L ミ 0 N 16_11

L ミ 0 N 16_11 — CS2 Stats

VA76561198314208672[U:1:353942944]Steam profile ↗✓ No bans

1,535Tracked matches48%Win rate2020Tracked since
4,741Hours in CS6Hrs last 2 wks
CSDB Rating4.4 DevelopingClutch Specialist
Premier CS Rating14,601Blue band · top ~30.5% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 25 Oct 2026 (10 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: 14,601 -967 29 Aug – 25 Oct · 29 days played
13,43718,390peak 18,39029 Aug25 Oct
18,774Peak Premier in tracked matches
29Days played since 2026-08-29

Premier CS Rating

  • 3,789 below peak (18,390)
  • -1,627 over 30 days · declining
  • Next: Purple band at 15,000 — 399 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-08-30
  • Blue band first seen 2026-08-30

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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate32.0%42.0%44.4%12.3% short
Shot accuracy13.7%9.6%11.9%above
Kill/death ratio1.150.981.03above
Match win rate42.8%43.8%45.2%2.4% short

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

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

Share this profile

CSDB.GGL ミ 0 N 16_11PREMIER14,601 · Blue bandcsdb.gg/stats

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Performance scores

Aim56
Positioning43
Utility31

0–100 skill scores via Leetify.

Recent form

COLD44–50–6Last 10044%Win rateWWLLLTLLLW

Last 10 vs previous 10: −10pp win rate · −0.00 avg rating · −2.2pp headshot accuracy · −66ms reaction

Win rate −10pp 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

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 497ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 521ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 554ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+2.4 against its own average).

Aim5.6
Utility3.1
Positioning4.3
Opening Duels1.1
Clutch6.0

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

iM

Plays most like iM 95% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution; 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. 598ms 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
Positioning4.3
Utility3.1
Mechanics6.5
Opening Duels1.8
Win Impact4.4

Composite 4.4/10 (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 rating-0.02+0.01
first ⅓ avg -0.04 → last ⅓ avg -0.02
Reaction time577ms+31ms
first ⅓ avg 546ms → last ⅓ avg 577ms
Headshot accuracy13.0%−1.9%
first ⅓ avg 14.9% → last ⅓ avg 13.0%

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

0.09Best match rating · 13–3 · ancient, 5 Sept →
36%Best headshot accuracy · 6–13 · inferno, 9 Oct →
359msFastest reaction time · 3–13 · inferno, 2 Oct →
13–1Biggest win · anubis, 27 Sept →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W2Current streak
5–6In matches decided by ≤2 rounds
9Overtime games

Map breakdown

ancientBest map · 65% over 17cacheWeakest map · 20% over 10
MapGradePlayedRecordWin rateAvg rating
anubisB2211–1150%-0.03
dust2B199–1047%-0.03
ancientS1711–665%-0.01
mirageC104–640%-0.03
cacheD102–820%-0.04
infernoC94–544%-0.04
nukeD51–420%-0.06
office—41–325%-0.04
eldorado—10–10%-0.13
train—11–0100%0.01
rush_001—10–10%-0.09
vertigo—10–10%-0.03

Across the last 100 tracked matches.

Lifetime stats

140,047Lifetime kills
1.15K/D · Top 25% of Blue band
6,965Matches
42.8%Match win rate
32.0%Headshot %
13.7%Shot accuracy · Top 50% of Blue band
13,618MVPs
2,076Hours (in match)
3,678Bombs planted
1,132Bombs defused

Most-used weapons

AK-4734,812
AWP15,478
Molotov13,056
P903,206
SG 5532,933

Lifetime map wins

5,951inferno
5,220dust2
2,053cbble
2,049office
1,940train
1,762nuke
1,126lake
1,008vertigo

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

Faceit stats

Combat

22Matches
50%Win rate
0.64Avg K/D
74.0ADR
31%Headshot %

Clutches & streaks

50%1v1 clutch win
50%1v2 clutch win
5Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Nuke3100%1.0713.7
Dust2367%0.8513.0

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.

12.4%Headshot accuracy
31.9%Accuracy (enemy spotted)
35.7%Spray accuracy
79.4%Counter-strafing
9.8°Preaim
598msReaction time
33.5%T opening success
40.6%CT opening success
0.32Enemies flashed / flash
1.4%Flash assists
7.18HE damage / grenade
6.78Flashes / 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 12.4481% — 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 0.3219 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 33.5008% — below the 40% mark we flag

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.

