Chunky Milk — CS2 Stats

76561198805278160[U:1:845012432]

574Tracked matches43%Win rate2021Tracked since
532Hours in CS1Hrs last 2 wks
CSDB Rating1.6 Learning
WingmanGold Nova Master
Ladder ranks via Leetify

Performance scores

Aim9
Positioning22
Utility30

0–100 skill scores via Leetify.

Recent form

STEADY464311Last 10046%Win rateLLLWWWWLLW

Last 10 vs previous 10: +10pp win rate · -0.01 avg rating

Player DNA

Aim0.9
Aggression0.0
Utility3.0
Positioning2.2
Opening Duels0.0

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 55% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower opening-fight frequency; 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

T-side openings. Opening success drops from 25% on CT to 9% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 649ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 57% 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

Aim0.9
Positioning2.2
Utility3.0
Mechanics1.5
Opening Duels0.0
Win Impact2.6

Composite 1.6/10 (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-0.07−0.03
first ⅓ avg -0.04 → last ⅓ avg -0.07
Reaction time648ms−18ms
first ⅓ avg 666ms → last ⅓ avg 648ms
Headshot accuracy15.8%+5.5%
first ⅓ avg 10.3% → last ⅓ avg 15.8%

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.

Highlights

0.07Best rating — office 8–13
131Biggest win — train
5Longest win streak
L3Current streak
56In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 67% over 6infernoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
officeC1761135%-0.05
trainA116555%-0.06
cacheC83538%-0.06
overpassC83538%-0.05
nukeS64267%-0.06
infernoD61517%-0.05
anubisB63350%-0.02
vertigoA53260%-0.07
warden43175%-0.05
dust242250%-0.02
ancient41325%-0.08
rooftop42250%-0.05
italy32167%-0.08
alpine330100%-0.07
palacio32167%-0.06
golden31233%-0.00
shelter21150%-0.05
stronghold2020%-0.06
boulder1010%-0.12

Across the last 100 tracked matches.

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

Lifetime stats

9,030Lifetime kills
0.62K/D
890Matches
37.3%Match win rate
39.7%Headshot %
3.1%Shot accuracy
830MVPs
297Hours (in match)
903Bombs planted
120Bombs defused

Most-used weapons

Lifetime map wins

826office
595inferno
519nuke
314dust2
291vertigo
279train
143italy
71cbble

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

Skill profile

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

16.0%Headshot accuracy
18.4%Accuracy (enemy spotted)
26.5%Spray accuracy
56.7%Counter-strafing
13.2°Preaim
649msReaction time
8.6%T opening success
24.7%CT opening success
0.35Enemies flashed / flash
0.9%Flash assists
5.62HE damage / grenade
6.25Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.1938° — above the 12° 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 0.3503 — below the 0.5 mark we flag

    Grenade Lineups
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 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
shelter10–13-0.0511%29 Aug
office0–5-0.1329%29 Aug
boulder11–13-0.1229%9 Jul
shelter13–11-0.0523%9 Jul
cache13–10-0.0610%4 Jul
cache13–60.0116%24 May
office13–10-0.037%16 May
cache3–13-0.1022%16 May
cache5–13-0.087%11 May
office13–10-0.0618%11 May
cache3–13-0.0819%11 May
cache10–13-0.067%4 May
cache3–13-0.0838%4 May
cache13–10-0.0710%29 Apr
train13–7-0.0720%22 Apr
office6–13-0.0213%22 Apr
nuke9–13-0.0813%21 Apr
office13–9-0.0118%21 Apr
warden13–11-0.0321%19 Apr
office1–13-0.0929%12 Apr
warden13–10-0.0633%8 Apr
train7–13-0.1214%7 Apr
inferno5–13-0.148%7 Apr
overpass11–13-0.0912%7 Apr
italy13–10-0.085%4 Apr
alpine13–8-0.079%4 Apr
office12–12-0.1219%4 Apr
dust29–13-0.0116%24 Mar
train10–13-0.0818%24 Mar
office12–12-0.108%11 Mar
alpine13–9-0.0612%11 Mar
nuke13–10-0.060%8 Mar
vertigo12–12-0.059%28 Feb
train12–12-0.078%28 Feb
overpass13–7-0.066%18 Feb
alpine13–4-0.088%3 Feb
stronghold9–13-0.089%27 Jan
warden8–13-0.0617%27 Jan
stronghold12–12-0.0421%23 Jan
warden13–9-0.0318%22 Jan
anubis12–12-0.0716%10 Jan
ancient7–13-0.1015%2 Jan
office13–9-0.0519%2 Jan
nuke9–13-0.088%31 Dec
dust213–50.0429%29 Dec
nuke13–8-0.0524%29 Dec
office13–11-0.044%25 Dec
italy13–9-0.085%25 Dec
train11–13-0.0014%25 Dec
italy8–13-0.0715%24 Dec
office8–130.0710%24 Dec
overpass7–13-0.026%24 Dec
palacio13–6-0.0324%24 Dec
overpass11–13-0.0415%22 Dec
anubis13–30.0210%22 Dec
inferno10–13-0.0513%22 Dec
office9–13-0.0836%20 Dec
train13–7-0.0636%20 Dec
train13–10-0.095%10 Dec
inferno12–12-0.0519%8 Dec
vertigo13–10-0.0817%8 Dec
ancient7–13-0.0913%8 Dec
dust24–13-0.1031%8 Dec
train12–12-0.0119%5 Dec
golden8–13-0.0214%5 Dec
anubis4–13-0.069%2 Dec
nuke13–8-0.0722%2 Dec
palacio6–13-0.107%2 Dec
vertigo13–11-0.0814%30 Nov
train13–7-0.110%30 Nov
ancient13–6-0.0511%30 Nov
inferno8–13-0.055%30 Nov
overpass8–13-0.058%29 Nov
office12–120.022%29 Nov
office11–13-0.0210%27 Nov
vertigo10–13-0.1111%25 Nov
overpass7–13-0.1212%25 Nov
train9–3-0.000%25 Nov
nuke8–3-0.0118%25 Nov
office13–4-0.0316%24 Nov
anubis13–7-0.028%24 Nov
vertigo13–2-0.0416%22 Nov
inferno4–13-0.060%22 Nov
anubis8–13-0.0519%21 Nov
ancient8–13-0.0719%21 Nov
golden7–00.050%21 Nov
train13–1-0.0211%21 Nov
dust213–5-0.014%20 Nov
overpass13–3-0.014%20 Nov
office5–13-0.0815%16 Nov
overpass13–8-0.0427%15 Nov
office11–13-0.0815%10 Nov
inferno13–50.0211%8 Nov
anubis13–50.049%7 Nov
rooftop9–7-0.0625%16 Oct
rooftop6–9-0.079%16 Oct
rooftop8–8-0.0710%16 Oct
rooftop9–30.000%14 Oct
golden12–12-0.0410%11 Oct
palacio13–6-0.0714%8 Oct

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 →