anolbeeds gugu

anolbeeds gugu — CS2 Stats

76561198167559622[U:1:207293894]Steam profile ↗✓ No bans

928Tracked matches55%Win rate2020Tracked since
CSDB Rating3.6 LearningSupport
Premier CS Rating16,518Purple band · top ~22.4% of ranked players (population est.)
FaceitLevel 2 · 598 ELOTop 97.9% of ranked FACEIT players
WingmanGold Nova III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 28 Sep 2026 (6 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: 16,518 +6,951 30 Dec – 28 Sept · 33 days played
8,04116,518peak 16,51830 Dec28 Sept
16,518Peak Premier in tracked matches
598Highest Faceit ELO seen on CSDB
49Days played since 2025-12-30

Faceit ELO

  • At peak — 598
  • Next: Level 3 at 751 — 153 to go
  • Reached: Level 2

Premier CS Rating

  • At peak — 16,518
  • Next: Pink band at 20,000 — 3,482 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.

Share this profile

CSDB.GGanolbeeds guguFACEITLevel 2 · 598 ELOSTANDINGTop 97.9% of rankedPREMIER16,518 · Purple bandPEAK ELO598csdb.gg/stats

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Performance scores

Aim33
Positioning38
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY46–52–2Last 10046%Win rateWWLLWLWLWL

Last 10 vs previous 10: −20pp win rate · −0.02 avg rating · −1.7pp headshot accuracy · −63ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 601ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 16%
  • Avg reaction 632ms

Last 20

  • 12–7–1 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 663ms

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 (+1.4 against its own average).

Aim3.3
Utility4.3
Positioning3.8
Opening Duels0.7
Clutch2.8

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

NiKo

Plays most like NiKo 69% 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. 636ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 63% 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

Aim3.3
Positioning3.8
Utility4.3
Mechanics2.8
Opening Duels0.9
Win Impact6.7

Composite 3.6/10 (Learning), 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+0.00
first ⅓ avg -0.03 → last ⅓ avg -0.03
Reaction time655ms−60ms
first ⅓ avg 715ms → last ⅓ avg 655ms
Headshot accuracy16.7%−1.5%
first ⅓ avg 18.2% → last ⅓ avg 16.7%

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

0.08Best match rating · 13–7 · mirage, 12 Feb →
42%Best headshot accuracy · 11–13 · mirage, 9 Feb →
453msFastest reaction time · 3–13 · nuke, 10 Jan →
13–2Biggest win · anubis, 12 Mar →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
6–10In matches decided by ≤2 rounds
10Overtime games

Map breakdown

ancientBest map · 63% over 8infernoWeakest map · 31% over 13
MapGradePlayedRecordWin rateAvg rating
dust2B2312–1152%-0.03
mirageA169–756%-0.02
anubisC145–936%-0.04
infernoD134–931%-0.02
nukeB105–550%-0.02
ancientA85–363%-0.03
overpassB84–450%-0.01
vertigo—31–233%-0.11
cache—10–10%0.01
poseidon—11–0100%-0.08
debris—10–10%-0.15
warden—10–10%0.02
train—10–10%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

485Matches
49%Win rate
0.88Avg K/D
67.5ADR
43%Headshot %

Clutches & streaks

34%1v1 clutch win
19%1v2 clutch win
5Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage3653%0.9411.9
Vertigo3358%0.8612.2
Inferno3238%0.6310.6
Ancient2662%0.8213.0
Anubis2343%0.8312.5
Nuke2255%0.7311.9
Dust21527%0.6111.7
Overpass1354%0.7412.6

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.

16.3%Headshot accuracy
29.9%Accuracy (enemy spotted)
31.8%Spray accuracy
62.6%Counter-strafing
11.3°Preaim
636msReaction time
28.7%T opening success
37.6%CT opening success
0.51Enemies flashed / flash
6.0%Flash assists
6.35HE damage / grenade
4.78Flashes / 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. 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 28.661% — 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.

