SKK

SKK — CS2 Stats

76561199204561264[U:1:1244295536]Steam profile ↗✓ No bans

173Tracked matches48%Win rate2024Tracked since
CSDB Rating4.8 DevelopingPositional Player
Premier CS Rating11,553Blue band · top ~46.7% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 2026 (5 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: 11,553 +2,988 23 Sept – 30 Oct · 21 days played
8,56511,866peak 11,86623 Sept30 Oct
11,922Peak Premier in tracked matches
42Days played since 2025-08-24

Premier CS Rating

  • 313 below peak (11,866)
  • +1,553 over 30 days · improving
  • Next: Purple band at 15,000 — 3,447 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.

Share this profile

CSDB.GGSKKPREMIER11,553 · Blue bandcsdb.gg/stats

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Performance scores

Aim56
Positioning61
Utility23

0–100 skill scores via Leetify.

Recent form

STEADY48–46–6Last 10048%Win rateLTLWWLLWWW

Last 10 vs previous 10: 0pp win rate · −0.00 avg rating · −8.0pp headshot accuracy · +51ms 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 11%
  • Avg reaction 619ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 9%
  • Avg reaction 602ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 577ms

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 (+2 against its own average).

Aim5.6
Utility2.3
Positioning6.1
Opening Duels2.2
Clutch6.0

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

donk

Plays most like donk 78% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

Strengths

T openings. 60% T opening-duel success — entries that actually open the round.

Areas to improve

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

CT openings. Opening success drops from 60% on T to 45% on CT — first contacts on the defending side are being lost.

Reaction time. 576ms 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

Aim5.6
Positioning6.1
Utility2.3
Mechanics5.3
Opening Duels5.6
Win Impact4.4

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 rating0.00−0.02
first ⅓ avg 0.02 → last ⅓ avg 0.00
Reaction time576ms−16ms
first ⅓ avg 593ms → last ⅓ avg 576ms
Headshot accuracy11.5%+1.2%
first ⅓ avg 10.4% → last ⅓ avg 11.5%

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.

Personal bests

0.18Best match rating · 9–1 · inferno, 26 Oct →
67%Best headshot accuracy · 9–2 · inferno, 26 Oct →
367msFastest reaction time · 1–6 · vertigo, 24 Aug →
13–0Biggest win · dust2, 30 Dec →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–8In matches decided by ≤2 rounds
10Overtime games

Map breakdown

nukeBest map · 65% over 17cacheWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
infernoA2113–862%0.00
anubisB189–950%0.01
nukeS1711–665%0.03
ancientC114–736%-0.01
dust2A116–555%0.01
mirageC114–736%-0.03
cacheD71–614%-0.00
vertigo—30–30%-0.02
train—10–10%0.04

Across the last 100 tracked matches.

Faceit stats

Combat

2Matches
0%Win rate
1.00Avg K/D
83.4ADR
40%Headshot %

Clutches & streaks

50%1v1 clutch win
0%1v2 clutch win
0Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Anubis10%1.0013.0
Mirage10%1.0016.0

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.

9.3%Headshot accuracy
36.1%Accuracy (enemy spotted)
37.6%Spray accuracy
73.8%Counter-strafing
10.2°Preaim
576msReaction time
60.2%T opening success
44.6%CT opening success
0.27Enemies flashed / flash
0.9%Flash assists
8.70HE damage / grenade
3.52Flashes / 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 Crosshair

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

    Headshot accuracy 9.3371% — below the 15% 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 0.2745 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Cache

