ΞΝΤЯΟРУ™

ΞΝΤЯΟРУ™ — CS2 Stats

CA76561197969395993[U:1:9130265]Steam profile ↗✓ No bans

1,455Tracked matches43%Win rate2023Tracked since
1,791Hours in CS8Hrs last 2 wks
CSDB Rating4.8 DevelopingSupport
Premier CS Rating13,958Blue band · top ~33.9% of ranked players (population est.)
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 15 Oct 2026 (2 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

13,958Peak Premier in tracked matches
50Days played since 2026-05-15

Premier CS Rating

  • At peak — 13,958
  • Next: Purple band at 15,000 — 1,042 to go
  • Reached: Blue band · Light Blue band

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

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=14,290), 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 4 medianLevel 5 medianvs Level 5
Headshot rate40.9%42.7%43.7%2.9% short
Shot accuracy5.3%11.3%12.0%6.7% short
Kill/death ratio0.850.991.020.17 short
Match win rate40.8%43.9%44.7%3.9% short

This profile sits below the typical Level 5 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGΞΝΤЯΟРУ™FACEITLevel 4STANDINGTop 81.0% of rankedPREMIER13,958 · Blue bandcsdb.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

Aim68
Positioning44
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY53–39–8Last 10053%Win rateWWWLLLLLLW

Last 10 vs previous 10: −20pp win rate · −0.04 avg rating · −0.6pp headshot accuracy · −1ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 558ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 634ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 635ms

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 (+1.2 against its own average).

Aim6.8
Utility4.5
Positioning4.4
Opening Duels1.1

Strong CT-side openerLimited 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 95% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; lower opening-duel success.

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

Reaction time. 628ms 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

Aim6.8
Positioning4.4
Utility4.5
Mechanics6.3
Opening Duels2.5
Win Impact2.6

Composite 4.8/10 (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 time627ms−26ms
first ⅓ avg 653ms → last ⅓ avg 627ms
Headshot accuracy15.3%−0.3%
first ⅓ avg 15.6% → last ⅓ avg 15.3%

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

0.12Best match rating · 9–0 · vertigo, 24 Sept →
38%Best headshot accuracy · 4–13 · mirage, 1 Sept →
406msFastest reaction time · 6–13 · inferno, 15 Sept →
13–1Biggest win · inferno, 19 Jun →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W3Current streak
9–5In matches decided by ≤2 rounds
4Overtime games

Map breakdown

cacheBest map · 82% over 11nukeWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
dust2A1811–761%-0.01
mirageC145–936%-0.04
anubisB136–746%-0.02
infernoB126–650%-0.04
ancientA127–558%-0.00
cacheS119–282%0.01
nukeD93–633%0.01
vertigoB63–350%0.04
train—42–250%-0.03
overpass—11–0100%0.00

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

35,847Lifetime kills
0.85K/D
2,867Matches
40.8%Match win rate
40.9%Headshot %
5.3%Shot accuracy
3,070MVPs
922Hours (in match)
1,701Bombs planted
341Bombs defused

Most-used weapons

Lifetime map wins

6,682dust2
2,556inferno
2,004nuke
1,516vertigo
799train
380office
196dust
134aztec

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

Faceit stats

Combat

18Matches
50%Win rate
0.58Avg K/D
—ADR
55%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
3Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage875%0.629.4
Vertigo30%0.5910.0
Inferno367%0.467.0
Ancient20%0.579.0
Anubis1100%0.8319.0
Dust210%0.294.0

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.

15.8%Headshot accuracy
37.8%Accuracy (enemy spotted)
38.1%Spray accuracy
78.2%Counter-strafing
9.8°Preaim
628msReaction time
34.0%T opening success
45.8%CT opening success
0.69Enemies flashed / flash
6.8%Flash assists
4.90HE damage / grenade
3.86Flashes / 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. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.8597 — below the 4 mark we flag

