Gurk

Gurk — CS2 Stats

US76561198153592958[U:1:193327230]Steam profile ↗✓ No bans

69Tracked matches43%Win rate2023Tracked since
110Hours in CS
CSDB Rating2.9 LearningPositional Player
Premier CS Rating3,912Grey band · top ~83.4% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 Nov 2025 (322 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: 3,912 -871 26 Sept – 22 Nov · 14 days played
3,6074,783peak 4,78326 Sept22 Nov
4,999Peak Premier in tracked matches
31Days played since 2023-03-27

Premier CS Rating

  • 871 below peak (4,783)
  • -240 over 30 days · steady
  • Next: Light Blue band at 5,000 — 1,088 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate36.9%38.2%39.9%3.0% short
Shot accuracy15.0%3.6%7.0%above
Kill/death ratio0.990.830.92above
Match win rate27.8%40.2%42.3%14.4% short

This profile matches the typical Light Blue band player on 2 of 4 comparable metrics.

Widest gap: Match win rate. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGGurkPREMIER3,912 · Grey bandcsdb.gg/stats

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Performance scores

Aim28
Positioning42
Utility39

0–100 skill scores via Leetify.

Recent form

STEADY32–34–3Last 6946%Win rateLWWWLWWLLL

Last 10 vs previous 10: +30pp win rate · +0.00 avg rating · +5.0pp headshot accuracy · +16ms reaction

Win rate up 30pp 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 22%
  • Avg reaction 659ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 19%
  • Avg reaction 647ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 639ms

Newest first, from the last 69 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 (+1.5 against its own average).

Aim2.8
Utility3.9
Positioning4.2
Opening Duels0.0

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 64% 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

Areas to improve

Reaction time. 643ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim2.8
Positioning4.2
Utility3.9
Mechanics4.1
Opening Duels0.2
Win Impact2.8

Composite 2.9/10 (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-0.04−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.04
Reaction time642ms+21ms
first ⅓ avg 621ms → last ⅓ avg 642ms
Headshot accuracy15.8%+1.2%
first ⅓ avg 14.6% → last ⅓ avg 15.8%

Rolling 5-match average across the last 69 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.07Best match rating · 13–2 · nuke, 30 Sept →
44%Best headshot accuracy · 13–7 · nuke, 6 Dec →
453msFastest reaction time · 3–13 · dust2, 22 Oct →
13–1Biggest win · anubis, 7 Sept →

Across the last 69 tracked matches.

Highlights

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

Map breakdown

ancientBest map · 60% over 5infernoWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
nukeC177–1041%-0.02
dust2A1710–759%-0.04
mirageC104–640%-0.05
infernoC83–538%-0.04
ancientA53–260%-0.02
train—31–233%-0.01
office—21–150%-0.02
vertigo—21–150%-0.01
overpass—20–20%-0.01
anubis—21–150%-0.01
agency—11–0100%0.03

Across the last 69 tracked matches.

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

Lifetime stats

8,884Lifetime kills
0.99K/D · Top 25% of Grey band
769Matches
27.8%Match win rate
36.9%Headshot %
15.0%Shot accuracy · Top 10% of Grey band
271MVPs
110Hours (in match)
128Bombs planted
39Bombs defused

Most-used weapons

Lifetime map wins

332dust2
246nuke
185inferno
85vertigo
72train
69lake
49ar_shoots
30safehouse

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.8%Headshot accuracy
29.5%Accuracy (enemy spotted)
25.6%Spray accuracy
68.3%Counter-strafing
11.9°Preaim
643msReaction time
31.5%T opening success
22.8%CT opening success
0.57Enemies flashed / flash
3.1%Flash assists
4.33HE damage / grenade
7.56Flashes / 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 14.7688% — below the 15% mark we flag

    Aim Training →
  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 31.4615% — below the 40% mark we flag

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.

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

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke10–13-0.0517%29 Jan →
office13–70.0319%7 Dec →
agency13–50.0317%7 Dec →
nuke13–7-0.0444%6 Dec →
vertigo2–13-0.0211%23 Nov →
dust213–5-0.0813%22 Nov →
dust213–8-0.0133%11 Nov →
inferno0–9-0.230%10 Nov →
train10–130.0524%28 Oct →
mirage8–13-0.037%27 Oct →
nuke6–13-0.0228%27 Oct →
overpass8–13-0.0321%25 Oct →
dust23–13-0.0411%22 Oct →
mirage10–130.0011%19 Oct →
dust211–13-0.0710%14 Oct →
mirage11–13-0.1014%3 Oct →
nuke13–8-0.0212%3 Oct →
mirage7–13-0.0617%1 Oct →
nuke13–8-0.005%1 Oct →
nuke11–13-0.077%1 Oct →
dust213–3-0.038%1 Oct →
nuke13–60.0313%1 Oct →
mirage13–8-0.0821%1 Oct →
dust213–11-0.0615%30 Sept →
nuke4–130.0313%30 Sept →
nuke13–20.0714%30 Sept →
inferno8–13-0.0210%29 Sept →
train9–13-0.037%29 Sept →
nuke10–13-0.025%29 Sept →
mirage13–7-0.037%29 Sept →
dust212–16-0.0011%28 Sept →
inferno15–15-0.0621%28 Sept →
ancient10–13-0.0214%28 Sept →
nuke8–13-0.126%26 Sept →
inferno13–110.035%26 Sept →
overpass10–13-0.0011%26 Sept →
train13–10-0.072%26 Sept →
ancient13–16-0.0610%26 Sept →
dust213–8-0.0314%26 Sept →
nuke13–70.0325%25 Sept →
dust213–9-0.058%25 Sept →
nuke10–13-0.028%25 Sept →
ancient13–7-0.026%25 Sept →
mirage4–13-0.0911%25 Sept →
mirage10–13-0.0719%25 Sept →
dust213–9-0.0112%24 Sept →
nuke10–13-0.029%23 Sept →
ancient13–70.059%23 Sept →
inferno12–160.0119%22 Sept →
mirage13–8-0.0218%22 Sept →
dust213–10-0.0416%21 Sept →
nuke4–13-0.0418%21 Sept →
dust27–13-0.0522%21 Sept →
inferno15–15-0.028%20 Sept →
mirage13–40.0013%20 Sept →
inferno13–90.0117%20 Sept →
ancient13–10-0.046%20 Sept →
nuke11–13-0.0414%20 Sept →
vertigo13–50.0022%18 Sept →
nuke13–30.0516%18 Sept →
dust213–4-0.0514%18 Sept →
anubis12–12-0.0613%14 Sept →
inferno13–5-0.0818%13 Sept →
dust23–13-0.1014%7 Sept →
dust213–30.0012%7 Sept →
anubis13–10.0415%7 Sept →
office8–13-0.0617%3 Sept →
dust20–16-0.085%27 Mar →
dust27–16-0.0520%27 Mar →

Match data via Leetify.

Recent teammates

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

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