naju

naju — CS2 Stats

NO76561197992277190[U:1:32011462]Steam profile ↗✓ No bans

1,375Tracked matches61%Win rate2020Tracked since
3,405Hours in CS0Hrs last 2 wks
CSDB Rating6.1 SolidSupport
FaceitLevel 10Top 12.4% of ranked FACEIT players
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 24 Sep 2026 (33 days ago). Ranks are recorded once per day this page is viewed.

+8Tracked matches · now 1,375
0.0ppWin rate · 60.7% → 60.7%

Rating over time

Premier CS Rating: 25,729 -691 1 Nov – 29 Dec · 8 days played
25,59726,421peak 26,4211 Nov29 Dec
26,629Peak Premier in tracked matches
57Days played since 2025-11-01

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches16——
Win rate31%——
K/D0.96——
Headshot %44%——

Measured 24 Sep 2026 → 27 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=30,986), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 10 median
Headshot rate37.5%50.9%
Shot accuracy13.4%13.7%
Kill/death ratio1.071.09
Match win rate40.0%48.4%

Share this profile

CSDB.GGnajuFACEITLevel 10STANDINGTop 12.4% of rankedcsdb.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

Aim69
Positioning41
Utility66

0–100 skill scores via Leetify.

Recent form

HOT53–44–3Last 10053%Win rateLWWLLWWWWW

Last 10 vs previous 10: 0pp win rate · +0.04 avg rating · +10.1pp headshot accuracy · −28ms reaction

Win rate 0pp 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 0.00
  • Avg headshot accuracy 35%
  • Avg reaction 541ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 30%
  • Avg reaction 568ms

Last 20

  • 14–6 · 70% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 25%
  • Avg reaction 582ms

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: Support — Utility contribution stands above the rest of this profile (+2.3 against its own average).

Aim6.9
Utility6.6
Positioning4.1
Opening Duels3.0
Clutch3.4

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 84% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower aim profile; lower positioning 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

T-side openings. Opening success drops from 47% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 599ms 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

Aim6.9
Positioning4.1
Utility6.6
Mechanics7.3
Opening Duels2.2
Win Impact8.6

Composite 6.1/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time600ms−14ms
first ⅓ avg 613ms → last ⅓ avg 600ms
Headshot accuracy24.0%+3.5%
first ⅓ avg 20.5% → last ⅓ avg 24.0%

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

0.13Best match rating · 7–13 · cache, 14 Jun →
100%Best headshot accuracy · 0–13 · mirage, 6 Oct →
359msFastest reaction time · 2–8 · dust2, 6 Oct →
13–1Biggest win · cache, 9 May →

Across the last 100 tracked matches.

Highlights

7Longest win streak
12–7In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 63% over 16nukeWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
cacheA2916–1355%-0.00
ancientA1810–856%0.00
infernoA1610–663%0.01
dust2B157–847%-0.03
nukeC83–538%-0.03
anubisC73–443%-0.01
mirageA53–260%-0.01
train—21–150%-0.02

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

148,312Lifetime kills
1.07K/D
5,718Matches
40.0%Match win rate
37.5%Headshot %
13.4%Shot accuracy
11,012MVPs
2,436Hours (in match)
2,621Bombs planted
1,049Bombs defused

Most-used weapons

AWP35,411
AK-4722,086
MAC-1014,805
SCAR-2014,345
AUG5,447
MP95,168
Knife2,611

Lifetime map wins

16,429inferno
9,068dust2
3,328train
2,167nuke
2,145vertigo
960cbble
57office
17militia

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

628Matches
54%Win rate
1.01Avg K/D
81.0ADR
49%Headshot %

Clutches & streaks

37%1v1 clutch win
16%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Ancient11760%1.0115.7
Anubis11346%0.9814.9
Inferno8367%1.1816.9
Dust27046%0.9814.6
Vertigo3549%0.9915.8
Nuke2752%0.9514.5
Mirage1926%0.8814.2
Overpass944%0.9315.3

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.