    Grenade Lineups →
  2. 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 34.0321% — 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.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–11-0.0713%15 Oct →
inferno13–50.038%15 Oct →
dust216–13-0.0415%14 Oct →
mirage8–130.0110%12 Oct →
dust25–130.0120%12 Oct →
inferno7–13-0.0214%12 Oct →
dust213–16-0.0525%9 Oct →
mirage8–13-0.0514%9 Oct →
mirage6–13-0.0923%8 Oct →
mirage13–11-0.0513%8 Oct →
vertigo13–30.0421%5 Oct →
mirage13–40.0620%29 Sept →
dust27–13-0.0727%29 Sept →
anubis11–13-0.0515%24 Sept →
vertigo9–00.1214%24 Sept →
vertigo10–130.0218%23 Sept →
dust213–9-0.0212%21 Sept →
mirage11–13-0.036%20 Sept →
anubis13–8-0.0611%20 Sept →
dust213–30.0916%15 Sept →
inferno6–13-0.117%15 Sept →
train9–13-0.0815%14 Sept →
mirage13–9-0.019%14 Sept →
dust213–20.039%14 Sept →
mirage2–13-0.058%6 Sept →
nuke15–15-0.0422%6 Sept →
mirage7–13-0.0623%1 Sept →
mirage4–13-0.0838%1 Sept →
nuke12–120.0520%27 Aug →
ancient8–130.0210%23 Aug →
inferno6–13-0.085%23 Aug →
dust213–9-0.0321%23 Aug →
vertigo8–13-0.058%20 Aug →
mirage11–13-0.059%20 Aug →
dust28–13-0.0714%20 Aug →
dust212–12-0.049%16 Aug →
nuke7–13-0.098%16 Aug →
nuke12–12-0.057%10 Aug →
anubis13–6-0.0412%10 Aug →
dust213–9-0.0223%31 Jul →
inferno13–90.0111%31 Jul →
inferno13–16-0.0118%27 Jul →
dust211–13-0.0313%26 Jul →
anubis4–13-0.058%25 Jul →
anubis2–13-0.069%23 Jul →
vertigo12–120.0315%18 Jul →
overpass13–100.0012%18 Jul →
cache13–100.0320%13 Jul →
inferno13–10-0.058%13 Jul →
ancient13–110.0114%13 Jul →
nuke13–90.0811%9 Jul →
cache13–90.0410%9 Jul →
ancient7–13-0.0124%8 Jul →
cache13–110.0221%8 Jul →
anubis10–13-0.0014%6 Jul →
nuke13–50.1112%6 Jul →
ancient13–4-0.0310%6 Jul →
ancient8–13-0.0221%4 Jul →
mirage11–13-0.0818%4 Jul →
nuke7–130.048%29 Jun →
vertigo13–70.0618%29 Jun →
ancient13–50.0122%26 Jun →
cache12–120.0026%26 Jun →
ancient4–13-0.0717%25 Jun →
dust212–120.0324%24 Jun →
ancient13–80.0723%22 Jun →
mirage13–60.0317%21 Jun →
cache4–0-0.050%21 Jun →
dust213–80.0819%20 Jun →
inferno13–20.0718%20 Jun →
anubis13–100.0018%19 Jun →
cache6–13-0.0318%19 Jun →
inferno13–10.0320%19 Jun →
train12–12-0.0211%19 Jun →
anubis9–13-0.0513%18 Jun →
dust213–110.0124%18 Jun →
ancient13–70.007%14 Jun →
train13–70.0516%14 Jun →
cache13–20.0112%14 Jun →
inferno3–9-0.1519%14 Jun →
anubis13–100.0124%12 Jun →
ancient13–100.0020%8 Jun →
nuke13–60.018%8 Jun →
cache13–30.0111%8 Jun →
anubis13–5-0.023%8 Jun →
inferno1–9-0.267%8 Jun →
anubis13–30.0826%6 Jun →
nuke8–130.0221%6 Jun →
cache9–00.0218%2 Jun →
dust213–11-0.0317%2 Jun →
ancient13–110.0223%1 Jun →
inferno13–80.086%1 Jun →
dust213–4-0.0214%1 Jun →
train13–5-0.0729%31 May →
anubis7–130.0216%31 May →
anubis6–13-0.0426%28 May →
cache13–11-0.0115%19 May →
dust213–9-0.037%19 May →
ancient7–13-0.0518%15 May →
cache13–110.0514%15 May →

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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