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LUUpdated 12 hours ago
Steam
JapanClub · GOZILINEC100%
SteamJapanClub · GOZILINEC100%ザッキー影山
Only Need Three Minutes
MR 1,810#8,850Last 106–4+15Last 2012–8+30
Winrate
58%
52W · 37L · 89 stored
Ranked matches
89
selected mode
Wins
52
Ranked
Losses
37
Ranked
Peak MR
1,810
Luke
Ranked MR · Luke
69 local · 0 imported · 69 on chart · 222 battles stored
Replay not requested
ZAMAPlaystyle reference
Habits vs top 30 Luke
Benchmark refreshed Sep 6, 2026, 10:21 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
LULargest absolute differences first23 habits
| Habit | ザッキー影山 | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA1 | 13.5% | 30.6% | -17.2% | |
| SA2 | 40.4% | 26.0% | +14.4% | |
| SA3 | 44.2% | 34.2% | +10.1% | |
| Drive Rush (cancel) | 46.6% | 37.3% | +9.3% | |
| Drive Arts | 9.2% | 16.7% | -7.5% | |
| CA | 1.9% | 9.2% | -7.2% | |
| Drive Guard | 9.1% | 13.2% | -4.1% | |
| Time cornered | 5.80 | 8.74 | -2.94 | |
| Corner pressure | 10.70 | 13.55 | -2.85 | |
| Drive Rush (parry) | 5.8% | 7.6% | -1.8% | |
| Drive Parry | 0.80 | 1.80 | -1.00 | |
| Throws | 1.90 | 2.43 | -0.53 | |
| Perfect Parry | 0.20 | 0.69 | -0.49 | |
| Drive Impact gauge | 1.7% | 1.4% | +0.3% | |
| Punish Counters landed | 0.30 | 0.08 | +0.22 | |
| Drive Reversal | 0.00 | 0.20 | -0.20 | |
| Throw parries | 0.10 | 0.22 | -0.12 | |
| Drive Impact | 0.30 | 0.19 | +0.11 | |
| Got thrown | 2.10 | 2.01 | +0.09 | |
| Stuns landed | 0.00 | 0.07 | -0.07 | |
| Got stunned | 0.00 | 0.06 | -0.06 | |
| Got Punish Countered | 0.10 | 0.06 | +0.04 | |
| Throw techs | 0.40 | 0.37 | +0.03 |
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.
Luke · Latest 100
What to improve
Find the cause of punish events
Got Punish Countered: profile 0.2 · reference 0.06
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 0.2 · reference 0.06
- Punish Counters landed: profile 0.2 · reference 0.08
Review close-range choices
Throw techs: profile 1 · reference 0.4
Look at five close-range exchanges. Separate throw opportunities, throw attempts and defensive choices; the aggregate counts cannot show which option was correct.
Try thisReplay one recurring situation in training with both a strike and a throw recorded. Practice your chosen responses, then check how often you make that choice deliberately in matches.
Supporting stats
- Throw techs: profile 1 · reference 0.4
- Throws: profile 1.9 · reference 2.57
- Got thrown: profile 3.1 · reference 2.04
Give each meter spend a purpose
CA: profile 21.2% · reference 10.5%
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
- CA: profile 21.2% · reference 10.5%
- SA1: profile 15.4% · reference 30.7%
- SA3: profile 42.3% · reference 36.2%
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
Test the Drive Impact tendency
Drive Impact: profile 0.2 · reference 0.17
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 0.17
- Drive Impact gauge: profile 1.6% · reference 1.3%
Use matchup records as scouting leads
vs Char 253: 356 wins in 598 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: 356 wins in 598 games
- vs A.K.I.: 47 wins in 65 games
- vs Ryu: 40 wins in 59 games
Separate a tendency from a one-off event
Recent stored ranked sample: 13 wins in 20 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: 13 wins in 20 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 6, 2026 · AI: dots-studio/dots-3-note-preview:free