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke16–12-0.0216%28 Sept →
ancient13–9-0.0310%28 Sept →
mirage10–13-0.0018%23 Sept →
cache8–130.0111%23 Sept →
ancient13–5-0.059%20 Sept →
mirage9–13-0.0511%20 Sept →
vertigo9–2-0.0124%12 Aug →
vertigo2–9-0.2115%12 Aug →
poseidon9–6-0.0829%12 Aug →
mirage4–13-0.0416%12 Aug →
dust213–9-0.1020%12 Aug →
anubis13–7-0.0115%7 Aug →
inferno15–150.0120%7 Aug →
dust213–7-0.0723%7 Aug →
inferno13–5-0.067%7 Aug →
debris7–9-0.1515%5 Aug →
dust25–4-0.0015%5 Aug →
nuke13–110.0426%5 Aug →
anubis13–50.0211%9 Jun →
warden11–130.0221%20 May →
inferno7–130.0213%11 May →
anubis13–16-0.0413%4 May →
anubis7–13-0.076%22 Apr →
nuke13–10-0.0128%22 Apr →
dust211–13-0.0319%22 Apr →
mirage13–8-0.0423%21 Apr →
dust213–50.0330%21 Apr →
mirage13–3-0.087%21 Apr →
dust213–7-0.0213%21 Apr →
overpass11–13-0.059%20 Apr →
inferno10–13-0.0319%18 Apr →
dust213–50.0024%18 Apr →
inferno11–130.0116%16 Apr →
dust26–13-0.0115%16 Apr →
anubis11–13-0.0524%16 Apr →
overpass13–80.0011%14 Apr →
nuke7–13-0.0023%14 Apr →
dust213–100.0525%14 Apr →
overpass13–160.0426%13 Apr →
ancient9–13-0.0319%11 Apr →
overpass13–3-0.1010%8 Apr →
inferno10–13-0.0526%1 Apr →
ancient13–11-0.0812%30 Mar →
dust27–13-0.0610%29 Mar →
anubis13–11-0.0414%29 Mar →
inferno13–10-0.025%29 Mar →
overpass8–13-0.0214%29 Mar →
anubis6–13-0.0612%26 Mar →
mirage13–5-0.0225%25 Mar →
dust213–50.0114%25 Mar →
nuke13–8-0.0216%25 Mar →
mirage13–11-0.0121%25 Mar →
nuke12–16-0.0217%24 Mar →
dust213–100.0213%23 Mar →
dust210–13-0.0814%22 Mar →
inferno9–13-0.0923%22 Mar →
dust210–13-0.0614%22 Mar →
mirage16–13-0.0614%22 Mar →
overpass13–50.0517%20 Mar →
inferno11–13-0.0416%18 Mar →
dust213–90.0015%18 Mar →
dust213–100.0521%17 Mar →
dust213–16-0.0813%16 Mar →
inferno13–80.0320%16 Mar →
ancient3–13-0.0513%16 Mar →
anubis9–13-0.0528%15 Mar →
dust213–5-0.0417%15 Mar →
nuke13–9-0.0125%15 Mar →
mirage16–120.0219%15 Mar →
nuke11–13-0.0630%12 Mar →
anubis13–2-0.0024%12 Mar →
anubis11–13-0.0429%11 Mar →
dust28–13-0.0815%11 Mar →
overpass13–11-0.018%2 Mar →
anubis5–13-0.0514%2 Mar →
dust25–13-0.125%18 Feb →
anubis6–13-0.096%18 Feb →
anubis8–130.0020%13 Feb →
mirage13–70.0838%12 Feb →
dust215–15-0.0317%11 Feb →
mirage13–3-0.0114%11 Feb →
overpass5–13-0.0323%9 Feb →
mirage11–13-0.0242%9 Feb →
anubis13–10-0.0215%28 Jan →
inferno9–13-0.0519%18 Jan →
inferno4–13-0.026%10 Jan →
ancient13–8-0.053%10 Jan →
mirage7–13-0.0321%10 Jan →
nuke3–13-0.1024%10 Jan →
mirage6–13-0.0925%10 Jan →
ancient13–90.066%8 Jan →
mirage13–50.0624%6 Jan →
inferno4–00.0017%4 Jan →
nuke12–16-0.0116%2 Jan →
train9–13-0.0514%2 Jan →
ancient8–13-0.0525%31 Dec →
mirage5–13-0.076%31 Dec →
vertigo3–9-0.1113%30 Dec →
dust26–13-0.0522%30 Dec →
dust24–13-0.1218%30 Dec →

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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