Latest game
DefeatRanked
M.
INM.Updated 1 week ago
Steam
JapanM100%
SteamJapanM100%Honey
Go Beyond the Battle!
MR 1,488#326,349Last 104–6-9Last 209–11-12
Winrate
53%
59W · 53L · 112 stored
Ranked matches
112
selected mode
Wins
59
Ranked
Losses
53
Ranked
Peak MR
1,557
M. Bison
Ranked MR · M. Bison
112 local · 0 imported · 112 on chart · 112 battles stored
Replay not requested
M.INPlaystyle 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 | Honey | Legends | Difference | LessLegendsMore |
|---|---|---|---|---|
| SA1 | 0.0% | 33.7% | -33.7% | |
| Drive Rush (cancel) | 0.3% | 30.0% | -29.7% | |
| SA3 | 60.8% | 35.2% | +25.6% | |
| Drive Arts | 28.4% | 18.7% | +9.6% | |
| CA | 19.6% | 10.2% | +9.4% | |
| Drive Rush (parry) | 15.6% | 7.2% | +8.4% | |
| Drive Guard | 19.3% | 13.4% | +6.0% | |
| Corner pressure | 9.90 | 11.91 | -2.01 | |
| SA2 | 19.6% | 21.0% | -1.4% | |
| Drive Impact gauge | 2.5% | 1.5% | +1.0% | |
| Drive Parry | 0.80 | 1.75 | -0.95 | |
| Time cornered | 10.60 | 9.85 | +0.75 | |
| Throws | 3.10 | 2.42 | +0.68 | |
| Perfect Parry | 0.10 | 0.74 | -0.64 | |
| Drive Reversal | 0.80 | 0.33 | +0.47 | |
| Got thrown | 2.20 | 2.59 | -0.39 | |
| Throw techs | 0.30 | 0.57 | -0.27 | |
| Throw parries | 0.40 | 0.26 | +0.14 | |
| Got Punish Countered | 0.20 | 0.09 | +0.11 | |
| Drive Impact | 0.30 | 0.19 | +0.11 | |
| Punish Counters landed | 0.20 | 0.11 | +0.09 | |
| Stuns landed | 0.00 | 0.07 | -0.07 | |
| Got stunned | 0.00 | 0.04 | -0.04 |
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
Got Punish Countered: profile 0.2 · reference 0.07
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 0.07
- Punish Counters landed: profile 0.2 · reference 0.09
Review defensive decisions
Drive Reversal: profile 0.8 · reference 0.3
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 Reversal: profile 0.8 · reference 0.3
- Drive Parry: profile 0.8 · reference 1.76
- Perfect Parry: profile 0.1 · reference 0.68
Trace how you lose or gain space
Corner pressure: profile 9.9 · reference 12.04
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 9.9 · reference 12.04
- Time cornered: profile 10.6 · reference 9.28
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 Yasmine: 31 wins in 71 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 Yasmine: 31 wins in 71 games
- vs Luke: 31 wins in 66 games
- vs Akuma: 35 wins in 63 games
Separate a tendency from a one-off event
Recent stored ranked sample: 54 wins in 100 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: 54 wins in 100 games
Test the Drive Impact tendency
Drive Impact: profile 0.3 · 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 0.3 · reference 0.18
- Drive Impact gauge: profile 2.5% · reference 1.4%
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 6, 2026 · AI: dots-studio/dots-3-note-preview:free