LarK-

LarK- — CS2 Stats

GB76561198254278373[U:1:294012645]Steam profile ↗✓ No bans

1,685Tracked matches53%Win rate2020Tracked since
4,666Hours in CS2Hrs last 2 wks
CSDB Rating5.7 SolidSupport
CSDB Leaderboard#99388 of 258808 tracked
FaceitLevel 9 · 1,648 ELOTop 20.7% of ranked FACEIT players
WingmanSupreme Master First Class
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 18,950 +1,319 8 Mar – 3 Jul · 23 days played
17,34818,950peak 18,9508 Mar3 Jul
18,950Peak Premier in tracked matches
1,648Highest Faceit ELO seen on CSDB
62Days played since 2026-01-24

Faceit ELO

  • At peak — 1,648
  • Next: Level 9 at 1,751 — 103 to go
  • Reached: Level 8 · Level 7 · Level 6 · Level 5

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 9 among CSDB-tracked players (n=15,132), 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 9 medianLevel 10 medianvs Level 10
Headshot rate49.7%48.2%50.9%1.3% short
Shot accuracy15.6%13.2%13.7%above
Kill/death ratio1.051.071.090.04 short
Match win rate46.7%46.9%48.4%1.7% short

This profile matches the typical Level 10 player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGLarK-FACEITLevel 9 · 1,648 ELOSTANDINGTop 20.7% of rankedPEAK ELO1,648csdb.gg/stats

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Performance scores

Aim75
Positioning50
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY57–40–3Last 10057%Win rateWWWLLLLLLW

Last 10 vs previous 10: −20pp win rate · +0.03 avg rating · −2.3pp headshot accuracy · −118ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 15%
  • Avg reaction 494ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 15%
  • Avg reaction 524ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 16%
  • Avg reaction 583ms

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 (+1.6 against its own average).

Aim7.5
Utility6.3
Positioning5.0
Opening Duels4.1
Clutch3.2

Strong CT-side opener

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 94% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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

T-side openings. Opening success drops from 55% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 595ms 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

Aim7.5
Positioning5.0
Utility6.3
Mechanics5.7
Opening Duels3.3
Win Impact6.1

Composite 5.7/10 (Solid), 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-0.00−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.00
Reaction time600ms−37ms
first ⅓ avg 637ms → last ⅓ avg 600ms
Headshot accuracy16.7%−0.2%
first ⅓ avg 16.9% → last ⅓ avg 16.7%

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

0.32Best match rating · 5–1 · rush_001, 7 Oct →
44%Best headshot accuracy · 9–4 · vertigo, 9 Jun →
422msFastest reaction time · 13–7 · cache, 18 May →
13–1Biggest win · nuke, 1 Apr →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W3Current streak
8–9In matches decided by ≤2 rounds
11Overtime games

Map breakdown

cacheBest map · 71% over 14nukeWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
mirageA2113–862%0.02
dust2B158–753%-0.00
cacheS1410–471%0.01
infernoA149–564%0.01
nukeD103–730%0.01
ancientA85–363%-0.01
anubisC83–538%-0.05
overpassD62–433%-0.02
poseidon—22–0100%-0.02
rush_001—11–0100%0.32
vertigo—11–0100%0.07

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

136,401Lifetime kills
1.05K/D
4,546Matches
46.7%Match win rate
49.7%Headshot % · Top 50% of Level 9 players
15.6%Shot accuracy · Top 50% of Level 9 players
12,931MVPs
2,560Hours (in match)
4,272Bombs planted
2,451Bombs defused

Most-used weapons

AK-4752,656
AWP17,827
Knife2,641
FAMAS2,536
SSG 082,274
P2502,153

Lifetime map wins

7,417inferno
4,972dust2
4,799train
3,459nuke
2,975cbble
1,290vertigo
69aztec
66bank

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

Faceit stats

Combat

1,564Matches
51%Win rate
1.05Avg K/D
73.4ADR
39%Headshot %

Clutches & streaks

36%1v1 clutch win
22%1v2 clutch win
9Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Ancient24348%0.9615.2
Anubis17347%0.9814.9
Mirage16153%0.9914.3
Nuke14454%1.0015.3
Inferno8945%1.0515.8
Overpass5564%1.1116.2
Dust24628%0.8013.1
Train4457%0.9915.3

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.

15.9%Headshot accuracy
38.2%Accuracy (enemy spotted)
41.8%Spray accuracy
75.7%Counter-strafing
8.9°Preaim
595msReaction time
31.8%T opening success
54.8%CT opening success
0.58Enemies flashed / flash
9.4%Flash assists
7.43HE damage / grenade
10.72Flashes / 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 31.7683% — 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.

