CM LuuK

CM LuuK — CS2 Stats

FR76561198364323878[U:1:404058150]Steam profile ↗✓ No bans

320Tracked matches52%Win rate2021Tracked since
259Hours in CS
CSDB Rating3.7 LearningPositional Player
Premier CS Rating6,689Light Blue band · top ~70.7% of ranked players (population est.)
WingmanGold Nova II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Oct 2026 (23 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: 6,689 +1,147 21 Feb – 13 Oct · 6 days played
4,3546,689peak 6,68921 Feb13 Oct
6,689Peak Premier in tracked matches
37Days played since 2026-01-30

Premier CS Rating

  • At peak — 6,689
  • Next: Blue band at 10,000 — 3,311 to go
  • Reached: 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 Light Blue band among CSDB-tracked players (n=8,820), 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 playerLight Blue band medianBlue band medianvs Blue band
Headshot rate36.0%39.9%42.0%6.0% short
Shot accuracy12.4%7.0%9.6%above
Kill/death ratio0.750.920.980.23 short
Match win rate42.4%42.3%43.8%1.4% short

This profile matches the typical Blue band player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGCM LuuKPREMIER6,689 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim39
Positioning50
Utility33

0–100 skill scores via Leetify.

Recent form

HOT39–53–8Last 10039%Win rateWWWWTLWTWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −0.7pp headshot accuracy · +37ms reaction

Win rate up 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

  • 4–0–1 · 80% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 544ms

Last 10

  • 7–1–2 · 70% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 571ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 12%
  • Avg reaction 553ms

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).

Aim3.9
Utility3.3
Positioning5.0
Opening Duels0.6

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

iM

Plays most like iM 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

Areas to improve

Reaction time. 558ms 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

Aim3.9
Positioning5.0
Utility3.3
Mechanics3.9
Opening Duels2.7
Win Impact5.6

Composite 3.7/10 (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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time563ms−117ms
first ⅓ avg 680ms → last ⅓ avg 563ms
Headshot accuracy12.4%−1.4%
first ⅓ avg 13.8% → last ⅓ avg 12.4%

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

0.19Best match rating · 9–3 · inferno, 2 Oct →
29%Best headshot accuracy · 4–13 · dust2, 8 Feb →
406msFastest reaction time · 11–13 · ancient, 2 Oct →
13–1Biggest win · ancient, 20 Feb →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W4Current streak
2–8In matches decided by ≤2 rounds
6Overtime games

Map breakdown

infernoBest map · 54% over 26anubisWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
infernoB2614–1254%-0.01
mirageD186–1233%-0.04
nukeB157–847%-0.02
dust2D134–931%-0.02
ancientC83–538%-0.03
anubisD61–517%-0.03
vertigoC52–340%0.02
cache—41–325%-0.03
office—41–325%-0.02
overpass—10–10%-0.03

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

12,283Lifetime kills
0.75K/D
703Matches
42.4%Match win rate · Top 50% of Light Blue band
36.0%Headshot %
12.4%Shot accuracy · Top 50% of Light Blue band
1,482MVPs
259Hours (in match)
660Bombs planted
192Bombs defused

Most-used weapons

Lifetime map wins

2,213inferno
1,180dust2
663vertigo
475nuke
140train
121office
39cbble
22lake

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.

12.1%Headshot accuracy
30.6%Accuracy (enemy spotted)
32.4%Spray accuracy
67.8%Counter-strafing
11.8°Preaim
558msReaction time
45.1%T opening success
36.3%CT opening success
0.41Enemies flashed / flash
2.4%Flash assists
7.44HE damage / grenade
1.60Flashes / 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 12.0726% — 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 0.4124 — below the 0.5 mark we flag

    Grenade Lineups →
  3. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 36.2839% — below the 40% mark we flag

