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ainoo

ainoo — CS2 Stats

76561199120943577[U:1:1160677849]Steam profile ↗✓ No bans

4,359Tracked matches33%Win rate2021Tracked since
CSDB Rating2.1 LearningPositional Player
Premier CS Rating6,475Light Blue band · top ~71.7% of ranked players (population est.)
CSDB Leaderboard#191350 of 251281 tracked
FaceitLevel 2 · 512 ELOTop 97.9% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 9 Oct 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 6,475 -5,119 6 Sept – 9 Oct · 16 days played
6,47511,594peak 11,5946 Sept9 Oct
12,434Peak Premier in tracked matches
512Highest Faceit ELO seen on CSDB
17Days played since 2026-09-06

Faceit ELO

  • At peak — 512
  • Next: Level 3 at 751 — 239 to go
  • Reached: Level 2
  • Level 2 first seen 2026-09-20

Premier CS Rating

  • 5,119 below peak (11,594)
  • -3,928 over 30 days · declining
  • Next: Blue band at 10,000 — 3,525 to go
  • Reached: Blue band · Light Blue band
  • Light Blue band first seen 2026-09-20

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGainooFACEITLevel 2 · 512 ELOSTANDINGTop 97.9% of rankedPREMIER6,475 · Light Blue bandPEAK ELO512csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim16
Positioning31
Utility22

0–100 skill scores via Leetify.

Recent form

STEADY32–67–1Last 10032%Win rateLWLWLWLWWL

Last 10 vs previous 10: +10pp win rate · −0.00 avg rating · +0.1pp headshot accuracy · +22ms reaction

Win rate +10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 11%
  • Avg reaction 861ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 10%
  • Avg reaction 815ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 10%
  • Avg reaction 804ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.7 against its own average).

Aim1.6
Utility2.2
Positioning3.1
Opening Duels0.0
Clutch0.4

Limited 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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

ZywOo

Plays most like ZywOo 70% playstyle similarity

Most alike: positioning profile, opening-duel success.

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

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

CT openings. Opening success drops from 45% on T to 29% on CT — first contacts on the defending side are being lost.

Reaction time. 773ms 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

Aim1.6
Positioning3.1
Utility2.2
Mechanics5.0
Opening Duels1.9
Win Impact0.0

Composite 2.1/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05−0.00
first ⅓ avg -0.04 → last ⅓ avg -0.05
Reaction time778ms+69ms
first ⅓ avg 709ms → last ⅓ avg 778ms
Headshot accuracy11.3%+0.2%
first ⅓ avg 11.1% → last ⅓ avg 11.3%

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.

Personal bests

0.02Best match rating · 9–13 · inferno, 2 Oct →
27%Best headshot accuracy · 11–13 · ancient, 2 Oct →
438msFastest reaction time · 11–13 · nuke, 6 Sept →
13–1Biggest win · cache, 30 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–7In matches decided by ≤2 rounds
4Overtime games

Map breakdown

nukeBest map · 55% over 20infernoWeakest map · 20% over 10
MapGradePlayedRecordWin rateAvg rating
nukeA2011–955%-0.04
ancientD195–1426%-0.05
cacheD175–1229%-0.06
dust2D113–827%-0.03
infernoD102–820%-0.05
mirageB84–450%-0.04
anubisD82–625%-0.05
vertigo—40–40%-0.08
train—20–20%-0.07
overpass—10–10%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

285Matches
41%Win rate
0.43Avg K/D
47.6ADR
36%Headshot %

Clutches & streaks

22%1v1 clutch win
4%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Nuke5347%0.457.4
Inferno4337%0.458.4
Ancient3858%0.548.8
Dust22232%0.427.2
Anubis1735%0.519.1
Train1631%0.518.4
Mirage1436%0.345.4
Vertigo40%0.448.0

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.

