Llama

Llama — CS2 Stats

76561198045686713[U:1:85420985]Steam profile ↗✓ No bans

1,267Tracked matches41%Win rate2020Tracked since
CSDB Rating4.4 DevelopingSupport
Premier CS Rating16,191Purple band · top ~23.7% of ranked players (population est.)
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 2026 (2 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: 16,191 -2,974 28 Jun – 30 Oct · 13 days played
14,83419,165peak 19,16528 Jun30 Oct
19,388Peak Premier in tracked matches
42Days played since 2026-06-28

Premier CS Rating

  • 2,974 below peak (19,165)
  • +433 over 30 days · improving
  • Next: Pink band at 20,000 — 3,809 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-09-22
  • Light Blue band first seen 2026-09-22

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

Share this profile

CSDB.GGLlamaPREMIER16,191 · Purple bandcsdb.gg/stats

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Performance scores

Aim66
Positioning32
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY39–56–5Last 10039%Win rateWWLLWWLWLL

Last 10 vs previous 10: +20pp win rate · −0.01 avg rating · +0.5pp headshot accuracy · +59ms reaction

Win rate up 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 (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 9%
  • Avg reaction 608ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 10%
  • Avg reaction 610ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 580ms

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 (+1.5 against its own average).

Aim6.6
Utility3.8
Positioning3.2
Opening Duels0.0

Limited utility dependence

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

ropz

Plays most like ropz 92% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower positioning profile; lower opening-duel success.

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

Positioning. Positioning trails aim by 33 points — deaths here waste a strong aim profile.

Reaction time. 560ms 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

Aim6.6
Positioning3.2
Utility3.8
Mechanics5.7
Opening Duels1.3
Win Impact2.1

Composite 4.4/10 (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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time565ms−26ms
first ⅓ avg 591ms → last ⅓ avg 565ms
Headshot accuracy10.4%−0.8%
first ⅓ avg 11.3% → last ⅓ avg 10.4%

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

0.15Best match rating · 13–2 · mirage, 28 Jul →
38%Best headshot accuracy · 0–13 · dust2, 24 Sept →
391msFastest reaction time · 13–8 · anubis, 17 Oct →
13–2Biggest win · mirage, 28 Jul →

Across the last 100 tracked matches.

Highlights

7Longest win streak
W2Current streak
5–2In matches decided by ≤2 rounds
4Overtime games

Map breakdown

anubisBest map · 100% over 5infernoWeakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
dust2D309–2130%-0.03
mirageC187–1139%-0.01
cacheC176–1135%-0.01
infernoD122–1017%-0.03
overpassS54–180%0.01
nukeA53–260%-0.01
anubisS55–0100%-0.01
ancient—31–233%-0.07
train—21–150%-0.05
office—10–10%-0.05
vertigo—10–10%-0.03
fachwerk—11–0100%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6Matches
50%Win rate
0.62Avg K/D
—ADR
26%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
3Longest win streak

Recent Faceit resultsWWLLL

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.

9.3%Headshot accuracy
36.3%Accuracy (enemy spotted)
41.3%Spray accuracy
75.4%Counter-strafing
9.1°Preaim
560msReaction time
39.4%T opening success
30.7%CT opening success
0.43Enemies flashed / flash
0.9%Flash assists
9.21HE damage / grenade
4.75Flashes / 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 9.2788% — 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 0.4251 — 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 39.3644% — below the 40% mark we flag

