Hello Kitty with M4A1-S๐Ÿ€

Hello Kitty with M4A1-S๐Ÿ€ โ€” CS2 Stats

IQ76561199014267354[U:1:1054001626]Steam profile โ†—โœ“ No bans

1,431Tracked matches69%Win rate2020Tracked since
1,413Hours in CS4Hrs last 2 wks
CSDB Rating6.3 SolidSupport
Premier CS Rating22,561Top 25% of 215,558 CSDB-tracked playersPink band ยท top ~5.7% of ranked players (population est.)
CSDB Leaderboard#49934 of 261677 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 14 Nov 2026 (yesterday). 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: 22,561 +6,946 24 Dec โ€“ 14 Nov ยท 25 days played
13,34022,561peak 22,56124 Dec14 Nov
22,561Peak Premier in tracked matches
41Days played since 2025-12-24

Premier CS Rating

  • At peak โ€” 22,561
  • +1,940 over 30 days ยท improving
  • Next: Red band at 25,000 โ€” 2,439 to go
  • Reached: Pink band ยท Purple band ยท Blue band ยท Light Blue band

Premier comes from this profileโ€™s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Pink band among CSDB-tracked players (n=42,632), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here โ€” those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerPink band medianRed band medianvs Red band
Headshot rate47.2%46.9%49.3%2.1% short
Shot accuracy7.6%13.0%13.3%5.7% short
Kill/death ratio1.081.081.120.04 short
Match win rate46.4%46.7%48.5%2.1% short

This profile sits below the typical Red band player on every metric we can compare.

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

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CSDB.GGHello Kitty with M4A1-S๐Ÿ€PREMIER22,561 ยท Pink bandcsdb.gg/stats

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

Performance scores

Aim61
Positioning61
Utility66

0โ€“100 skill scores via Leetify.

Recent form

STEADY48โ€“38โ€“14Last 10048%Win rateWLWWTWTWLW

Last 10 vs previous 10: +10pp win rate ยท โˆ’0.02 avg rating ยท +3.6pp headshot accuracy ยท โˆ’97ms reaction

Win rate +10pp across the last 10 against the 10 before โ€” within the normal variation of a 10-match window (ยฑ20pp), so no real shift yet.

Last 5 ยท 10 ยท 20 matches

Last 5

  • 3โ€“1โ€“1 ยท 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 536ms

Last 10

  • 6โ€“2โ€“2 ยท 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 28%
  • Avg reaction 497ms

Last 20

  • 11โ€“6โ€“3 ยท 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 26%
  • Avg reaction 545ms

Newest first, from the last 100 tracked matches. Each block is its own sample โ€” one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support โ€” Utility contribution stands above the rest of this profile (+1.2 against its own average).

Aim6.1
Utility6.6
Positioning6.1
Opening Duels3.6

Style profile from tracked-match aggregates โ€” 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 โ€” 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 75% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile.

Similarity of playstyle shape across shared dimensions โ€” it says how you play, not that you play at their level. Full comparison โ†’

Strengths & areas to improve

Strengths

T openings. 61% T opening-duel success โ€” entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 61% on T to 40% on CT โ€” first contacts on the defending side are being lost.

Counter-strafing. Only 67% of shots are taken properly stopped โ€” moving-shot inaccuracy is quietly taxing every duel.

Generated by fixed rules over this profile's own numbers โ€” no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim6.1
Positioning6.1
Utility6.6
Mechanics3.9
Opening Duels5.1
Win Impact10.0

Composite 6.3/10 (Solid), a weighted mean of the bars with a small opposition adjustment (ร—1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01โˆ’0.02
first โ…“ avg 0.04 โ†’ last โ…“ avg 0.01
Reaction time537msโˆ’87ms
first โ…“ avg 623ms โ†’ last โ…“ avg 537ms
Headshot accuracy22.1%+4.1%
first โ…“ avg 18.0% โ†’ last โ…“ avg 22.1%

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 ยท 11โ€“13 ยท dust2, 1 Jan โ†’
100%Best headshot accuracy ยท 13โ€“6 ยท anubis, 1 Nov โ†’
375msFastest reaction time ยท 1โ€“13 ยท dust2, 23 Aug โ†’
13โ€“4Biggest win ยท ancient, 23 Aug โ†’

Across the last 100 tracked matches.

