FuriousPenguin

FuriousPenguin — CS2 Stats

76561198204999263[U:1:244733535]Steam profile ↗✓ No bans

1,170Tracked matches36%Win rate2020Tracked since
4,242Hours in CS8Hrs last 2 wks
CSDB Rating4.3 DevelopingAll-Rounder
Premier CS Rating10,241Blue band · top ~53.6% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Oct 2026 (25 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: 10,241 -4,646 14 Jan – 1 Oct · 14 days played
10,24114,887peak 14,88714 Jan1 Oct
14,999Peak Premier in tracked matches
48Days played since 2025-02-22

Premier CS Rating

  • 4,646 below peak (14,887)
  • -441 over 30 days · declining
  • -2,196 over 90 days
  • Next: Purple band at 15,000 — 4,759 to go
  • Reached: Blue band · Light Blue band

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 rate35.9%42.0%44.4%8.4% short
Shot accuracy17.7%9.6%11.9%above
Kill/death ratio0.930.981.030.11 short
Match win rate42.8%43.8%45.2%2.4% short

This profile matches the typical Purple band player on 1 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.GGFuriousPenguinPREMIER10,241 · Blue bandcsdb.gg/stats

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Performance scores

Aim47
Positioning48
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY46–52–2Last 10046%Win rateWLLLLWWLWW

Last 10 vs previous 10: +30pp win rate · −0.01 avg rating · −0.8pp headshot accuracy · +83ms reaction

Win rate up 30pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 11%
  • Avg reaction 692ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 16%
  • Avg reaction 726ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 16%
  • Avg reaction 684ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim4.7
Utility4.6
Positioning4.8
Opening Duels3.5
Clutch4.6

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

m0NESY

Plays most like m0NESY 77% 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. 679ms 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

Aim4.7
Positioning4.8
Utility4.6
Mechanics7.2
Opening Duels3.6
Win Impact0.2

Composite 4.3/10 (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-0.03−0.00
first ⅓ avg -0.03 → last ⅓ avg -0.03
Reaction time676ms−48ms
first ⅓ avg 724ms → last ⅓ avg 676ms
Headshot accuracy19.0%+3.5%
first ⅓ avg 15.5% → last ⅓ avg 19.0%

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

0.13Best match rating · 13–3 · overpass, 29 May →
50%Best headshot accuracy · 0–7 · ancient, 29 Jul →
500msFastest reaction time · 6–13 · inferno, 29 Jun →
13–2Biggest win · inferno, 22 Feb →

Across the last 100 tracked matches.

Highlights

5Longest win streak
9–5In matches decided by ≤2 rounds
11Overtime games

Map breakdown

nukeBest map · 57% over 21ancientWeakest map · 39% over 23
MapGradePlayedRecordWin rateAvg rating
ancientC239–1439%-0.04
infernoC2310–1343%-0.03
nukeA2112–957%-0.02
anubisB126–650%-0.05
overpassB126–650%-0.01
cache—31–233%-0.02
vertigo—31–233%-0.03
mirage—21–150%-0.05
dust2—10–10%0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (39% over 23). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

71,754Lifetime kills
0.93K/D
4,496Matches
42.8%Match win rate
35.9%Headshot %
17.7%Shot accuracy · Top 10% of Blue band
8,286MVPs
1,951Hours (in match)
5,549Bombs planted
1,095Bombs defused

Most-used weapons

AK-4719,602
AWP9,123
SG 5533,306
MAC-102,548
AUG2,410
MP91,883
P901,472

Lifetime map wins

10,425inferno
5,661nuke
3,518dust2
2,793vertigo
1,226cbble
872train
285lake
274assault

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

Faceit stats

Combat

740Matches
50%Win rate
0.83Avg K/D
61.2ADR
38%Headshot %

Clutches & streaks

43%1v1 clutch win
13%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno5659%0.8912.0
Ancient4441%0.7811.3
Nuke4058%0.8110.7
Vertigo3348%0.8112.0
Overpass978%0.8713.0
Mirage862%0.629.5
Anubis633%0.6512.5
Dust2333%0.9416.3

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.

