Latest game
DefeatRanked
SA
RYSAUpdated 2 days ago
Steam
JapanC100%
SteamJapanC100%hagesu4444
All Will Be Mine
MR 1,289#598,244Last 104–6-11Last 2011–9+16
Winrate
47%
27W · 31L · 58 stored
Ranked matches
58
selected mode
Wins
27
Ranked
Losses
31
Ranked
Peak MR
1,318
Sagat
Ranked MR · Sagat
58 local · 0 imported · 58 on chart · 58 battles stored
Replay not requested
SARYPlaystyle 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 | hagesu4444 | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA3 | 56.9% | 39.9% | +16.9% | |
| SA1 | 9.8% | 24.6% | -14.8% | |
| SA2 | 11.8% | 26.4% | -14.6% | |
| CA | 21.6% | 9.1% | +12.5% | |
| Drive Rush (cancel) | 44.1% | 34.0% | +10.1% | |
| Drive Guard | 6.9% | 14.2% | -7.3% | |
| Drive Rush (parry) | 2.8% | 8.4% | -5.6% | |
| Drive Arts | 11.3% | 16.0% | -4.8% | |
| Corner pressure | 8.50 | 12.43 | -3.93 | |
| Drive Impact gauge | 2.6% | 1.3% | +1.3% | |
| Throws | 1.00 | 2.23 | -1.23 | |
| Drive Parry | 1.20 | 1.81 | -0.61 | |
| Perfect Parry | 0.20 | 0.74 | -0.54 | |
| Throw techs | 0.10 | 0.46 | -0.36 | |
| Got thrown | 2.50 | 2.21 | +0.29 | |
| Throw parries | 0.00 | 0.25 | -0.25 | |
| Got Punish Countered | 0.30 | 0.09 | +0.21 | |
| Punish Counters landed | 0.30 | 0.11 | +0.19 | |
| Drive Reversal | 0.40 | 0.24 | +0.16 | |
| Drive Impact | 0.30 | 0.18 | +0.12 | |
| Stuns landed | 0.00 | 0.08 | -0.08 | |
| Got stunned | 0.10 | 0.05 | +0.05 | |
| Time cornered | 8.90 | 8.88 | +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
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 0.09
Trace how you lose or gain space
Corner pressure: profile 8.6 · reference 12.38
Review five trips into the corner. Identify the earlier decision that gave up space, not just the final escape attempt. Check successful corner pressure too.
Try thisRecreate one recurring position in training. Compare your usual response with a less committal alternative, then track whether you reach the corner less often over the next set.
Supporting stats
- Corner pressure: profile 8.6 · reference 12.38
- Time cornered: profile 8.9 · reference 9.28
Compare decisions across wins and losses
Recent stored ranked sample: 25 wins in 50 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: 25 wins in 50 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 4, 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: 25 wins in 50 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: 25 wins in 50 games
Use matchup records as scouting leads
vs Akuma: 6 wins in 19 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 Akuma: 6 wins in 19 games
- vs Char 253: 66 wins in 159 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 4, 2026 · AI: nex-agi/nex-n2.5-mini:free