Highlights

7Longest win streak
11โ€“9In matches decided by โ‰ค2 rounds
18Overtime games

Map breakdown

nukeBest map ยท 67% over 6dust2Weakest map ยท 39% over 31
MapGradePlayedRecordWin rateAvg rating
dust2C3112โ€“1939%0.02
mirageB3014โ€“1647%0.01
infernoA127โ€“558%0.03
ancientA106โ€“460%0.03
nukeS64โ€“267%0.02
anubisโ€”31โ€“233%0.01
trainโ€”32โ€“167%0.02
overpassโ€”32โ€“167%0.06
cacheโ€”10โ€“10%0.00
vertigoโ€”10โ€“10%-0.09

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (39% over 31). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

39,644Lifetime kills
1.08K/D ยท Top 50% of Pink band
1,958Matches
46.4%Match win rate
47.2%Headshot % ยท Top 50% of Pink band
7.6%Shot accuracy
6,609MVPs
782Hours (in match)
2,733Bombs planted
745Bombs defused

Most-used weapons

AK-4710,912
AWP4,446
SSG 082,079
MP91,443
XM10141,166
Knife1,150

Lifetime map wins

4,698dust2
2,608inferno
1,708vertigo
1,523nuke
211train
187cbble
12office
6lake

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

Skill profile

Aggregate performance across tracked matches โ€” stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

22.4%Headshot accuracy
32.5%Accuracy (enemy spotted)
37.2%Spray accuracy
67.4%Counter-strafing
12.0ยฐPreaim
543msReaction time
60.9%T opening success
40.0%CT opening success
0.64Enemies flashed / flash
9.6%Flash assists
8.72HE damage / grenade
22.62Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag โ€” the measurement behind each one is shown, so you can disagree with it.

  1. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 39.9531% โ€” below the 40% mark we flag

Spend your practice time on Dust 2

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

39% win rate across 31 tracked games โ€” your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy โ†’Dust 2 grenade lineups โ†’