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
inferno6–3-0.039%25 Oct →
mirage13–20.0722%25 Oct →
nuke9–13-0.083%25 Oct →
dust24–13-0.1013%23 Oct →
office3–13-0.0330%23 Oct →
office12–12-0.056%23 Oct →
office11–13-0.0211%22 Oct →
cache5–13-0.096%22 Oct →
anubis11–130.0110%19 Oct →
anubis13–9-0.0318%19 Oct →
cache5–13-0.0717%18 Oct →
dust213–30.0522%18 Oct →
dust28–13-0.0424%18 Oct →
cache8–13-0.0411%18 Oct →
dust213–9-0.0721%17 Oct →
anubis4–13-0.097%17 Oct →
inferno7–13-0.078%17 Oct →
cache7–13-0.0914%17 Oct →
ancient13–90.0317%17 Oct →
cache13–20.089%17 Oct →
ancient13–110.027%17 Oct →
nuke13–80.0317%17 Oct →
dust213–60.0211%17 Oct →
mirage16–120.0110%17 Oct →
dust26–13-0.002%17 Oct →
office13–4-0.0514%15 Oct →
anubis10–13-0.042%15 Oct →
anubis13–11-0.1011%13 Oct →
ancient13–8-0.068%13 Oct →
inferno5–13-0.0125%11 Oct →
anubis13–30.018%11 Oct →
anubis13–110.0316%11 Oct →
inferno13–7-0.0123%11 Oct →
mirage13–80.0313%11 Oct →
ancient5–13-0.0726%9 Oct →
inferno6–13-0.0536%9 Oct →
mirage16–130.0022%9 Oct →
ancient10–13-0.0120%9 Oct →
mirage3–13-0.0216%9 Oct →
ancient13–30.0328%9 Oct →
nuke6–13-0.1030%8 Oct →
anubis15–15-0.063%8 Oct →
mirage1–13-0.1233%4 Oct →
dust26–130.0114%2 Oct →
dust210–13-0.0623%2 Oct →
dust213–7-0.0010%2 Oct →
eldorado2–9-0.130%2 Oct →
anubis11–13-0.0115%2 Oct →
inferno3–13-0.0720%2 Oct →
train13–40.0122%2 Oct →
rush_0013–7-0.090%30 Sept →
nuke5–13-0.0311%28 Sept →
vertigo12–12-0.0323%27 Sept →
anubis13–1-0.0310%27 Sept →
ancient9–13-0.0617%27 Sept →
ancient13–10.022%23 Sept →
anubis16–120.0218%23 Sept →
dust216–13-0.0418%20 Sept →
anubis8–13-0.0520%14 Sept →
dust213–100.018%14 Sept →
anubis14–16-0.0110%12 Sept →
dust210–13-0.039%12 Sept →
ancient13–50.0433%12 Sept →
dust213–11-0.0423%12 Sept →
ancient14–160.0015%12 Sept →
mirage7–13-0.0612%11 Sept →
anubis2–13-0.083%11 Sept →
mirage8–130.0115%11 Sept →
nuke8–8-0.1217%11 Sept →
dust26–13-0.0832%10 Sept →
dust211–13-0.0815%10 Sept →
dust28–13-0.0117%10 Sept →
dust213–40.0419%10 Sept →
ancient6–13-0.0517%10 Sept →
dust215–15-0.0218%8 Sept →
mirage1–13-0.0720%8 Sept →
cache7–13-0.0822%6 Sept →
anubis7–3-0.0211%6 Sept →
ancient13–10-0.0914%6 Sept →
ancient13–70.0211%6 Sept →
cache4–13-0.078%6 Sept →
ancient13–30.0913%5 Sept →
ancient13–8-0.037%5 Sept →
anubis13–8-0.0315%5 Sept →
anubis13–2-0.0318%5 Sept →
anubis13–9-0.0212%4 Sept →
cache13–9-0.0312%4 Sept →
anubis13–6-0.0117%4 Sept →
inferno13–1-0.0219%4 Sept →
anubis5–13-0.089%4 Sept →
cache6–13-0.0110%1 Sept →
dust213–11-0.057%30 Aug →
inferno13–9-0.0612%30 Aug →
ancient15–15-0.039%30 Aug →
inferno10–13-0.0226%29 Aug →
cache10–13-0.0211%29 Aug →
mirage3–13-0.1125%29 Aug →
anubis6–13-0.085%29 Aug →
anubis9–130.0213%29 Aug →
ancient13–9-0.0215%29 Aug →

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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