Latest game
DefeatRanked
CH
LUCHUpdated 3 days ago
Steam
JapanC100%
SteamJapanC100%Ricorabbit
Angel Devil Kingdom
MR 1,427#486,626Last 105–5-1Last 209–11-13
Winrate
48%
60W · 65L · 125 stored
Ranked matches
125
selected mode
Wins
60
Ranked
Losses
65
Ranked
Peak MR
1,491
Chun-Li
Ranked MR · Chun-Li
125 local · 0 imported · 125 on chart · 193 battles stored
Replay not requested
CHLUPlaystyle reference
Habits vs top 30 Chun-Li
Benchmark refreshed Sep 3, 2026, 7:25 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
CHLargest absolute differences first23 habits
| Habit | Ricorabbit | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA1 | 46.3% | 34.5% | +11.8% | |
| SA2 | 22.2% | 31.7% | -9.5% | |
| Drive Rush (cancel) | 49.1% | 40.1% | +9.0% | |
| SA3 | 18.5% | 26.2% | -7.7% | |
| Drive Arts | 9.9% | 16.9% | -6.9% | |
| CA | 13.0% | 7.6% | +5.4% | |
| Corner pressure | 9.80 | 11.27 | -1.47 | |
| Time cornered | 8.40 | 9.57 | -1.17 | |
| Drive Guard | 9.7% | 10.2% | -0.5% | |
| Drive Impact gauge | 1.9% | 1.4% | +0.5% | |
| Got thrown | 2.50 | 2.08 | +0.42 | |
| Drive Rush (parry) | 4.7% | 5.0% | -0.3% | |
| Throw techs | 0.70 | 0.40 | +0.30 | |
| Perfect Parry | 0.30 | 0.57 | -0.27 | |
| Throws | 2.60 | 2.39 | +0.21 | |
| Drive Reversal | 0.00 | 0.17 | -0.17 | |
| Drive Parry | 1.50 | 1.64 | -0.14 | |
| Got Punish Countered | 0.20 | 0.09 | +0.11 | |
| Got stunned | 0.10 | 0.05 | +0.05 | |
| Stuns landed | 0.00 | 0.04 | -0.04 | |
| Drive Impact | 0.20 | 0.16 | +0.04 | |
| Throw parries | 0.20 | 0.22 | -0.02 | |
| Punish Counters landed | 0.10 | 0.10 | -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.
Chun-Li · Latest 100
What to improve
Find the cause of punish events
Punish Counters landed: profile 0.2 · reference 0.1
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 0.1
- Got Punish Countered: profile 0.2 · reference 0.09
Make Drive Impact a deliberate choice
Drive Impact: profile 0.2 · reference 0.16
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 0.2 · reference 0.16
- Drive Impact gauge: profile 1.7% · reference 1.4%
Review defensive decisions
Drive Reversal: profile 0 · reference 0.17
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 Reversal: profile 0 · reference 0.17
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 Char 253: 91 wins in 194 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 Char 253: 91 wins in 194 games
- vs Elena: 21 wins in 45 games
- vs Akuma: 10 wins in 22 games
Separate a tendency from a one-off event
Recent stored ranked sample: 37 wins in 81 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: 37 wins in 81 games
Test the Drive Impact tendency
Drive Impact: profile 0.2 · reference 0.16
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 0.16
- Drive Impact gauge: profile 1.7% · reference 1.4%
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 6, 2026 · AI: dots-studio/dots-3-note-preview:free