Recent matches

MapScoreRatingHS%Date
inferno13โ€“90.056%14 Nov โ†’
anubis8โ€“13-0.0314%10 Nov โ†’
ancient13โ€“110.0418%10 Nov โ†’
mirage16โ€“14-0.0236%4 Nov โ†’
inferno15โ€“15-0.0121%2 Nov โ†’
dust213โ€“11-0.0225%1 Nov โ†’
ancient15โ€“15-0.0511%1 Nov โ†’
anubis13โ€“60.01100%1 Nov โ†’
dust211โ€“13-0.0110%25 Oct โ†’
nuke13โ€“60.0240%25 Oct โ†’
dust211โ€“130.0526%25 Oct โ†’
inferno13โ€“100.0418%19 Oct โ†’
anubis6โ€“130.0338%19 Oct โ†’
nuke5โ€“13-0.0513%18 Oct โ†’
inferno13โ€“90.0829%25 Sept โ†’
cache15โ€“150.0025%25 Sept โ†’
mirage13โ€“110.0121%25 Sept โ†’
ancient13โ€“90.0418%22 Sept โ†’
mirage13โ€“90.0031%21 Sept โ†’
mirage4โ€“130.0228%21 Sept โ†’
dust213โ€“90.0613%21 Sept โ†’
ancient3โ€“130.0122%21 Sept โ†’
mirage15โ€“15-0.0211%1 Sept โ†’
dust213โ€“8-0.0616%31 Aug โ†’
dust216โ€“130.0419%31 Aug โ†’
inferno13โ€“110.0616%24 Aug โ†’
mirage13โ€“80.0716%24 Aug โ†’
dust21โ€“13-0.0216%23 Aug โ†’
dust213โ€“7-0.0222%23 Aug โ†’
ancient13โ€“40.0611%23 Aug โ†’
inferno13โ€“9-0.026%22 Aug โ†’
dust28โ€“130.0414%20 Aug โ†’
dust213โ€“80.0622%20 Aug โ†’
mirage2โ€“130.0013%20 Aug โ†’
dust215โ€“150.0715%23 Apr โ†’
nuke13โ€“70.0320%23 Apr โ†’
inferno5โ€“130.0314%23 Apr โ†’
ancient8โ€“130.0019%23 Apr โ†’
dust26โ€“11-0.0216%22 Apr โ†’
vertigo7โ€“13-0.0916%18 Apr โ†’
mirage12โ€“12-0.0318%18 Apr โ†’
mirage15โ€“15-0.087%19 Mar โ†’
dust215โ€“15-0.0719%14 Mar โ†’
mirage13โ€“11-0.0114%8 Mar โ†’
dust215โ€“150.0222%8 Mar โ†’
inferno15โ€“150.0415%12 Feb โ†’
dust29โ€“130.0214%6 Feb โ†’
dust213โ€“40.0119%3 Feb โ†’
ancient9โ€“130.005%3 Feb โ†’
mirage15โ€“150.0023%1 Feb โ†’
mirage11โ€“130.0613%1 Feb โ†’
dust213โ€“70.0114%1 Feb โ†’
ancient13โ€“110.066%1 Feb โ†’
dust27โ€“13-0.0314%1 Feb โ†’
dust25โ€“13-0.0514%30 Jan โ†’
mirage16โ€“13-0.0222%30 Jan โ†’
inferno10โ€“130.0010%25 Jan โ†’
nuke13โ€“80.0418%25 Jan โ†’
mirage13โ€“10-0.0013%25 Jan โ†’
mirage13โ€“110.086%25 Jan โ†’
nuke13โ€“110.0330%23 Jan โ†’
dust213โ€“40.0435%23 Jan โ†’
mirage13โ€“80.038%17 Jan โ†’
dust213โ€“70.079%17 Jan โ†’
mirage8โ€“130.0123%11 Jan โ†’
mirage3โ€“13-0.077%11 Jan โ†’
mirage13โ€“60.0227%9 Jan โ†’
mirage13โ€“160.0020%7 Jan โ†’
mirage8โ€“130.0219%7 Jan โ†’
mirage10โ€“130.0719%4 Jan โ†’
inferno13โ€“40.0731%4 Jan โ†’
nuke15โ€“150.0616%4 Jan โ†’
mirage13โ€“10-0.0110%4 Jan โ†’
dust215โ€“150.0214%4 Jan โ†’
dust213โ€“10-0.0121%3 Jan โ†’
mirage13โ€“110.0415%1 Jan โ†’
dust24โ€“110.0720%1 Jan โ†’
mirage13โ€“100.0020%1 Jan โ†’
dust211โ€“130.1523%1 Jan โ†’
mirage13โ€“80.0722%1 Jan โ†’
mirage10โ€“130.048%1 Jan โ†’
mirage11โ€“13-0.0431%1 Jan โ†’
mirage11โ€“130.0816%1 Jan โ†’
inferno16โ€“140.0319%1 Jan โ†’
train13โ€“7-0.029%1 Jan โ†’
train13โ€“100.0811%28 Dec โ†’
dust28โ€“130.0312%28 Dec โ†’
overpass6โ€“130.1018%28 Dec โ†’
dust213โ€“90.0812%28 Dec โ†’
inferno2โ€“130.0118%28 Dec โ†’
dust26โ€“130.0216%28 Dec โ†’
dust211โ€“13-0.0336%26 Dec โ†’
ancient13โ€“100.0412%26 Dec โ†’
dust215โ€“150.0628%26 Dec โ†’
overpass13โ€“80.098%25 Dec โ†’
dust211โ€“13-0.0126%25 Dec โ†’
ancient13โ€“100.1410%25 Dec โ†’
mirage11โ€“13-0.0315%24 Dec โ†’
train6โ€“13-0.0121%24 Dec โ†’
overpass13โ€“7-0.0018%24 Dec โ†’

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone โ†’Inventory value for this account โ†’Where does this rating sit? Premier rank tiers โ†’

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.