skuul

skuul — CS2 Stats

76561198119489393[U:1:159223665]Steam profile ↗✓ No bans

1,277Tracked matches43%Win rate2021Tracked since
CSDB Rating5.4 DevelopingSupport
Premier CS Rating19,602Top 50% of 180,525 CSDB-tracked playersPurple band · top ~10.1% of ranked players (population est.)
CSDB Leaderboard#80503 of 225180 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Sep 2026 (16 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,277 tracked matches. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 52 days played since 30 Oct 2025. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 19,602 -4,508 30 Oct2 Sept · 31 days played
18,54525,100peak 25,10030 Oct2 Sept
25,100Peak Premier in tracked matches
1,850Highest Faceit ELO seen on CSDB
52Days played since 2025-10-30

Faceit ELO

  • At peak — 1,850
  • Next: Level 10 at 2,001 151 to go
  • Reached: Level 9 · Level 8 · Level 7 · Level 6
  • Level 9 first seen 2026-09-02
  • Level 8 first seen 2026-09-02

Premier CS Rating

  • 5,498 below peak (25,100)
  • Next: Pink band at 20,000 398 to go
  • Reached: Red band · Pink band · Purple band · Blue band
  • Purple band first seen 2026-09-02
  • Blue band first seen 2026-09-02

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.GGskuulPREMIER19,602 · Purple bandPEAK ELO1,850csdb.gg/stats

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Performance scores

Aim69
Positioning50
Utility50

0–100 skill scores via Leetify.

Recent form

STEADY37567Last 10037%Win rateLWLLLLLWWW

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · +2.2pp headshot accuracy · −52ms 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

  • 14 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 24%
  • Avg reaction 663ms

Last 10

  • 46 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 25%
  • Avg reaction 633ms

Last 20

  • 7121 · 35% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 24%
  • Avg reaction 659ms

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: SupportUtility contribution stands above the rest of this profile (+1 against its own average).

Aim6.9
Utility5.0
Positioning5.0
Opening Duels1.9
Clutch4.2

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

NiKo

Plays most like NiKo 88% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; 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. 660ms 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
Positioning5.0
Utility5.0
Mechanics7.6
Opening Duels1.3
Win Impact2.6

Composite 5.4/10 (Developing), 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-0.01−0.01
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time666ms−7ms
first ⅓ avg 673ms → last ⅓ avg 666ms
Headshot accuracy24.3%+2.4%
first ⅓ avg 21.9% → last ⅓ avg 24.3%

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

0.20Best match rating · 13–3 · overpass, 16 Jan
64%Best headshot accuracy · 1–7 · mirage, 19 Mar
500msFastest reaction time · 11–13 · ancient, 23 Jul
13–1Biggest win · ancient, 24 Jan

Across the last 100 tracked matches.

Highlights

3Longest win streak
512In matches decided by ≤2 rounds
11Overtime games

Map breakdown

overpassBest map · 50% over 10dust2Weakest map · 27% over 11
MapGradePlayedRecordWin rateAvg rating
mirageC2281436%-0.01
nukeC2181338%0.02
infernoC156940%-0.02
dust2D113827%-0.02
ancientB115645%0.00
overpassB105550%0.05
anubisC52340%0.01
train4040%-0.02
vertigo1010%-0.01

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

390Matches
53%Win rate
1.06Avg K/D
71.9ADR
49%Headshot %

Clutches & streaks

41%1v1 clutch win
15%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Nuke2544%0.9014.8
Mirage2152%0.8615.4
Ancient1540%0.9315.8
Anubis1464%1.1216.4
Vertigo1258%1.0516.1
Inferno1040%0.8815.1
Train650%0.8611.3
Dust240%0.7412.8

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.

