L3na

L3na — CS2 Stats

76561198262817974[U:1:302552246]Steam profile ↗✓ No bans

787Tracked matches37%Win rate2020Tracked since
CSDB Rating4.0 DevelopingSupport
Premier CS Rating15,936Purple band · top ~24.7% of ranked players (population est.)
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 26 Sep 2026 (5 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: 15,936 -2,373 24 Oct – 26 Sept · 19 days played
15,93623,314peak 23,31424 Oct26 Sept
23,430Peak Premier in tracked matches
41Days played since 2025-10-24

Premier CS Rating

  • 7,378 below peak (23,314)
  • Next: Pink band at 20,000 — 4,064 to go
  • Reached: Pink band · 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.

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CSDB.GGL3naPREMIER15,936 · Purple bandcsdb.gg/stats

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Performance scores

Aim34
Positioning52
Utility68

0–100 skill scores via Leetify.

Recent form

STEADY50–48–2Last 10050%Win rateWLWLLLWLLW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · +6.9pp headshot accuracy · +37ms 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 -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 606ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 16%
  • Avg reaction 648ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 629ms

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 (+2.2 against its own average).

Aim3.4
Utility6.8
Positioning5.2
Opening Duels1.7

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 53% playstyle similarity

Most alike: utility contribution, positioning profile.

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. 638ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% 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

Aim3.4
Positioning5.2
Utility6.8
Mechanics3.4
Opening Duels3.9
Win Impact0.6

Composite 4.0/10 (Developing), 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 rating-0.02−0.03
first ⅓ avg 0.01 → last ⅓ avg -0.02
Reaction time642ms−7ms
first ⅓ avg 649ms → last ⅓ avg 642ms
Headshot accuracy11.9%+1.0%
first ⅓ avg 10.9% → last ⅓ avg 11.9%

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

0.28Best match rating · 9–2 · inferno, 7 May →
35%Best headshot accuracy · 13–4 · inferno, 14 Jan →
422msFastest reaction time · 10–13 · anubis, 22 Sept →
13–1Biggest win · overpass, 3 Dec →

Across the last 100 tracked matches.

Highlights

6Longest win streak
12–9In matches decided by ≤2 rounds
9Overtime games

Map breakdown

dust2Best map · 75% over 8nukeWeakest map · 10% over 10
MapGradePlayedRecordWin rateAvg rating
ancientA2213–959%-0.01
infernoA2011–955%0.01
anubisD113–827%-0.02
nukeD101–910%-0.04
mirageC94–544%-0.03
overpassA95–456%0.02
dust2S86–275%0.01
cacheC52–340%-0.03
train—44–0100%0.01
vertigo—21–150%-0.01

Across the last 100 tracked matches.

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

Skill profile

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

11.8%Headshot accuracy
31.3%Accuracy (enemy spotted)
35.6%Spray accuracy
65.2%Counter-strafing
11.4°Preaim
638msReaction time
50.0%T opening success
40.9%CT opening success
0.65Enemies flashed / flash
12.8%Flash assists
9.20HE damage / grenade
9.88Flashes / 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 11.8355% — below the 15% mark we flag

    Aim Training →
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.

10% 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
dust216–14-0.0210%26 Sept →
mirage11–13-0.0418%26 Sept →
ancient13–7-0.0316%26 Sept →
inferno5–13-0.1025%26 Sept →
mirage10–130.0013%26 Sept →
cache2–13-0.0721%26 Sept →
dust213–110.0319%25 Sept →
anubis14–160.0012%25 Sept →
nuke3–13-0.0517%25 Sept →
cache13–6-0.0212%25 Sept →
dust213–60.0316%24 Sept →
cache13–2-0.044%24 Sept →
vertigo13–60.0517%23 Sept →
anubis10–130.028%22 Sept →
inferno9–13-0.0416%22 Sept →
anubis6–130.016%22 Sept →
ancient16–14-0.017%21 Sept →
anubis7–13-0.065%21 Sept →
nuke13–8-0.038%21 Sept →
cache4–13-0.079%20 Sept →
inferno10–13-0.049%20 Sept →
anubis8–13-0.0312%20 Sept →
inferno4–13-0.033%20 Sept →
anubis2–13-0.037%19 Sept →
inferno13–9-0.0013%19 Sept →
anubis3–13-0.0611%19 Sept →
mirage13–11-0.016%12 Aug →
cache4–130.0318%22 Jul →
overpass11–13-0.0214%14 Jun →
inferno7–13-0.016%14 Jun →
nuke3–13-0.0615%12 Jun →
ancient8–13-0.0310%12 Jun →
anubis4–13-0.0910%24 May →
inferno16–140.0215%24 May →
ancient13–100.028%24 May →
inferno13–90.045%24 May →
anubis13–100.028%14 May →
ancient13–9-0.024%14 May →
mirage9–13-0.0611%10 May →
mirage4–13-0.095%8 May →
ancient13–9-0.057%8 May →
overpass5–130.018%8 May →
mirage10–13-0.075%8 May →
mirage13–60.0413%8 May →
vertigo7–9-0.078%7 May →
nuke4–9-0.1210%7 May →
inferno9–20.2812%7 May →
anubis13–60.047%6 May →
dust213–8-0.032%6 May →
nuke10–13-0.015%6 May →
mirage13–11-0.068%6 May →
ancient13–8-0.029%6 May →
nuke9–13-0.0610%5 May →
ancient5–13-0.004%4 May →
inferno8–130.0325%4 May →
ancient11–13-0.013%3 May →
overpass13–10-0.0213%3 May →
ancient4–13-0.063%25 Apr →
ancient13–100.015%18 Apr →
ancient15–15-0.036%19 Mar →
anubis13–110.0111%15 Feb →
train16–14-0.0114%14 Jan →
inferno13–40.1035%14 Jan →
ancient9–13-0.0328%14 Jan →
dust27–130.029%14 Jan →
inferno7–13-0.0718%11 Dec →
ancient13–6-0.068%11 Dec →
inferno13–4-0.016%10 Dec →
nuke9–130.0319%7 Dec →
ancient13–11-0.0712%7 Dec →
nuke4–13-0.095%6 Dec →
inferno16–130.0014%4 Dec →
ancient15–15-0.0515%4 Dec →
train13–100.038%4 Dec →
inferno5–90.0018%4 Dec →
overpass13–60.0515%3 Dec →
dust213–4-0.0211%3 Dec →
ancient8–13-0.0119%3 Dec →
overpass13–10.1914%3 Dec →
overpass11–13-0.079%9 Nov →
ancient13–90.018%9 Nov →
train13–30.027%9 Nov →
inferno13–110.049%7 Nov →
dust212–16-0.0417%1 Nov →
ancient11–13-0.027%1 Nov →
ancient13–8-0.032%1 Nov →
inferno13–11-0.037%1 Nov →
overpass10–20.035%1 Nov →
nuke11–13-0.027%31 Oct →
ancient13–20.1911%31 Oct →
inferno13–70.0420%31 Oct →
inferno8–13-0.0511%30 Oct →
nuke8–13-0.0211%30 Oct →
ancient13–110.019%29 Oct →
inferno13–80.0513%29 Oct →
overpass13–40.0312%28 Oct →
train13–50.0213%28 Oct →
dust213–60.0910%26 Oct →
mirage13–80.0310%26 Oct →
overpass11–13-0.016%24 Oct →

Match data via Leetify.

Recent teammates

Milestones

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

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