Spend your practice time on Inferno

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 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
overpass13–10-0.0510%31 Oct →
inferno13–6-0.045%31 Oct →
inferno5–13-0.0110%30 Oct →
dust26–13-0.0714%28 Oct →
nuke9–9-0.029%28 Oct →
train13–8-0.0212%28 Oct →
mirage3–13-0.0325%27 Oct →
mirage13–8-0.0215%24 Oct →
cache4–13-0.100%24 Oct →
inferno5–13-0.032%24 Oct →
mirage7–13-0.078%24 Oct →
cache6–130.0310%22 Oct →
dust21–13-0.0918%22 Oct →
mirage6–13-0.0912%22 Oct →
dust29–13-0.1211%21 Oct →
cache7–13-0.013%21 Oct →
mirage13–60.048%19 Oct →
dust28–13-0.0113%19 Oct →
overpass13–70.0112%17 Oct →
cache13–40.033%17 Oct →
dust213–40.0611%17 Oct →
cache6–13-0.0412%17 Oct →
anubis13–8-0.057%17 Oct →
inferno10–13-0.047%3 Oct →
anubis13–80.0111%2 Oct →
dust211–13-0.0510%2 Oct →
anubis13–8-0.059%2 Oct →
office5–13-0.050%2 Oct →
train12–12-0.085%2 Oct →
vertigo8–13-0.0310%25 Sept →
overpass13–110.1113%24 Sept →
dust20–13-0.0938%24 Sept →
cache8–13-0.0112%23 Sept →
dust213–4-0.0214%23 Sept →
cache13–100.0018%23 Sept →
mirage13–6-0.0113%22 Sept →
dust212–120.0318%22 Sept →
cache10–13-0.055%21 Sept →
inferno11–13-0.0410%21 Sept →
ancient1–13-0.1112%20 Sept →
anubis13–6-0.016%19 Sept →
inferno3–13-0.063%19 Sept →
dust22–13-0.1215%19 Sept →
mirage5–130.0511%19 Sept →
anubis13–90.048%18 Sept →
dust216–120.0123%16 Sept →
cache13–90.047%16 Sept →
nuke13–30.0511%15 Sept →
ancient13–11-0.0611%15 Sept →
dust213–9-0.0014%15 Sept →
cache13–50.035%14 Sept →
dust212–160.0112%13 Sept →
mirage6–13-0.058%13 Sept →
mirage13–50.0110%13 Sept →
inferno13–4-0.039%11 Sept →
mirage12–120.0311%11 Sept →
mirage13–100.0112%8 Sept →
dust29–13-0.029%7 Sept →
nuke6–13-0.0510%7 Sept →
mirage3–13-0.085%7 Sept →
mirage13–8-0.007%7 Sept →
inferno7–13-0.032%7 Sept →
nuke13–80.0312%7 Sept →
dust27–130.0110%7 Sept →
inferno10–130.0011%31 Aug →
ancient5–13-0.0410%31 Aug →
cache10–13-0.0514%20 Aug →
dust212–12-0.037%17 Aug →
inferno7–13-0.056%16 Aug →
mirage6–13-0.0812%16 Aug →
mirage9–13-0.065%15 Aug →
dust24–13-0.0811%15 Aug →
nuke15–15-0.058%15 Aug →
dust216–14-0.0316%15 Aug →
cache10–1-0.0114%15 Aug →
cache6–130.0120%15 Aug →
dust213–80.008%11 Aug →
dust213–5-0.0613%11 Aug →
inferno9–13-0.0310%9 Aug →
inferno1–13-0.037%9 Aug →
dust24–13-0.063%9 Aug →
dust28–13-0.0213%9 Aug →
dust29–13-0.057%9 Aug →
dust23–13-0.0413%7 Aug →
mirage5–130.0317%28 Jul →
overpass13–70.0116%28 Jul →
mirage13–20.1516%28 Jul →
dust213–8-0.0014%19 Jul →
cache8–13-0.0110%18 Jul →
dust213–20.0512%18 Jul →
dust210–13-0.0114%17 Jul →
cache7–13-0.0415%11 Jul →
fachwerk13–11-0.055%11 Jul →
cache9–13-0.0218%11 Jul →
overpass6–13-0.0313%10 Jul →
cache13–10-0.008%10 Jul →
dust29–13-0.085%5 Jul →
mirage4–13-0.0213%5 Jul →
dust28–13-0.0711%28 Jun →
dust26–13-0.0417%28 Jun →

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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