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–10-0.016%15 Oct →
cache13–70.0822%15 Oct →
rush_0015–10.3212%7 Oct →
cache11–13-0.0320%29 Sept →
inferno10–13-0.0514%22 Sept →
cache8–130.0111%11 Sept →
ancient8–13-0.0421%31 Aug →
inferno13–160.0215%31 Aug →
anubis2–13-0.084%27 Aug →
inferno13–10-0.0123%19 Aug →
ancient16–140.0315%17 Aug →
cache5–13-0.0718%17 Aug →
ancient2–13-0.1122%15 Aug →
mirage13–11-0.0221%15 Aug →
cache13–110.0424%10 Aug →
mirage13–9-0.0114%28 Jul →
mirage11–130.0518%27 Jul →
cache9–0-0.0010%27 Jul →
dust25–13-0.0323%25 Jul →
mirage13–60.015%25 Jul →
dust212–16-0.0318%25 Jul →
dust26–13-0.0027%22 Jul →
inferno13–80.0214%4 Jul →
mirage16–140.0411%3 Jul →
mirage13–7-0.0012%3 Jul →
dust28–1-0.075%3 Jul →
anubis13–6-0.0212%1 Jul →
mirage6–13-0.0217%20 Jun →
inferno9–13-0.0314%18 Jun →
inferno13–7-0.0022%16 Jun →
overpass16–14-0.0012%9 Jun →
anubis6–13-0.0925%9 Jun →
vertigo9–40.0744%9 Jun →
nuke9–13-0.0513%7 Jun →
dust213–80.0716%7 Jun →
overpass2–13-0.095%7 Jun →
inferno13–8-0.0523%6 Jun →
cache7–13-0.0118%2 Jun →
mirage13–50.0621%1 Jun →
cache13–50.0117%30 May →
cache13–110.0622%30 May →
cache13–8-0.008%29 May →
ancient13–70.0422%29 May →
ancient13–90.0420%23 May →
nuke10–130.0519%23 May →
overpass11–13-0.0127%18 May →
nuke6–13-0.0013%18 May →
cache13–70.0113%18 May →
nuke13–2-0.0218%17 May →
mirage15–15-0.0310%17 May →
dust213–40.066%16 May →
inferno9–30.1624%16 May →
cache13–9-0.0125%3 May →
inferno13–80.086%3 May →
nuke7–130.029%3 May →
cache13–50.0640%1 May →
nuke2–13-0.0520%28 Apr →
mirage13–8-0.0444%28 Apr →
cache13–8-0.0221%23 Apr →
mirage13–80.0013%21 Apr →
mirage9–130.025%21 Apr →
dust26–13-0.0623%18 Apr →
dust26–00.0320%18 Apr →
anubis11–13-0.0217%16 Apr →
anubis8–13-0.0713%10 Apr →
mirage11–130.0418%10 Apr →
mirage15–150.0515%10 Apr →
dust29–13-0.0321%8 Apr →
mirage13–9-0.0420%2 Apr →
anubis16–14-0.0125%2 Apr →
nuke13–1-0.038%1 Apr →
overpass11–13-0.0310%28 Mar →
overpass13–50.0018%24 Mar →
mirage13–50.0423%24 Mar →
dust24–13-0.0711%19 Mar →
poseidon9–2-0.0821%19 Mar →
overpass9–130.0214%17 Mar →
nuke8–13-0.0318%16 Mar →
inferno13–9-0.027%16 Mar →
mirage11–130.0521%10 Mar →
dust213–80.0623%8 Mar →
mirage14–16-0.0116%7 Mar →
inferno9–30.0623%7 Mar →
ancient13–7-0.0118%5 Mar →
mirage13–9-0.0214%25 Feb →
ancient2–9-0.0714%23 Feb →
dust213–9-0.0026%23 Feb →
anubis16–12-0.0114%22 Feb →
inferno13–60.0118%22 Feb →
mirage13–100.0710%21 Feb →
dust213–110.0321%21 Feb →
mirage13–70.0829%19 Feb →
inferno15–150.0816%2 Feb →
poseidon9–50.0323%2 Feb →
nuke9–20.1615%29 Jan →
ancient13–40.0815%26 Jan →
dust23–13-0.0212%26 Jan →
inferno1–10-0.0813%25 Jan →
nuke11–130.0013%24 Jan →
anubis1–13-0.098%24 Jan →

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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