24.6%Headshot accuracy
29.8%Accuracy (enemy spotted)
32.2%Spray accuracy
84.4%Counter-strafing
8.0°Preaim
660msReaction time
30.2%T opening success
40.1%CT opening success
0.65Enemies flashed / flash
4.0%Flash assists
6.85HE damage / grenade
5.73Flashes / 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 30.1602% — below the 40% mark we flag

Spend your practice time on Dust 2

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategyDust 2 grenade lineups

Recent matches

MapScoreRatingHS%Date
dust210–130.0129%8 Aug
anubis13–30.0111%8 Aug
mirage6–13-0.0923%8 Aug
vertigo12–16-0.0136%7 Aug
mirage7–13-0.0620%26 Jul
nuke8–13-0.0422%26 Jul
ancient11–13-0.0631%23 Jul
nuke13–100.0538%21 Jul
anubis13–90.0017%21 Jul
nuke19–150.0025%19 Jul
dust211–13-0.0514%19 Jul
dust28–13-0.0320%18 Jul
dust213–80.0133%3 Jul
inferno3–13-0.1114%3 Jul
mirage3–13-0.0737%26 Jun
inferno1–13-0.127%26 Jun
ancient13–30.1629%26 Jun
mirage13–8-0.0332%13 May
ancient15–150.0718%10 Apr
nuke8–130.0526%9 Apr
inferno13–20.0327%8 Apr
mirage13–50.0623%7 Apr
ancient15–15-0.0319%5 Apr
mirage11–130.0223%29 Mar
dust213–5-0.0128%26 Mar
mirage13–10-0.0318%22 Mar
nuke10–130.0328%22 Mar
inferno13–100.0330%19 Mar
mirage1–70.0564%19 Mar
inferno8–130.0113%27 Feb
mirage5–13-0.0211%27 Feb
dust25–13-0.1216%9 Feb
inferno7–13-0.0119%9 Feb
nuke13–110.0731%31 Jan
anubis11–13-0.0335%24 Jan
inferno13–9-0.0326%24 Jan
overpass7–130.0432%24 Jan
ancient13–1-0.0121%24 Jan
inferno4–13-0.086%24 Jan
nuke15–15-0.0033%23 Jan
inferno13–7-0.0335%23 Jan
overpass13–40.0739%23 Jan
dust24–13-0.0417%23 Jan
mirage1–13-0.0124%23 Jan
ancient2–9-0.110%23 Jan
anubis11–130.070%23 Jan
nuke13–100.0243%23 Jan
nuke13–50.0734%23 Jan
dust28–130.0029%23 Jan
mirage10–13-0.0416%23 Jan
inferno13–20.0615%23 Jan
overpass13–110.030%22 Jan
overpass13–70.0822%21 Jan
anubis14–160.0334%21 Jan
inferno11–13-0.0527%20 Jan
train7–13-0.0334%20 Jan
nuke15–150.0728%18 Jan
mirage4–13-0.0426%16 Jan
overpass13–30.2034%16 Jan
dust24–13-0.0719%14 Jan
nuke11–130.0724%14 Jan
mirage9–130.0131%14 Jan
overpass13–100.0227%13 Jan
mirage13–20.0818%13 Jan
nuke9–130.0222%9 Jan
overpass11–130.0231%7 Jan
inferno9–13-0.0327%7 Jan
nuke4–13-0.0527%7 Jan
nuke5–13-0.0131%7 Jan
mirage3–13-0.0619%4 Jan
ancient13–11-0.0341%3 Jan
overpass6–130.0430%3 Jan
nuke13–11-0.0624%2 Jan
inferno7–13-0.0212%2 Jan
mirage13–7-0.0522%17 Dec
ancient13–50.0117%17 Dec
nuke14–16-0.0021%11 Dec
mirage9–130.0128%11 Dec
nuke12–12-0.0123%11 Dec
dust213–70.0122%10 Dec
nuke8–130.0118%10 Dec
overpass9–130.0723%10 Dec
mirage13–9-0.0012%10 Dec
ancient6–130.0323%9 Dec
mirage13–90.0130%7 Dec
train11–13-0.0322%23 Nov
nuke13–160.0116%11 Nov
overpass10–13-0.0517%11 Nov
train11–13-0.0117%9 Nov
ancient13–8-0.048%8 Nov
inferno15–150.0516%7 Nov
nuke13–11-0.0129%7 Nov
mirage13–6-0.0117%6 Nov
ancient4–130.0225%5 Nov
mirage15–150.0417%5 Nov
dust28–130.0233%4 Nov
train7–13-0.0232%4 Nov
nuke13–80.0619%3 Nov
inferno13–80.0221%31 Oct
mirage7–13-0.0411%30 Oct

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 →