23.1%Headshot accuracy
31.1%Accuracy (enemy spotted)
41.3%Spray accuracy
82.8%Counter-strafing
11.7°Preaim
599msReaction time
30.1%T opening success
47.2%CT opening success
0.51Enemies flashed / flash
8.1%Flash assists
10.26HE damage / grenade
17.53Flashes / 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

    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 30.0985% — below the 40% mark we flag

Spend your practice time on Nuke

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

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust22–8-0.0422%6 Oct →
cache4–10.0914%6 Oct →
inferno13–90.0524%6 Oct →
mirage0–13-0.09100%6 Oct →
cache8–130.0214%30 Sept →
mirage16–130.0322%29 Sept →
cache13–110.0017%29 Sept →
dust213–5-0.0119%29 Sept →
ancient13–100.0140%21 Sept →
cache13–60.0329%21 Sept →
dust213–11-0.0531%21 Sept →
anubis13–10-0.0615%21 Sept →
cache8–13-0.0320%31 Jul →
cache13–11-0.090%31 Jul →
cache13–8-0.0220%25 Jul →
cache11–13-0.0126%24 Jul →
cache13–8-0.0419%23 Jul →
cache3–13-0.0223%23 Jul →
cache13–7-0.0628%22 Jul →
cache13–50.0217%21 Jul →
cache13–6-0.0238%20 Jul →
cache13–20.0926%3 Jul →
cache2–9-0.0116%3 Jul →
cache13–10-0.0220%26 Jun →
cache7–130.1326%14 Jun →
cache12–12-0.0220%13 Jun →
cache11–13-0.0215%8 Jun →
cache12–12-0.0123%6 Jun →
cache9–13-0.059%30 May →
cache11–130.0124%22 May →
cache13–10-0.0019%18 May →
cache2–30.0338%10 May →
cache13–9-0.0718%9 May →
cache13–10.0614%9 May →
cache6–13-0.0025%5 May →
cache13–9-0.0819%2 May →
cache13–110.0518%30 Apr →
ancient4–13-0.058%4 Feb →
nuke4–13-0.0736%4 Feb →
ancient22–180.0115%30 Jan →
inferno13–10.0520%29 Jan →
inferno4–13-0.0116%29 Jan →
inferno13–70.030%25 Jan →
nuke13–8-0.080%23 Jan →
anubis7–13-0.000%23 Jan →
ancient16–14-0.010%22 Jan →
inferno13–60.080%22 Jan →
inferno7–130.0121%14 Jan →
ancient13–80.0511%14 Jan →
anubis8–130.0222%13 Jan →
ancient11–13-0.0216%13 Jan →
dust213–60.0421%12 Jan →
inferno7–130.0135%12 Jan →
anubis4–13-0.0219%11 Jan →
ancient13–20.0422%11 Jan →
dust216–12-0.0422%9 Jan →
ancient13–9-0.0116%9 Jan →
nuke9–13-0.0010%5 Jan →
ancient7–13-0.0116%5 Jan →
dust225–21-0.0122%4 Jan →
anubis5–13-0.0413%4 Jan →
inferno9–130.0620%2 Jan →
dust27–13-0.0117%2 Jan →
inferno10–13-0.0628%2 Jan →
inferno13–110.0218%2 Jan →
ancient13–90.0229%2 Jan →
nuke13–7-0.0126%29 Dec →
ancient15–150.0024%29 Dec →
dust24–13-0.0720%27 Dec →
nuke5–13-0.0726%27 Dec →
mirage13–11-0.0314%21 Dec →
mirage13–60.0229%20 Dec →
inferno13–8-0.0217%19 Dec →
inferno13–80.0121%19 Dec →
nuke11–13-0.0319%19 Dec →
nuke10–130.0128%18 Dec →
anubis13–60.0019%10 Dec →
inferno4–13-0.0122%10 Dec →
mirage7–130.0017%10 Dec →
inferno13–60.039%9 Dec →
ancient13–100.0417%8 Dec →
dust216–190.0219%8 Dec →
inferno16–140.0022%1 Dec →
dust24–13-0.0525%1 Dec →
dust214–16-0.0715%1 Dec →
dust213–2-0.0121%1 Dec →
train13–90.0322%1 Dec →
anubis19–170.0019%28 Nov →
nuke13–110.0323%28 Nov →
ancient13–110.0529%28 Nov →
dust26–13-0.0518%28 Nov →
dust29–13-0.0233%24 Nov →
ancient13–80.0121%21 Nov →
ancient10–130.0320%20 Nov →
ancient9–13-0.0421%17 Nov →
ancient6–13-0.0317%11 Nov →
dust213–11-0.0619%11 Nov →
inferno13–8-0.0318%9 Nov →
ancient9–13-0.0219%1 Nov →
train2–13-0.0612%1 Nov →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 101,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.