11.1%Headshot accuracy
29.7%Accuracy (enemy spotted)
28.3%Spray accuracy
72.4%Counter-strafing
13.1°Preaim
773msReaction time
45.3%T opening success
29.2%CT opening success
0.26Enemies flashed / flash
3.1%Flash assists
6.76HE damage / grenade
3.62Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.1193° — above the 12° mark we flag

    Aim Training →
  2. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 11.075% — below the 15% mark we flag

    Aim Training →
  3. 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 772.605ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Inferno

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

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage8–13-0.0710%9 Oct →
mirage13–3-0.0411%9 Oct →
dust28–13-0.0819%9 Oct →
mirage13–9-0.079%9 Oct →
inferno9–13-0.074%9 Oct →
ancient13–9-0.018%9 Oct →
dust211–13-0.023%9 Oct →
nuke13–100.0114%9 Oct →
nuke13–10-0.0213%8 Oct →
mirage5–130.018%8 Oct →
mirage13–5-0.005%8 Oct →
inferno12–16-0.088%7 Oct →
cache13–8-0.0120%7 Oct →
mirage5–13-0.0214%7 Oct →
inferno11–13-0.0111%7 Oct →
dust25–130.008%7 Oct →
inferno3–13-0.007%7 Oct →
nuke13–8-0.1414%3 Oct →
cache7–13-0.095%3 Oct →
mirage13–30.006%3 Oct →
mirage10–13-0.1010%3 Oct →
vertigo8–13-0.105%3 Oct →
anubis10–13-0.057%3 Oct →
ancient10–13-0.0624%3 Oct →
cache10–13-0.1116%3 Oct →
nuke3–13-0.0411%3 Oct →
anubis1–13-0.089%3 Oct →
ancient13–30.006%3 Oct →
cache7–13-0.1126%3 Oct →
nuke1–13-0.0422%3 Oct →
dust215–15-0.067%3 Oct →
ancient11–13-0.1027%2 Oct →
nuke13–4-0.048%2 Oct →
cache7–13-0.1210%2 Oct →
inferno3–13-0.117%2 Oct →
nuke6–13-0.108%2 Oct →
ancient2–13-0.0711%2 Oct →
cache6–13-0.098%2 Oct →
ancient4–13-0.074%2 Oct →
anubis11–13-0.0513%2 Oct →
overpass6–13-0.0410%2 Oct →
train10–13-0.0119%2 Oct →
vertigo9–13-0.0713%2 Oct →
cache5–13-0.0413%2 Oct →
inferno9–130.0219%2 Oct →
anubis13–8-0.0215%2 Oct →
nuke7–130.019%2 Oct →
cache5–13-0.1123%1 Oct →
nuke13–11-0.0312%1 Oct →
ancient9–13-0.0715%1 Oct →
cache13–11-0.0413%1 Oct →
nuke8–13-0.0314%1 Oct →
dust213–16-0.0326%30 Sept →
cache13–1-0.017%30 Sept →
ancient11–13-0.073%30 Sept →
ancient6–13-0.048%26 Sept →
nuke13–7-0.0814%26 Sept →
cache13–9-0.0311%26 Sept →
ancient8–13-0.078%26 Sept →
nuke13–90.0115%26 Sept →
cache8–13-0.0518%25 Sept →
ancient13–11-0.058%24 Sept →
nuke6–13-0.0717%24 Sept →
cache13–1-0.0210%24 Sept →
anubis13–10-0.037%24 Sept →
cache5–13-0.0811%24 Sept →
inferno13–11-0.0922%18 Sept →
anubis2–13-0.080%18 Sept →
ancient4–13-0.0613%18 Sept →
inferno1–13-0.0517%18 Sept →
train2–13-0.140%18 Sept →
nuke3–13-0.0812%18 Sept →
vertigo3–13-0.0722%18 Sept →
cache2–13-0.045%18 Sept →
ancient3–13-0.0615%18 Sept →
nuke9–130.0113%18 Sept →
nuke13–10-0.038%15 Sept →
inferno13–10-0.037%15 Sept →
dust27–13-0.0515%13 Sept →
ancient13–7-0.014%13 Sept →
anubis8–13-0.0821%13 Sept →
ancient6–9-0.029%13 Sept →
ancient2–13-0.0518%13 Sept →
nuke13–11-0.0515%13 Sept →
vertigo6–13-0.095%12 Sept →
cache9–13-0.057%12 Sept →
inferno5–13-0.038%11 Sept →
nuke13–11-0.077%11 Sept →
cache10–13-0.035%11 Sept →
dust213–8-0.0117%11 Sept →
ancient4–13-0.0316%11 Sept →
anubis7–13-0.0120%10 Sept →
ancient8–130.017%10 Sept →
dust23–9-0.040%10 Sept →
dust211–13-0.018%6 Sept →
nuke11–13-0.0511%6 Sept →
dust213–9-0.0123%6 Sept →
ancient13–10-0.1215%6 Sept →
dust216–13-0.0312%6 Sept →
nuke13–6-0.0411%6 Sept →

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 →

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