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
cache6–13-0.0312%30 Oct →
nuke15–150.0811%30 Oct →
nuke4–9-0.050%30 Oct →
nuke9–00.0927%30 Oct →
nuke13–80.054%28 Oct →
ancient11–13-0.037%27 Oct →
anubis6–130.0110%27 Oct →
anubis13–10.026%26 Oct →
nuke13–20.034%26 Oct →
dust216–12-0.067%26 Oct →
dust215–15-0.0518%26 Oct →
inferno9–40.0819%26 Oct →
inferno9–10.1813%26 Oct →
inferno9–20.1467%26 Oct →
inferno5–9-0.118%24 Oct →
ancient9–13-0.127%23 Oct →
dust216–130.0213%23 Oct →
ancient8–13-0.064%22 Oct →
mirage13–40.007%22 Oct →
cache8–130.0613%22 Oct →
dust213–3-0.0210%22 Oct →
inferno9–5-0.130%22 Oct →
inferno2–9-0.016%21 Oct →
inferno9–40.107%21 Oct →
mirage13–9-0.1411%21 Oct →
mirage11–13-0.0515%21 Oct →
ancient13–90.0412%21 Oct →
inferno9–3-0.0515%21 Oct →
mirage13–8-0.0410%19 Oct →
dust29–130.0810%19 Oct →
inferno9–70.058%19 Oct →
mirage9–13-0.0410%18 Oct →
inferno13–11-0.029%18 Oct →
inferno9–13-0.027%18 Oct →
anubis11–13-0.085%18 Oct →
dust215–150.028%15 Oct →
cache13–90.078%15 Oct →
anubis13–90.027%14 Oct →
mirage7–13-0.039%14 Oct →
nuke7–90.012%14 Oct →
inferno9–4-0.0818%14 Oct →
mirage9–130.0010%13 Oct →
cache7–130.008%13 Oct →
nuke13–10.057%13 Oct →
nuke13–2-0.009%13 Oct →
anubis13–11-0.0213%12 Oct →
cache5–13-0.068%6 Oct →
ancient8–13-0.0212%5 Oct →
ancient13–11-0.0410%5 Oct →
anubis15–150.059%2 Oct →
anubis16–14-0.007%1 Oct →
nuke13–8-0.0414%1 Oct →
nuke13–9-0.014%1 Oct →
mirage10–13-0.049%1 Oct →
anubis5–130.0410%29 Sept →
dust210–130.0912%29 Sept →
dust28–13-0.0217%29 Sept →
anubis13–110.0411%29 Sept →
inferno5–9-0.113%29 Sept →
anubis5–13-0.133%28 Sept →
dust213–50.0420%24 Sept →
anubis2–13-0.0510%24 Sept →
anubis13–9-0.006%24 Sept →
dust213–8-0.0010%24 Sept →
nuke9–60.1018%24 Sept →
inferno12–30.0012%23 Sept →
inferno13–100.035%23 Sept →
ancient15–15-0.0317%23 Sept →
anubis13–70.033%23 Sept →
anubis11–130.007%22 Sept →
inferno6–13-0.005%22 Sept →
nuke11–130.046%22 Sept →
cache1–13-0.0614%22 Sept →
anubis13–80.0112%22 Sept →
inferno9–60.0314%22 Sept →
inferno10–130.015%20 Sept →
anubis15–150.0711%20 Sept →
nuke13–6-0.005%20 Sept →
ancient2–13-0.0115%18 Sept →
inferno16–130.1117%16 Sept →
cache8–130.0113%16 Sept →
ancient13–9-0.0315%28 Aug →
nuke13–20.126%23 May →
nuke10–130.0414%16 Apr →
inferno5–9-0.0512%8 Feb →
inferno2–9-0.137%8 Feb →
nuke13–70.0411%1 Jan →
mirage5–13-0.049%31 Dec →
mirage13–110.0914%31 Dec →
nuke5–13-0.0310%31 Dec →
dust213–00.0615%30 Dec →
ancient13–50.1310%22 Dec →
train11–130.048%11 Dec →
mirage10–130.0017%8 Dec →
ancient11–130.039%24 Sept →
vertigo3–100.032%17 Sept →
anubis10–130.0813%2 Sept →
anubis13–4-0.0117%29 Aug →
vertigo6–130.017%26 Aug →
vertigo1–6-0.090%24 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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