󠁳⁧⁧ LaLa

󠁳⁧⁧ LaLa — CS2 Stats

SE76561199467004493[U:1:1506738765]Steam profile ↗✓ No bans

790Tracked matches60%Win rate2023Tracked since
CSDB Rating6.0 SolidPositional Player
Premier CS Rating21,390Top 50% of 205,416 CSDB-tracked playersPink band · top ~7% of ranked players (population est.)
CSDB Leaderboard#62857 of 252698 tracked
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Oct 2026 (yesterday). Ranks are recorded once per day this page is viewed.

+983Premier CS Rating · 20,407 → 21,390

Rating over time

Premier CS Rating: 21,390 -114 5 Sept – 17 Oct · 7 days played
20,00021,504peak 21,5045 Sept17 Oct
21,504Peak Premier in tracked matches
31Days played since 2026-09-04

Premier CS Rating

  • 114 below peak (21,504)
  • +1,264 over 30 days · improving
  • Next: Red band at 25,000 — 3,610 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-09-07
  • Purple band first seen 2026-09-07

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GG󠁳⁧⁧ LaLaPREMIER21,390 · Pink bandcsdb.gg/stats

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Performance scores

Aim68
Positioning54
Utility53

0–100 skill scores via Leetify.

Recent form

HOT55–41–4Last 10055%Win rateWWWLWWWTWW

Last 10 vs previous 10: +10pp win rate · +0.05 avg rating · +2.0pp headshot accuracy · +6ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 15%
  • Avg reaction 556ms

Last 10

  • 8–1–1 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 539ms

Last 20

  • 15–4–1 · 75% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 536ms

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 against its own average).

Aim6.8
Utility5.3
Positioning5.4
Opening Duels2.6

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 91% playstyle similarity

Most alike: positioning profile, opening-duel success.

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

T-side openings. Opening success drops from 53% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim6.8
Positioning5.4
Utility5.3
Mechanics5.6
Opening Duels2.8
Win Impact8.3

Composite 6.0/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.01
first ⅓ avg 0.00 → last ⅓ avg 0.01
Reaction time558ms+32ms
first ⅓ avg 526ms → last ⅓ avg 558ms
Headshot accuracy16.4%+3.3%
first ⅓ avg 13.1% → last ⅓ avg 16.4%

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 · 9–1 · vertigo, 12 Oct →
36%Best headshot accuracy · 8–8 · inferno, 12 Oct →
344msFastest reaction time · 9–0 · inferno, 7 Oct →
13–2Biggest win · anubis, 12 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W3Current streak
9–3In matches decided by ≤2 rounds
16Overtime games

Map breakdown

vertigoBest map · 75% over 8nukeWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2C188–1044%-0.00
infernoB178–947%0.01
anubisA1610–663%-0.00
ancientA149–564%-0.00
cacheS107–370%0.01
mirageC83–538%0.02
vertigoS86–275%0.07
nukeD61–517%-0.05
train—33–0100%0.09

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (17% over 6). 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.

15.8%Headshot accuracy
32.2%Accuracy (enemy spotted)
35.1%Spray accuracy
75.1%Counter-strafing
8.3°Preaim
535msReaction time
30.0%T opening success
52.6%CT opening success
0.65Enemies flashed / flash
6.0%Flash assists
6.88HE damage / grenade
5.98Flashes / 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 30.026% — 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.