Spend your practice time on Anubis

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–4-0.0219%13 Oct →
ancient13–2-0.0414%13 Oct →
inferno13–6-0.1214%13 Oct →
dust213–4-0.059%13 Oct →
inferno12–120.0110%10 Oct →
anubis10–13-0.094%10 Oct →
nuke13–70.0619%7 Oct →
ancient15–15-0.0113%7 Oct →
inferno13–50.047%7 Oct →
ancient13–10-0.0011%7 Oct →
ancient8–13-0.059%5 Oct →
inferno13–5-0.083%4 Oct →
nuke13–7-0.045%3 Oct →
mirage16–13-0.0518%3 Oct →
mirage11–13-0.0911%3 Oct →
dust23–13-0.039%3 Oct →
cache3–13-0.0824%3 Oct →
inferno13–7-0.0112%3 Oct →
mirage13–110.079%3 Oct →
inferno9–130.0026%2 Oct →
ancient11–13-0.0415%2 Oct →
nuke4–13-0.0410%2 Oct →
cache9–13-0.067%2 Oct →
dust29–13-0.0614%2 Oct →
inferno9–30.1912%2 Oct →
nuke4–9-0.0122%2 Oct →
vertigo7–130.0020%29 Sept →
nuke13–7-0.039%29 Sept →
inferno4–13-0.078%29 Sept →
inferno13–10-0.0814%28 Sept →
vertigo12–120.0112%28 Sept →
ancient9–13-0.078%27 Sept →
mirage4–13-0.0616%27 Sept →
inferno4–13-0.034%25 Sept →
mirage10–13-0.0918%21 Sept →
anubis7–13-0.0416%21 Sept →
inferno13–3-0.0413%9 Sept →
dust213–30.0116%9 Sept →
vertigo13–5-0.0211%4 Sept →
nuke5–13-0.037%4 Sept →
inferno2–13-0.107%4 Sept →
inferno4–13-0.002%3 Sept →
mirage12–12-0.0913%3 Sept →
cache9–130.039%1 Jul →
inferno6–9-0.0311%1 Jul →
vertigo7–90.0711%1 Jul →
overpass15–15-0.0311%4 Jun →
mirage11–13-0.089%3 Jun →
office7–90.018%30 May →
mirage13–5-0.0711%30 May →
dust210–13-0.029%30 May →
office4–13-0.096%29 May →
anubis13–11-0.057%29 May →
mirage3–13-0.064%29 May →
inferno5–13-0.068%6 Mar →
dust212–12-0.0210%6 Mar →
nuke10–13-0.0013%6 Mar →
mirage11–13-0.0119%6 Mar →
dust213–6-0.0313%6 Mar →
inferno13–4-0.028%6 Mar →
inferno5–90.0210%4 Mar →
anubis12–120.009%1 Mar →
vertigo13–50.0410%25 Feb →
mirage13–3-0.0212%25 Feb →
office13–60.048%24 Feb →
inferno13–7-0.0214%24 Feb →
anubis12–120.008%21 Feb →
mirage11–13-0.0420%21 Feb →
nuke13–8-0.065%21 Feb →
nuke13–6-0.037%21 Feb →
inferno3–130.036%21 Feb →
mirage8–13-0.0922%21 Feb →
nuke16–13-0.0512%20 Feb →
ancient13–10.028%20 Feb →
ancient10–13-0.0612%19 Feb →
inferno13–10-0.0010%17 Feb →
dust27–13-0.0215%16 Feb →
mirage13–4-0.046%16 Feb →
nuke13–6-0.0110%16 Feb →
inferno13–8-0.0213%13 Feb →
nuke2–13-0.0624%13 Feb →
mirage10–13-0.0413%10 Feb →
nuke13–160.039%10 Feb →
anubis9–13-0.0111%10 Feb →
mirage8–130.057%10 Feb →
dust213–160.039%10 Feb →
mirage3–13-0.0417%10 Feb →
dust213–40.0417%9 Feb →
inferno13–5-0.0018%9 Feb →
mirage13–20.0120%9 Feb →
dust26–130.007%8 Feb →
inferno13–30.1218%8 Feb →
nuke7–13-0.0615%8 Feb →
dust24–13-0.0529%8 Feb →
nuke11–130.0316%5 Feb →
office6–13-0.0521%5 Feb →
dust29–13-0.0610%2 Feb →
inferno5–13-0.0410%2 Feb →
inferno13–8-0.0117%30 Jan →
inferno1–13-0.0425%30 Jan →

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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