Latest game
VictoryRanked
SA
ELSAUpdated 5 days ago
Steam
JapanClub · StreetCatsC100%
SteamJapanClub · StreetCatsC100%jalerter
Let's Do This
MR 1,660#40,759Last 107–3+19Last 2010–10+19
Winrate
48%
48W · 53L · 101 stored
Ranked matches
101
selected mode
Wins
48
Ranked
Losses
53
Ranked
Peak MR
1,668
Sagat
Ranked MR · Sagat
71 local · 0 imported · 71 on chart · 147 battles stored
Replay not requested
SAELPlaystyle reference
Habits vs top 30 Sagat
Benchmark refreshed Sep 13, 2026, 10:18 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
SALargest absolute differences first23 habits
| Habit | jalerter | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA3 | 17.8% | 39.9% | -22.1% | |
| SA1 | 42.5% | 24.6% | +17.9% | |
| Drive Arts | 23.3% | 16.0% | +7.3% | |
| Corner pressure | 5.30 | 12.43 | -7.13 | |
| Drive Rush (cancel) | 29.1% | 34.0% | -4.9% | |
| Drive Guard | 10.2% | 14.2% | -4.0% | |
| SA2 | 30.1% | 26.4% | +3.7% | |
| Drive Impact gauge | 4.8% | 1.3% | +3.5% | |
| Drive Rush (parry) | 5.6% | 8.4% | -2.8% | |
| Time cornered | 7.00 | 8.88 | -1.88 | |
| Drive Parry | 1.20 | 1.81 | -0.61 | |
| Drive Impact | 0.70 | 0.18 | +0.52 | |
| CA | 9.6% | 9.1% | +0.5% | |
| Punish Counters landed | 0.60 | 0.11 | +0.49 | |
| Got thrown | 2.60 | 2.21 | +0.39 | |
| Perfect Parry | 0.40 | 0.74 | -0.34 | |
| Throw techs | 0.20 | 0.46 | -0.26 | |
| Throws | 2.00 | 2.23 | -0.23 | |
| Got stunned | 0.20 | 0.05 | +0.15 | |
| Got Punish Countered | 0.20 | 0.09 | +0.11 | |
| Drive Reversal | 0.30 | 0.24 | +0.06 | |
| Throw parries | 0.20 | 0.25 | -0.05 | |
| Stuns landed | 0.10 | 0.08 | +0.02 |
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.
Sagat · Latest 100
What to improve
Compare decisions across wins and losses
Recent stored ranked sample: 35 wins in 71 games
Choose two wins and two losses from the recent stored sample. Find one decision that changes between them; the record alone cannot explain why results changed.
Try thisWrite down one specific decision to test in your next five games. Review whether you executed it and what happened, rather than judging the drill only by wins.
Supporting stats
- Recent stored ranked sample: 35 wins in 71 games
Find the cause of punish events
Punish Counters landed: profile 0.6 · 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 0.6 · reference 0.1
- Got Punish Countered: profile 0.2 · reference 0.09
Make Drive Impact a deliberate choice
Drive Impact: profile 0.7 · reference 0.18
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 0.7 · reference 0.18
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: 35 wins in 71 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: 35 wins in 71 games
Look for a repeatable punish opportunity
Got Punish Countered: profile 0.2 · reference 0.09
Use the stats as a scouting lead. Watch for an action you have already verified as punishable at that spacing; do not assume every apparent opening is unsafe.
Try thisTest one confirmed response when that action appears. If it stops appearing, return to your normal spacing instead of forcing the punish.
Supporting stats
- Got Punish Countered: profile 0.2 · reference 0.09
Test the Drive Impact tendency
Drive Impact: profile 0.7 · reference 0.18
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 0.7 · reference 0.18
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