FENTPEEK クッキー

FENTPEEK クッキー — CS2 Stats

FI76561199053269626[U:1:1093003898]Steam profile ↗✓ No bans

208Tracked matches66%Win rate2023Tracked since
367Hours in CS13Hrs last 2 wks
CSDB Rating7.2 StrongPositional Player
Premier CS Rating17,987Purple band · top ~16.5% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 28 Oct 2026 (7 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: 17,987 +4,917 11 Jan – 28 Oct · 27 days played
13,07017,987peak 17,98711 Jan28 Oct
18,280Peak Premier in tracked matches
1,059Highest Faceit ELO seen on CSDB
45Days played since 2026-01-11

Faceit ELO

  • At peak — 1,059
  • Next: Level 6 at 1,201 — 142 to go
  • Reached: Level 5 · Level 4 · Level 3 · Level 2

Premier CS Rating

  • At peak — 17,987
  • Next: Pink band at 20,000 — 2,013 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.

How this compares with the same rank

Median values for Purple band among CSDB-tracked players (n=37,767), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate54.6%44.4%46.9%above
Shot accuracy6.4%11.9%13.0%6.6% short
Kill/death ratio0.941.031.080.14 short
Match win rate44.7%45.2%46.7%1.9% short

This profile matches the typical Pink band player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGFENTPEEK クッキーPREMIER17,987 · Purple bandPEAK ELO1,059csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim72
Positioning68
Utility57

0–100 skill scores via Leetify.

Recent form

STEADY47–50–3Last 10047%Win rateLWWWLWWWWL

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · +1.6pp headshot accuracy · +41ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 28%
  • Avg reaction 623ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 25%
  • Avg reaction 623ms

Last 20

  • 15–4–1 · 75% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 24%
  • Avg reaction 602ms

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 (+1.7 against its own average).

Aim7.2
Utility5.7
Positioning6.8
Opening Duels3.3
Clutch4.6

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

Twistzz

Plays most like Twistzz 86% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Strengths

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 61% on CT to 46% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 609ms 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

Aim7.2
Positioning6.8
Utility5.7
Mechanics8.0
Opening Duels6.0
Win Impact10.0

Composite 7.2/10 (Strong), 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-0.01−0.00
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time617ms−14ms
first ⅓ avg 630ms → last ⅓ avg 617ms
Headshot accuracy25.7%−0.1%
first ⅓ avg 25.8% → last ⅓ avg 25.7%

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

0.11Best match rating · 13–5 · ancient, 25 Oct →
50%Best headshot accuracy · 9–0 · inferno, 5 Sept →
406msFastest reaction time · 13–11 · dust2, 23 Oct →
13–1Biggest win · anubis, 24 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–7In matches decided by ≤2 rounds
6Overtime games

Map breakdown

nukeBest map · 72% over 18infernoWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
mirageD2910–1934%-0.00
nukeS1813–572%0.01
dust2B157–847%-0.01
ancientC146–843%0.00
infernoD93–633%-0.05
anubisS64–267%-0.01
overpassD62–433%-0.01
cache—32–167%0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

8,435Lifetime kills
0.94K/D
561Matches
44.7%Match win rate
54.6%Headshot % · Top 25% of Purple band
6.4%Shot accuracy
1,253MVPs
195Hours (in match)
440Bombs planted
130Bombs defused

Most-used weapons

Lifetime map wins

887nuke
623inferno
444vertigo
371dust2
79train
78lake
5cbble

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

Faceit stats

Combat

52Matches
60%Win rate
1.00Avg K/D
76.8ADR
57%Headshot %

Clutches & streaks

43%1v1 clutch win
27%1v2 clutch win
5Longest win streak

Recent Faceit resultsLWWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage1567%1.0515.5
Ancient978%0.9714.6
Nuke850%0.8217.0
Dust2650%0.9916.8
Anubis667%1.2417.0
Inferno425%0.7814.3
Cache250%1.2419.0
Vertigo250%1.0614.0

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.

