Ryu
Updated 2 days agoSteamSteamUnited StatesUnited StatesC100%

Locusts

Let's Do This
Rank 34LP 23,332
Last 1010–0Last 2013–7
Winrate
53%
92W · 80L · 172 stored
Ranked matches
172
selected mode
Wins
92
Ranked
Losses
80
Ranked
Peak LP
23,332
Ryu

Ranked LP · Ryu

League points over time for this character

Latest game

VictoryRanked

Replay not requested
Ryu
Locusts · Ryu
A.K.I.
Opponent · A.K.I.Nunie_NY

Playstyle reference

Habits vs top 30 Ryu

Benchmark refreshed Sep 14, 2026, 1:24 PM

Latest reported trends across the last 100 matches, not lifetime habit averages. · Data details

Ryu
Locusts’s Ryu benchmark

Compared with the average habits of the top 30 sampled Ryu players.

Shuto 2303 · Sahara 2231 · Tigger 2230 · hinao 2224 · SDUINJNKPAADQQE 2184 · +25 others

Largest absolute differences first23 habits
HabitLocustsLegendsDifference LessLegendsMore
SA158.7%34.2%+24.5%
SA20.0%19.3%-19.3%
Drive Rush (cancel)51.6%38.7%+13.0%
SA326.7%37.6%-10.9%
Drive Guard4.2%11.3%-7.1%
Corner pressure4.6011.48-6.88
CA14.7%8.9%+5.7%
Drive Rush (parry)0.5%5.8%-5.3%
Drive Arts16.4%18.8%-2.5%
Drive Impact gauge1.9%1.1%+0.8%
Throws2.902.29+0.61
Perfect Parry0.300.75-0.45
Got thrown2.402.07+0.33
Punish Counters landed0.400.07+0.33
Drive Impact0.400.16+0.24
Drive Parry1.501.71-0.21
Throw techs0.300.45-0.15
Got stunned0.200.06+0.14
Got Punish Countered0.200.07+0.13
Throw parries0.100.22-0.12
Drive Reversal0.000.11-0.11
Stuns landed0.000.06-0.06
Time cornered8.708.74-0.04
FROM STATS TO PRACTICE

Match plan

Latest 100

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.

Ryu · Latest 100

What to improve

  1. Find the cause of punish events

    Punish Counters landed: profile 0.4 · 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 this

    Recreate 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 0.4 · reference 0.08
    • Got Punish Countered: profile 0.2 · reference 0.07
  2. Give each meter spend a purpose

    SA2: profile 0% · reference 20.3%

    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 this

    Practice 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
    • SA2: profile 0% · reference 20.3%
    • SA3: profile 26.7% · reference 35.4%
    • CA: profile 14.7% · reference 9.4%
  3. Review defensive decisions

    Drive Reversal: profile 0 · reference 0.15

    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 this

    Record 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 · reference 0.15
    • Throw techs: profile 0.3 · reference 0.44
    • Drive Parry: profile 1.5 · reference 1.69

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 12, 2026 · AI: dots-studio/dots-3-note-preview:free

How to beat this player

  1. Use matchup records as scouting leads

    vs Ingrid: 2 wins in 12 games

    A lower win rate suggests footage to examine, not a guaranteed counterpick. Check whether the same difficult situation appears in multiple matches.

    Try this

    If 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 Ingrid: 2 wins in 12 games
    • vs Yasmine: 2 wins in 12 games
  2. Separate a tendency from a one-off event

    Recent stored ranked sample: 48 wins in 100 games

    Scout several recent matches and compare wins with losses. Prepare around a repeated situation rather than one memorable mistake.

    Try this

    Use 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: 48 wins in 100 games
  3. Build pressure without overextending

    Corner pressure: profile 4.6 · reference 10.94

    Look for chances to gain space with familiar options. Once the opponent is cornered, observe how they actually try to leave before selecting an adjustment.

    Try this

    Test one pressure sequence you know well. If an escape repeats, rehearse an answer to that exact option; if they vary their defense, avoid committing to a single read.

    Supporting stats
    • Corner pressure: profile 4.6 · reference 10.94
    • Time cornered: profile 8.7 · reference 8.58

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 12, 2026 · AI: dots-studio/dots-3-note-preview:free

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