · 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 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 0.1 · reference 0.07
- Got Punish Countered: profile 0.1 · reference 0.08
Review defensive decisions
Drive Parry: profile 0.9 · 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 thisRecord 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 0.9 · reference 1.7
- Perfect Parry: profile 0.2 · reference 0.6
- Drive Reversal: profile 0.2 · reference 0.24
Give each meter spend a purpose
SA1: profile 47.8% · reference 30%
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
- SA1: profile 47.8% · reference 30%
- SA2: profile 3.3% · reference 21.4%
- SA3: profile 41.1% · reference 38.6%
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 Ryu: 69 wins in 160 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 Ryu: 69 wins in 160 games
- vs Luke: 69 wins in 156 games
- vs Yasmine: 60 wins in 119 games
Separate a tendency from a one-off event
Recent stored ranked sample: 20 wins in 34 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: 20 wins in 34 games
Test the Drive Impact tendency
Drive Impact: profile 0.2 · 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 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 0.2
- Drive Impact gauge: profile 1.8% · reference 1.5%
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