Latest game
VictoryRanked
AL
AKALUpdated 1 day ago
Steam
JapanC100%
SteamJapanC100%デリボレ
Saturday! Night! Slam Masters!
MR 1,511#213,260Last 107–3+32Last 2010–10+2
Winrate
52%
127W · 115L · 242 stored
Ranked matches
242
selected mode
Wins
127
Ranked
Losses
115
Ranked
Peak MR
1,549
Alex
Ranked MR · Alex
242 local · 3197 imported · 3203 on chart · 306 battles stored
Replay not requested
ALAKPlaystyle reference
Habits vs top 30 Alex
Benchmark refreshed Sep 14, 2026, 4:24 AM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
ALLargest absolute differences first23 habits
| Habit | デリボレ | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA3 | 40.7% | 25.2% | +15.5% | |
| SA2 | 16.9% | 27.6% | -10.7% | |
| CA | 1.7% | 8.3% | -6.6% | |
| Drive Arts | 7.9% | 13.2% | -5.3% | |
| Corner pressure | 5.60 | 10.07 | -4.47 | |
| Drive Guard | 10.8% | 14.0% | -3.2% | |
| Drive Rush (cancel) | 36.4% | 33.2% | +3.2% | |
| Time cornered | 11.60 | 9.50 | +2.10 | |
| SA1 | 40.7% | 38.9% | +1.8% | |
| Drive Rush (parry) | 6.7% | 8.2% | -1.5% | |
| Drive Impact gauge | 0.9% | 2.0% | -1.1% | |
| Perfect Parry | 0.10 | 0.64 | -0.54 | |
| Drive Parry | 1.10 | 1.62 | -0.52 | |
| Got thrown | 2.60 | 2.18 | +0.42 | |
| Throws | 2.60 | 2.24 | +0.36 | |
| Drive Impact | 0.10 | 0.23 | -0.13 | |
| Stuns landed | 0.00 | 0.10 | -0.10 | |
| Got Punish Countered | 0.20 | 0.11 | +0.09 | |
| Drive Reversal | 0.50 | 0.43 | +0.07 | |
| Throw parries | 0.20 | 0.27 | -0.07 | |
| Got stunned | 0.10 | 0.04 | +0.06 | |
| Punish Counters landed | 0.10 | 0.14 | -0.04 | |
| Throw techs | 0.50 | 0.51 | -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.
Alex · Latest 100
What to improve
Find the cause of punish events
Punish Counters landed: profile 0 · reference 0.12
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 · reference 0.12
- Got Punish Countered: profile 0.1 · reference 0.12
Trace how you lose or gain space
Corner pressure: profile 4.7 · reference 9.01
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 4.7 · reference 9.01
- Time cornered: profile 11.7 · reference 9.88
Give each meter spend a purpose
SA1: profile 16.7% · reference 43%
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
- SA1: profile 16.7% · reference 43%
- SA2: profile 35% · reference 28.4%
- SA3: profile 43.3% · reference 22.1%
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 Ryu: 107 wins in 201 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 Ryu: 107 wins in 201 games
- vs Yasmine: 98 wins in 189 games
- vs Akuma: 95 wins in 166 games
Separate a tendency from a one-off event
Recent stored ranked sample: 30 wins in 63 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: 30 wins in 63 games
Test the Drive Impact tendency
Drive Impact: profile 0.1 · reference 0.2
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 0.1 · reference 0.2
- Drive Impact gauge: profile 0.9% · reference 1.7%
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