Latest game
VictoryRanked
M.
YAM.Updated 5 days ago
CrossPlatform
JapanClub · unteaC99%
CrossPlatformJapanClub · unteaC99%山本文夫
Special A-Type Maverick Hunter
MR 1,712#22,421Last 106–4+3Last 2012–8+16
Winrate
53%
37W · 33L · 70 stored
Ranked matches
70
selected mode
Wins
37
Ranked
Losses
33
Ranked
Peak MR
1,767
M. Bison
Ranked MR · M. Bison
70 local · 0 imported · 70 on chart · 180 battles stored
Replay not requested
M.YAPlaystyle reference
Habits vs top 30 M. Bison
Benchmark refreshed Sep 13, 2026, 1:26 PM
Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details
M.Largest absolute differences first23 habits
| Habit | 山本文夫 | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA1 | 51.0% | 33.7% | +17.4% | |
| Drive Rush (cancel) | 12.7% | 30.0% | -17.3% | |
| Drive Arts | 35.6% | 18.7% | +16.8% | |
| SA2 | 10.4% | 21.0% | -10.5% | |
| SA3 | 26.0% | 35.2% | -9.1% | |
| Drive Rush (parry) | 10.1% | 7.2% | +2.9% | |
| CA | 12.5% | 10.2% | +2.3% | |
| Time cornered | 7.70 | 9.85 | -2.15 | |
| Drive Impact gauge | 3.6% | 1.5% | +2.1% | |
| Drive Guard | 11.7% | 13.4% | -1.6% | |
| Drive Parry | 0.40 | 1.75 | -1.35 | |
| Corner pressure | 10.80 | 11.91 | -1.11 | |
| Perfect Parry | 0.10 | 0.74 | -0.64 | |
| Got thrown | 2.10 | 2.59 | -0.49 | |
| Throws | 2.90 | 2.42 | +0.48 | |
| Got Punish Countered | 0.30 | 0.09 | +0.21 | |
| Drive Impact | 0.40 | 0.19 | +0.21 | |
| Throw techs | 0.40 | 0.57 | -0.17 | |
| Punish Counters landed | 0.20 | 0.11 | +0.09 | |
| Throw parries | 0.20 | 0.26 | -0.06 | |
| Got stunned | 0.10 | 0.04 | +0.06 | |
| Drive Reversal | 0.30 | 0.33 | -0.03 | |
| Stuns landed | 0.10 | 0.07 | +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.
M. Bison · Latest 100
What to improve
Find the cause of punish events
Punish Counters landed: profile 0.3 · reference 0.09
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 0.3 · reference 0.09
- Got Punish Countered: profile 0.2 · reference 0.07
Review defensive decisions
Drive Parry: profile 0.4 · reference 1.76
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 Parry: profile 0.4 · reference 1.76
- Perfect Parry: profile 0.2 · reference 0.68
- Drive Reversal: profile 0.3 · reference 0.3
Give each meter spend a purpose
Drive Arts: profile 36.4% · reference 17.8%
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
- Drive Arts: profile 36.4% · reference 17.8%
- SA1: profile 56.5% · reference 30.3%
- SA3: profile 21.2% · reference 40.4%
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 7, 2026 · AI: dots-studio/dots-3-note-preview:free
How to beat this player
Use matchup records as scouting leads
vs Luke: 33 wins in 59 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 Luke: 33 wins in 59 games
- vs Marisa: 35 wins in 50 games
Test the Drive Impact tendency
Drive Impact: profile 0.4 · 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 0.4 · reference 0.18
- Drive Impact gauge: profile 3.3% · reference 1.4%
Test the close-range pattern
Throws: profile 2.5 · reference 2.55
Observe actual strike, throw and defensive choices at close range. Change one part of your familiar mix only after a tendency appears.
Try thisIf the same response repeats twice, try a different option in that situation. If the player changes their response, return to varied choices instead of assuming the pattern is permanent.
Supporting stats
- Throws: profile 2.5 · reference 2.55
- Got thrown: profile 1.8 · reference 2.48
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 7, 2026 · AI: dots-studio/dots-3-note-preview:free