24.1%Headshot accuracy
33.7%Accuracy (enemy spotted)
32.4%Spray accuracy
85.8%Counter-strafing
10.9°Preaim
609msReaction time
46.4%T opening success
61.4%CT opening success
0.66Enemies flashed / flash
10.1%Flash assists
9.70HE damage / grenade
10.15Flashes / match

Recommended for you

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.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke7–13-0.0126%28 Oct →
ancient13–7-0.0021%28 Oct →
dust213–30.1041%28 Oct →
nuke13–80.0022%26 Oct →
dust27–13-0.0228%25 Oct →
dust213–20.0420%25 Oct →
ancient13–50.1125%25 Oct →
ancient13–4-0.0122%25 Oct →
mirage13–60.0220%25 Oct →
nuke11–13-0.0326%25 Oct →
cache13–30.0632%25 Oct →
ancient13–100.0423%25 Oct →
mirage13–16-0.0516%25 Oct →
nuke13–5-0.0321%24 Oct →
mirage15–15-0.0338%24 Oct →
anubis13–10.0318%24 Oct →
dust213–11-0.0426%23 Oct →
mirage13–50.0726%23 Oct →
cache13–11-0.0125%23 Oct →
inferno12–30.019%12 Oct →
dust21–13-0.0936%10 Oct →
cache6–13-0.0425%10 Oct →
dust213–110.0125%2 Oct →
nuke13–9-0.0115%2 Oct →
nuke13–90.1029%12 Sept →
mirage1–13-0.0319%11 Sept →
inferno1–9-0.1742%11 Sept →
nuke10–13-0.0624%6 Sept →
ancient3–13-0.0626%6 Sept →
inferno8–8-0.0438%6 Sept →
inferno9–0-0.0050%5 Sept →
nuke13–80.0119%3 Sept →
mirage8–13-0.0415%3 Sept →
mirage13–6-0.0121%3 Sept →
inferno8–8-0.1033%2 Sept →
dust23–13-0.0512%15 Aug →
mirage3–90.0928%16 Jun →
ancient6–13-0.0531%9 Jun →
ancient13–50.0724%9 Jun →
nuke13–70.0330%9 Jun →
dust213–8-0.0429%8 Jun →
mirage11–130.0035%22 May →
nuke13–70.0224%21 May →
mirage8–13-0.0227%21 May →
inferno13–16-0.0335%21 May →
nuke13–10-0.0021%12 May →
dust21–13-0.0231%29 Apr →
mirage8–13-0.0028%29 Apr →
dust29–130.0021%18 Apr →
anubis8–13-0.0527%16 Apr →
dust213–110.0617%16 Apr →
anubis13–50.0723%16 Apr →
dust211–13-0.0326%16 Apr →
nuke4–13-0.0729%11 Apr →
dust20–13-0.0535%11 Apr →
mirage9–13-0.0327%8 Apr →
inferno9–13-0.0738%6 Apr →
ancient6–13-0.0521%6 Apr →
mirage13–8-0.0215%6 Apr →
mirage8–130.0431%30 Mar →
ancient6–13-0.0526%28 Mar →
ancient6–130.0420%26 Mar →
mirage13–90.0725%24 Mar →
overpass7–13-0.0126%24 Mar →
overpass8–13-0.0519%22 Mar →
nuke13–90.0834%22 Mar →
mirage8–13-0.0329%22 Mar →
mirage11–130.0040%3 Mar →
ancient11–13-0.0323%3 Mar →
inferno13–30.0221%28 Feb →
mirage13–10.0629%22 Feb →
ancient11–130.0234%22 Feb →
mirage5–13-0.0316%22 Feb →
mirage8–13-0.0223%17 Feb →
overpass8–13-0.0128%17 Feb →
ancient16–130.0522%17 Feb →
overpass6–13-0.0836%17 Feb →
nuke16–13-0.0132%17 Feb →
anubis13–9-0.0325%15 Feb →
nuke11–130.0627%15 Feb →
anubis7–13-0.0716%15 Feb →
nuke13–20.0822%15 Feb →
dust29–13-0.0317%14 Feb →
mirage13–90.0125%14 Feb →
mirage5–13-0.0417%14 Feb →
mirage9–13-0.0218%14 Feb →
mirage9–13-0.0232%11 Feb →
mirage13–11-0.0227%8 Feb →
nuke16–140.0123%8 Feb →
nuke13–7-0.0325%8 Feb →
mirage13–10.0233%7 Feb →
mirage5–13-0.0710%7 Feb →
mirage13–80.0231%7 Feb →
ancient10–13-0.0622%31 Jan →
mirage6–13-0.0034%26 Jan →
anubis13–11-0.0331%26 Jan →
dust213–100.0434%26 Jan →
inferno8–13-0.0325%13 Jan →
overpass13–60.0318%13 Jan →
overpass13–60.0833%11 Jan →

Match data via Leetify.

Recent teammates

Milestones

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

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