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

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–3-0.0111%17 Oct →
mirage13–110.0418%17 Oct →
ancient13–110.0215%17 Oct →
dust29–130.0115%16 Oct →
cache13–50.0714%16 Oct →
mirage13–60.1131%16 Oct →
anubis13–70.0113%16 Oct →
vertigo8–8-0.0010%16 Oct →
cache13–70.0120%15 Oct →
inferno9–60.088%15 Oct →
nuke8–13-0.0813%15 Oct →
mirage19–160.029%15 Oct →
inferno13–6-0.0113%15 Oct →
nuke13–7-0.018%15 Oct →
dust217–19-0.0020%15 Oct →
cache13–80.0113%14 Oct →
inferno13–100.0312%12 Oct →
anubis13–2-0.0611%12 Oct →
inferno8–13-0.0621%12 Oct →
dust213–70.0117%12 Oct →
vertigo9–50.1519%12 Oct →
inferno8–80.0536%12 Oct →
vertigo9–10.1926%12 Oct →
nuke6–9-0.0617%11 Oct →
inferno9–5-0.0413%11 Oct →
vertigo13–90.0018%11 Oct →
cache8–13-0.0117%11 Oct →
dust29–130.0417%11 Oct →
nuke6–13-0.0315%10 Oct →
anubis13–8-0.039%10 Oct →
mirage4–130.0126%10 Oct →
dust24–13-0.0718%9 Oct →
dust213–90.0020%9 Oct →
mirage11–130.0015%8 Oct →
ancient13–10-0.0216%8 Oct →
inferno9–40.0922%8 Oct →
vertigo9–50.1513%7 Oct →
inferno8–8-0.0122%7 Oct →
inferno8–80.0118%7 Oct →
inferno9–00.1720%7 Oct →
dust27–130.0417%6 Oct →
anubis10–13-0.0115%6 Oct →
cache16–120.0815%6 Oct →
ancient13–50.039%5 Oct →
dust212–160.0418%5 Oct →
cache3–130.0318%4 Oct →
inferno7–130.0219%4 Oct →
inferno25–21-0.0310%3 Oct →
mirage12–160.0214%3 Oct →
anubis19–17-0.0215%3 Oct →
train13–80.0922%3 Oct →
ancient13–30.057%3 Oct →
cache13–40.087%1 Oct →
dust28–13-0.0316%1 Oct →
anubis5–13-0.0520%1 Oct →
ancient7–13-0.0417%1 Oct →
ancient9–13-0.0420%30 Sept →
dust213–30.019%30 Sept →
cache2–13-0.1013%30 Sept →
ancient13–8-0.007%29 Sept →
anubis16–140.0115%29 Sept →
nuke6–13-0.063%29 Sept →
dust216–13-0.0112%29 Sept →
ancient13–11-0.0412%28 Sept →
inferno19–160.0112%28 Sept →
anubis13–7-0.064%27 Sept →
ancient9–13-0.0613%27 Sept →
dust214–16-0.0415%27 Sept →
vertigo13–90.0818%26 Sept →
ancient12–16-0.003%26 Sept →
dust213–5-0.0312%25 Sept →
vertigo19–220.0011%25 Sept →
dust213–110.0317%25 Sept →
anubis13–60.0511%25 Sept →
ancient9–13-0.0212%25 Sept →
anubis9–130.0314%25 Sept →
mirage8–13-0.0111%25 Sept →
dust213–10-0.045%24 Sept →
mirage8–13-0.0210%24 Sept →
cache13–11-0.0013%23 Sept →
dust210–10.1313%23 Sept →
train13–40.0614%23 Sept →
anubis10–130.038%23 Sept →
anubis10–13-0.027%22 Sept →
inferno5–9-0.0920%22 Sept →
vertigo13–9-0.053%21 Sept →
cache13–9-0.0514%21 Sept →
ancient13–110.0416%21 Sept →
inferno13–16-0.0011%21 Sept →
train13–30.1117%20 Sept →
dust26–13-0.0613%20 Sept →
anubis13–60.0419%11 Sept →
ancient13–110.0410%11 Sept →
anubis22–180.0313%7 Sept →
inferno7–13-0.0526%7 Sept →
inferno10–13-0.0533%7 Sept →
anubis6–130.0110%6 Sept →
dust212–16-0.0616%5 Sept →
nuke3–13-0.068%5 Sept →
anubis13–90.0111%4 Sept →

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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