Lav1sh

Lav1sh — CS2 Stats

US76561198138547560[U:1:178281832]Steam profile ↗✓ No bans

1,698Tracked matches46%Win rate2022Tracked since
2,543Hours in CS44Hrs last 2 wks
CSDB Rating6.8 SolidPositional Player
Premier CS Rating17,869Purple band · top ~17% of ranked players (population est.)
WingmanGold Nova I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Oct 2026 (yesterday). 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: 17,869 +2,759 19 Jul – 13 Oct · 21 days played
15,11018,613peak 18,61319 Jul13 Oct
18,687Peak Premier in tracked matches
908Highest Faceit ELO seen on CSDB
35Days played since 2026-07-19

Faceit ELO

  • At peak — 908
  • Next: Level 5 at 1,051 — 143 to go
  • Reached: Level 4 · Level 3 · Level 2

Premier CS Rating

  • 744 below peak (18,613)
  • +1,482 over 30 days · improving
  • +2,759 over 90 days
  • Next: Pink band at 20,000 — 2,131 to go
  • Reached: Purple band · Blue band · 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 Purple band among CSDB-tracked players (n=37,767), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate54.7%44.3%46.9%above
Shot accuracy3.2%11.9%13.0%9.8% short
Kill/death ratio1.151.031.08above
Match win rate37.2%45.2%46.7%9.5% short

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

Widest gap: Shot accuracy. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGLav1shPREMIER17,869 · Purple bandPEAK ELO908csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim89
Positioning66
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY52–45–3Last 10052%Win rateLLLWLWWWLW

Last 10 vs previous 10: +30pp win rate · −0.02 avg rating · +0.5pp headshot accuracy · −30ms reaction

Win rate up 30pp 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 (−0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 24%
  • Avg reaction 587ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 21%
  • Avg reaction 552ms

Last 20

  • 7–11–2 · 35% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 21%
  • Avg reaction 567ms

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 (+1.8 against its own average).

Aim8.9
Utility4.3
Positioning6.6
Opening Duels5.1
Clutch3.2

Sharp aimer

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

s1mple

Plays most like s1mple 89% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution.

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

Aim. Aim score of 89 — the mechanical foundation is a clear strength.

Areas to improve

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

Reaction time. 581ms 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

Aim8.9
Positioning6.6
Utility4.3
Mechanics7.5
Opening Duels6.9
Win Impact3.8

Composite 6.8/10 (Solid), 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 rating0.02−0.02
first ⅓ avg 0.04 → last ⅓ avg 0.02
Reaction time583ms+8ms
first ⅓ avg 575ms → last ⅓ avg 583ms
Headshot accuracy18.6%−0.5%
first ⅓ avg 19.1% → last ⅓ avg 18.6%

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

0.21Best match rating · 6–9 · inferno, 4 Oct →
71%Best headshot accuracy · 3–9 · train, 15 Aug →
359msFastest reaction time · 13–9 · dust2, 19 Jul →
13–1Biggest win · fachwerk, 22 Jul →

Across the last 100 tracked matches.

Highlights

10Longest win streak
L3Current streak
9–5In matches decided by ≤2 rounds
4Overtime games

Map breakdown

mirageBest map · 60% over 20ancientWeakest map · 40% over 10
MapGradePlayedRecordWin rateAvg rating
mirageA2012–860%0.02
dust2B179–853%0.02
infernoB126–650%0.06
nukeB115–645%0.05
ancientC104–640%0.02
vertigoC94–544%0.05
cacheA74–357%-0.01
trainB63–350%0.04
anubisC52–340%0.02
office—11–0100%0.11
fachwerk—11–0100%0.13
shelter—11–0100%0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

71,374Lifetime kills
1.15K/D · Top 25% of Purple band
2,564Matches
37.2%Match win rate
54.7%Headshot % · Top 25% of Purple band
3.2%Shot accuracy
4,222MVPs
2,768Hours (in match)
2,010Bombs planted
780Bombs defused

Most-used weapons

Lifetime map wins

3,188dust2
2,136nuke
1,574inferno
1,223train
820vertigo
435office
115lake
99italy

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

Faceit stats

Combat

108Matches
55%Win rate
0.86Avg K/D
61.2ADR
33%Headshot %

Clutches & streaks

36%1v1 clutch win
12%1v2 clutch win
7Longest win streak

Recent Faceit resultsWLWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage2650%0.8311.5
Dust21968%0.9110.6
Ancient1856%0.8712.6
Overpass1450%0.9415.4
Nuke1060%0.7210.5
Inferno850%0.649.5
Train757%1.0814.4
Anubis425%0.8215.3

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.