17.9%Headshot accuracy
29.0%Accuracy (enemy spotted)
32.4%Spray accuracy
82.4%Counter-strafing
10.8°Preaim
679msReaction time
40.2%T opening success
48.8%CT opening success
0.50Enemies flashed / flash
3.0%Flash assists
12.58HE damage / grenade
4.62Flashes / 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. 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 0.4954 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Ancient

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

39% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–4-0.0113%19 Oct →
ancient8–13-0.1216%1 Oct →
inferno5–13-0.044%1 Oct →
inferno14–16-0.077%24 Sept →
nuke6–130.0415%2 Sept →
nuke13–40.0024%31 Aug →
nuke16–12-0.0213%31 Aug →
ancient10–13-0.0429%26 Aug →
nuke13–9-0.0028%26 Aug →
inferno13–11-0.067%26 Aug →
nuke11–130.0411%25 Aug →
nuke10–13-0.0311%24 Aug →
nuke13–9-0.0333%22 Aug →
cache9–130.0419%22 Aug →
inferno6–13-0.0222%21 Aug →
nuke10–13-0.0320%11 Aug →
cache3–13-0.089%11 Aug →
anubis13–10-0.0611%11 Aug →
dust26–130.0017%11 Aug →
anubis10–13-0.0211%11 Aug →
ancient13–100.0129%11 Aug →
anubis15–150.0318%10 Aug →
ancient5–13-0.0835%10 Aug →
inferno15–15-0.0817%4 Aug →
inferno3–13-0.1325%4 Aug →
inferno3–13-0.0345%4 Aug →
ancient13–3-0.0713%4 Aug →
inferno13–9-0.0413%29 Jul →
ancient0–7-0.0750%29 Jul →
inferno9–13-0.078%29 Jul →
nuke13–50.0526%29 Jul →
inferno13–80.0320%1 Jul →
overpass13–4-0.019%1 Jul →
ancient13–16-0.0215%29 Jun →
inferno6–13-0.0215%29 Jun →
nuke16–14-0.0812%28 Jun →
nuke6–13-0.1018%28 Jun →
anubis13–10-0.078%28 Jun →
ancient6–13-0.0126%18 Jun →
ancient13–10-0.0221%18 Jun →
overpass4–13-0.1310%16 Jun →
ancient16–14-0.0021%16 Jun →
inferno11–13-0.0117%13 Jun →
overpass11–13-0.0115%13 Jun →
nuke7–13-0.0820%30 May →
ancient13–60.0218%30 May →
inferno6–13-0.055%29 May →
anubis13–10-0.074%29 May →
overpass13–30.1319%29 May →
ancient9–13-0.0610%28 May →
overpass13–110.066%4 May →
anubis7–13-0.044%4 May →
nuke13–3-0.0417%4 May →
anubis16–13-0.0216%3 May →
anubis13–11-0.048%3 May →
ancient5–130.0012%3 May →
nuke13–4-0.0223%2 May →
inferno2–13-0.039%2 May →
anubis16–14-0.0219%25 Apr →
overpass13–9-0.0413%8 Apr →
anubis4–13-0.1117%8 Apr →
overpass7–13-0.0426%7 Apr →
nuke11–13-0.043%7 Apr →
inferno13–100.0328%7 Apr →
nuke13–11-0.087%10 Mar →
ancient7–13-0.0515%10 Mar →
anubis9–13-0.0914%9 Mar →
inferno7–13-0.0314%9 Mar →
ancient9–13-0.0325%1 Mar →
nuke8–13-0.043%11 Feb →
anubis9–13-0.0513%30 Jan →
nuke13–10-0.0213%29 Jan →
ancient6–13-0.1019%29 Jan →
overpass5–13-0.0518%26 Jan →
ancient13–8-0.027%26 Jan →
overpass5–13-0.0527%14 Jan →
inferno13–10-0.0216%14 Jan →
ancient13–8-0.0429%14 Jan →
nuke13–6-0.0330%14 Jan →
ancient13–16-0.059%10 Jan →
nuke8–130.0514%10 Jan →
nuke13–50.0719%10 Jan →
inferno13–6-0.014%9 Jan →
ancient13–7-0.0227%9 Jan →
overpass13–50.0310%9 Jan →
inferno13–10-0.0715%9 Jan →
inferno10–13-0.0310%7 Jan →
overpass10–13-0.0417%7 Jan →
mirage13–11-0.0614%5 Jan →
mirage9–13-0.0520%5 Jan →
vertigo3–13-0.0821%26 Oct →
vertigo3–13-0.0112%26 Oct →
inferno13–30.0017%12 Oct →
overpass13–50.0317%12 Oct →
ancient4–13-0.104%18 Jun →
inferno16–14-0.0312%17 Jun →
ancient13–10-0.0219%3 May →
ancient9–13-0.088%9 Apr →
vertigo13–7-0.0119%22 Feb →
inferno13–20.0114%22 Feb →

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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