♡Asuna♡ — CS2 Stats

76561199097763875[U:1:1137498147]✓ No bans

1,928Tracked matches43%Win rate2023Tracked since
CSDB Rating4.7 DevelopingHybrid Rifler
Premier CS Rating10,372Blue band · top ~52.9% of ranked players (population est.)
CSDB Leaderboard#23819 of 32982 tracked
FaceitLevel 2 · 724 ELOTop 97.9% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GG♡Asuna♡FACEITLevel 2 · 724 ELOSTANDINGTop 97.9% of rankedPREMIER10,372 · Blue bandcsdb.gg/stats

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Performance scores

Aim66
Positioning48
Utility25

0–100 skill scores via Leetify.

Recent form

STEADY48448Last 10048%Win rateLLLLLWWWLW

Last 10 vs previous 10: -10pp win rate · +0.04 avg rating

Player DNA

Primary style: Hybrid RiflerAim-led profile without a single dominant tendency.

Aim6.6
Aggression4.8
Utility2.5
Positioning4.8
Opening Duels0.2
Clutch1.2

Excellent counter-strafingLimited utility dependence

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 81% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 738ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim6.6
Positioning4.8
Utility2.5
Mechanics8.6
Opening Duels0.5
Win Impact2.8

Composite 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time738ms+17ms
first ⅓ avg 721ms → last ⅓ avg 738ms
Headshot accuracy22.5%+2.5%
first ⅓ avg 20.0% → last ⅓ avg 22.5%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.14Best rating — inferno 13–2
131Biggest win — inferno
4Longest win streak
L5Current streak
810In matches decided by ≤2 rounds
10Overtime games

Map breakdown

ancientBest map · 89% over 9mirageWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
infernoC2191243%-0.00
nukeA169756%-0.02
dust2C156940%-0.02
anubisC125742%-0.03
ancientS98189%-0.03
trainB84450%-0.01
mirageD72529%-0.03
vertigoD62433%-0.04
overpass42250%-0.07
cache21150%0.01

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

36Matches
39%Win rate
0.72Avg K/D
61.1ADR
45%Headshot %

Clutches & streaks

26%1v1 clutch win
9%1v2 clutch win
2Longest win streak

Recent Faceit resultsWLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage1331%0.6810.7
Dust2838%0.7713.0
Inferno771%0.738.4
Ancient617%0.628.5
Train250%1.0217.5

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

22.6%Headshot accuracy
31.8%Accuracy (enemy spotted)
29.4%Spray accuracy
88.6%Counter-strafing
7.5°Preaim
738msReaction time
27.8%T opening success
33.9%CT opening success
0.27Enemies flashed / flash
7.4%Flash assists
8.30HE damage / grenade
1.71Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 737.7218ms — above the 700ms mark we flag

    Aim Training
  2. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.2659 — below the 0.5 mark we flag

    Grenade Lineups
  3. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 27.7683% — below the 40% mark we flag

Spend your practice time on Mirage

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategyMirage grenade lineups

Recent matches

MapScoreRatingHS%Date
cache3–13-0.0338%6 May
dust214–160.0822%6 May
inferno11–13-0.008%6 May
mirage3–13-0.0313%5 May
nuke7–13-0.0517%5 May
anubis13–7-0.0124%5 May
anubis13–90.0327%5 May
nuke13–5-0.0411%5 May
inferno3–13-0.0733%3 May
cache8–00.0631%30 Apr
vertigo13–11-0.0630%23 Apr
ancient16–14-0.0722%8 Apr
nuke11–13-0.0420%8 Apr
inferno13–5-0.0550%8 Apr
mirage7–130.0126%8 Apr
dust213–9-0.107%8 Apr
inferno3–13-0.0326%19 Mar
dust27–13-0.0829%19 Mar
dust29–13-0.0231%13 Mar
nuke13–80.0010%13 Mar
anubis13–11-0.0111%13 Mar
inferno6–13-0.1224%13 Mar
overpass9–13-0.1226%12 Mar
inferno11–13-0.0014%18 Feb
dust213–50.0715%18 Feb
dust213–40.0325%18 Feb
inferno7–130.0531%18 Feb
dust211–13-0.0329%12 Feb
inferno8–13-0.0324%11 Feb
inferno13–20.1419%8 Feb
anubis15–15-0.0812%3 Feb
anubis9–13-0.1515%3 Feb
nuke13–2-0.0524%3 Feb
dust213–9-0.077%3 Feb
ancient13–80.0026%27 Jan
ancient13–9-0.0615%27 Jan
anubis9–13-0.0913%25 Jan
inferno7–13-0.0518%25 Jan
dust213–100.0016%25 Jan
mirage13–8-0.0816%25 Jan
dust24–13-0.0126%25 Jan
nuke4–13-0.1119%25 Jan
dust25–13-0.0819%25 Jan
dust29–13-0.0122%25 Jan
overpass15–15-0.0316%24 Jan
ancient3–13-0.0819%24 Jan
anubis11–13-0.0415%24 Jan
anubis8–130.0328%22 Jan
nuke13–5-0.0612%22 Jan
dust216–14-0.0424%22 Jan
ancient13–11-0.088%22 Jan
anubis13–8-0.0313%22 Jan
train6–13-0.0320%19 Jan
train8–13-0.0419%14 Jan
nuke13–40.0324%14 Jan
inferno13–20.0925%13 Jan
inferno13–20.0912%11 Jan
overpass13–8-0.0910%11 Jan
mirage10–13-0.0217%11 Jan
nuke13–16-0.0317%11 Jan
nuke7–13-0.0221%11 Jan
train13–60.0115%31 Dec
vertigo8–13-0.0714%31 Dec
vertigo12–120.0031%29 Dec
inferno13–1-0.0429%29 Dec
ancient13–100.027%28 Dec
inferno7–13-0.0326%28 Dec
train16–13-0.0514%27 Dec
dust215–150.0312%27 Dec
dust215–15-0.0418%27 Dec
inferno13–50.0432%27 Dec
inferno13–6-0.0118%27 Dec
train11–13-0.0013%26 Dec
train13–40.0626%26 Dec
anubis13–9-0.0119%26 Dec
train13–40.0640%26 Dec
anubis5–13-0.0326%24 Dec
vertigo10–13-0.0512%24 Dec
vertigo2–13-0.0335%24 Dec
nuke13–40.0517%24 Dec
nuke13–6-0.0515%24 Dec
nuke13–30.0119%24 Dec
vertigo13–11-0.0217%24 Dec
mirage11–13-0.0422%24 Dec
ancient13–11-0.0614%24 Dec
overpass13–11-0.0218%24 Dec
nuke5–13-0.0112%24 Dec
inferno13–20.0610%23 Dec
inferno5–13-0.0632%23 Dec
inferno12–12-0.0321%19 Dec
train12–12-0.0721%19 Dec
ancient16–13-0.0025%15 Dec
ancient13–90.0713%15 Dec
mirage11–130.0418%15 Dec
anubis12–12-0.038%15 Dec
inferno10–13-0.0716%15 Dec
nuke11–13-0.0529%14 Dec
nuke13–80.0333%14 Dec
mirage13–7-0.0621%14 Dec
inferno13–70.0412%14 Dec

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →