Latest game
VictoryRanked
IN
A.INUpdated 5 days ago
Steam
JapanClub · IPhone16ProC96%
SteamJapanClub · IPhone16ProC96%KKKK
GG
MR 1,502#239,434Last 105–50Last 2013–7+45
Winrate
52%
145W · 136L · 281 stored
Ranked matches
281
selected mode
Wins
145
Ranked
Losses
136
Ranked
Peak MR
1,603
Ingrid
Ranked MR · Ingrid
281 local · 0 imported · 281 on chart · 318 battles stored
Replay not requested
INA.Playstyle reference
Habits vs top 30 Ingrid
Benchmark refreshed Sep 2, 2026, 4:15 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
INLargest absolute differences first23 habits
| Habit | KKKK | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA2 | 15.0% | 57.0% | -42.0% | |
| SA3 | 45.0% | 15.0% | +30.0% | |
| CA | 25.0% | 4.6% | +20.4% | |
| SA1 | 15.0% | 23.4% | -8.4% | |
| Drive Rush (cancel) | 18.2% | 25.3% | -7.1% | |
| Drive Guard | 18.3% | 12.2% | +6.1% | |
| Drive Rush (parry) | 10.2% | 7.4% | +2.9% | |
| Corner pressure | 9.10 | 11.85 | -2.75 | |
| Drive Arts | 25.9% | 27.5% | -1.7% | |
| Drive Parry | 2.30 | 1.51 | +0.79 | |
| Throws | 1.80 | 2.31 | -0.51 | |
| Time cornered | 9.90 | 10.23 | -0.33 | |
| Got Punish Countered | 0.30 | 0.08 | +0.22 | |
| Throw parries | 0.10 | 0.28 | -0.18 | |
| Got thrown | 2.00 | 2.13 | -0.13 | |
| Drive Reversal | 0.40 | 0.30 | +0.10 | |
| Perfect Parry | 0.40 | 0.50 | -0.10 | |
| Punish Counters landed | 0.20 | 0.13 | +0.07 | |
| Drive Impact | 0.20 | 0.27 | -0.07 | |
| Got stunned | 0.00 | 0.06 | -0.06 | |
| Stuns landed | 0.10 | 0.14 | -0.04 | |
| Drive Impact gauge | 2.1% | 2.1% | -0.0% | |
| Throw techs | 0.40 | 0.41 | -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.
Ingrid · Latest 100
What to improve
Find the cause of punish events
Got Punish Countered: profile 0.3 · reference 0.08
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 0.08
- Punish Counters landed: profile 0.2 · reference 0.13
Review defensive decisions
Drive Parry: profile 2.3 · reference 1.51
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 2.3 · reference 1.51
- Perfect Parry: profile 0.4 · reference 0.5
- Drive Reversal: profile 0.4 · reference 0.3
Give each meter spend a purpose
CA: profile 25% · reference 4.6%
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 25% · reference 4.6%
- SA2: profile 15% · reference 57%
- SA3: profile 45% · reference 15%
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: nex-agi/nex-n2.5-mini:free
How to beat this player
Separate a tendency from a one-off event
Recent stored ranked sample: 56 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: 56 wins in 100 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: nex-agi/nex-n2.5-mini:free