18.5%Headshot accuracy
40.5%Accuracy (enemy spotted)
46.8%Spray accuracy
83.8%Counter-strafing
7.7°Preaim
581msReaction time
57.5%T opening success
57.6%CT opening success
0.52Enemies flashed / flash
3.7%Flash assists
6.74HE damage / grenade
8.32Flashes / match

Recommended for you

Spend your practice time on Ancient

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

40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis1–13-0.0628%13 Oct →
cache9–13-0.0322%13 Oct →
dust23–13-0.0517%13 Oct →
ancient16–140.0128%11 Oct →
vertigo8–130.1324%10 Oct →
train13–50.0922%10 Oct →
train13–60.1417%10 Oct →
inferno13–90.0526%10 Oct →
cache1–13-0.0910%10 Oct →
mirage13–9-0.0018%10 Oct →
dust23–13-0.0218%9 Oct →
mirage10–130.0716%6 Oct →
nuke6–90.1121%6 Oct →
ancient12–120.0122%5 Oct →
mirage13–11-0.0919%4 Oct →
inferno3–9-0.0526%4 Oct →
inferno8–80.1717%4 Oct →
inferno6–90.2130%4 Oct →
inferno13–80.0220%3 Oct →
nuke5–13-0.0518%3 Oct →
mirage1–13-0.0313%2 Oct →
dust27–130.0611%2 Oct →
train8–13-0.0222%29 Sept →
nuke13–70.0110%29 Sept →
anubis13–8-0.0121%29 Sept →
inferno13–7-0.0411%28 Sept →
cache13–11-0.0316%23 Sept →
dust213–110.0721%23 Sept →
inferno3–13-0.0520%23 Sept →
dust21–13-0.013%23 Sept →
vertigo12–120.1825%23 Sept →
dust27–130.0113%22 Sept →
anubis13–80.0911%22 Sept →
anubis8–130.1020%22 Sept →
mirage11–13-0.0330%18 Sept →
vertigo4–9-0.0411%16 Sept →
mirage13–110.0316%16 Sept →
ancient7–130.0017%16 Sept →
nuke7–90.1226%7 Sept →
office13–50.1125%4 Sept →
ancient6–130.0013%4 Sept →
mirage6–130.0924%3 Sept →
dust27–13-0.097%3 Sept →
ancient8–13-0.0118%28 Aug →
mirage5–13-0.0436%27 Aug →
inferno10–130.1413%27 Aug →
nuke6–130.008%27 Aug →
mirage13–5-0.008%27 Aug →
dust25–13-0.0211%23 Aug →
nuke13–100.056%23 Aug →
ancient9–13-0.043%22 Aug →
inferno13–9-0.0228%22 Aug →
ancient13–160.0525%20 Aug →
nuke13–160.0311%20 Aug →
dust213–80.0120%19 Aug →
dust213–100.0721%19 Aug →
mirage13–110.0117%19 Aug →
vertigo13–70.0840%19 Aug →
vertigo13–50.0717%18 Aug →
train3–130.0219%18 Aug →
ancient13–80.0818%16 Aug →
cache13–80.0329%16 Aug →
vertigo9–130.0220%16 Aug →
inferno7–90.1616%15 Aug →
mirage13–70.0818%15 Aug →
dust22–00.0333%15 Aug →
inferno9–10.0050%15 Aug →
cache13–100.0216%15 Aug →
ancient13–90.047%15 Aug →
vertigo8–4-0.0142%15 Aug →
train3–9-0.0371%15 Aug →
vertigo11–13-0.0217%15 Aug →
mirage7–13-0.0314%12 Aug →
vertigo13–110.0121%11 Aug →
train13–100.0728%11 Aug →
mirage13–70.1016%11 Aug →
dust213–30.1413%11 Aug →
mirage13–90.0116%11 Aug →
mirage13–30.0738%11 Aug →
nuke16–130.0512%10 Aug →
dust213–100.0224%10 Aug →
nuke13–90.0613%10 Aug →
dust213–70.0322%10 Aug →
anubis8–13-0.0124%10 Aug →
dust213–50.0715%30 Jul →
mirage9–13-0.0426%30 Jul →
cache13–100.0511%24 Jul →
cache9–13-0.0315%24 Jul →
mirage8–130.0016%24 Jul →
ancient13–70.0310%24 Jul →
dust26–13-0.128%24 Jul →
fachwerk13–10.1310%22 Jul →
shelter13–110.0616%21 Jul →
mirage13–100.0813%21 Jul →
dust213–90.123%19 Jul →
mirage13–80.0426%19 Jul →
nuke13–50.1315%19 Jul →
inferno13–20.1114%19 Jul →
nuke11–130.0516%19 Jul →
mirage13–10.0925%19 Jul →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.