kazocker

kazocker — CS2 Stats

76561198054170333[U:1:93904605]Steam profile ↗✓ No bans

640Tracked matches26%Win rate2023Tracked since
CSDB Rating4.2 DevelopingAll-Rounder
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (44 days ago). Ranks are recorded once per day this page is viewed.

+20Tracked matches · now 640
−1.9ppWin rate · 28.0% → 26.1%

Rating over time

Premier CS Rating: 9,187 +218 7 Mar – 9 May · 9 days played
8,4999,307peak 9,3077 Mar9 May
9,307Peak Premier in tracked matches
36Days played since 2026-03-07

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim58
Positioning42
Utility33

0–100 skill scores via Leetify.

Recent form

COLD24–60–16Last 10024%Win rateLTLLWLLWTL

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · −6.9pp headshot accuracy · −30ms 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

  • 1–3–1 · 20% win rate
  • Avg rating 0.07
  • Avg headshot accuracy 17%
  • Avg reaction 586ms

Last 10

  • 2–6–2 · 20% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 17%
  • Avg reaction 592ms

Last 20

  • 5–10–5 · 25% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 20%
  • Avg reaction 607ms

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.

Aim5.8
Utility3.3
Positioning4.2
Opening Duels3.4

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 93% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; 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. 610ms 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

Aim5.8
Positioning4.2
Utility3.3
Mechanics5.6
Opening Duels2.6
Win Impact0.0

Composite 4.2/10 (Developing), 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 rating0.02+0.03
first ⅓ avg -0.01 → last ⅓ avg 0.02
Reaction time613ms−32ms
first ⅓ avg 645ms → last ⅓ avg 613ms
Headshot accuracy18.7%+3.3%
first ⅓ avg 15.4% → last ⅓ avg 18.7%

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

0.32Best match rating · 9–0 · debris, 15 Aug →
38%Best headshot accuracy · 9–1 · debris, 30 Oct →
438msFastest reaction time · 8–8 · eldorado, 13 Aug →
13–3Biggest win · ancient, 19 Apr →

Across the last 100 tracked matches.

Highlights

2Longest win streak
4–7In matches decided by ≤2 rounds
3Overtime games

Map breakdown

overpassBest map · 44% over 9dust2Weakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
infernoD242–228%-0.03
vertigoD195–1426%-0.00
ancientD122–1017%-0.01
anubisD93–633%-0.01
overpassC94–544%-0.02
dust2D60–60%-0.04
trainC52–340%0.00
debris—42–250%0.17
eldorado—31–233%0.04
poseidon—31–233%0.11
cache—31–233%0.02
fachwerk—10–10%-0.04
boulder—10–10%-0.06
stronghold—11–0100%-0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (0% over 6). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

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

16.6%Headshot accuracy
34.4%Accuracy (enemy spotted)
39.8%Spray accuracy
75.0%Counter-strafing
11.6°Preaim
610msReaction time
38.0%T opening success
42.8%CT opening success
0.44Enemies flashed / flash
1.0%Flash assists
10.51HE damage / grenade
2.85Flashes / 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 0.4448 — below the 0.5 mark we flag

    Grenade Lineups →
  2. 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 38.03% — below the 40% mark we flag

Spend your practice time on Dust 2

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

0% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno3–13-0.0510%31 Oct →
inferno8–8-0.027%31 Oct →
eldorado5–90.0813%30 Oct →
vertigo7–90.1118%30 Oct →
debris9–10.2438%30 Oct →
inferno6–9-0.0821%30 Oct →
dust210–13-0.0222%25 Oct →
anubis13–6-0.0111%25 Oct →
vertigo12–120.0112%25 Oct →
debris2–90.0215%24 Oct →
poseidon9–40.2422%24 Oct →
inferno5–9-0.0535%24 Oct →
vertigo5–90.0221%14 Oct →
eldorado9–60.1020%14 Oct →
inferno8–80.0026%14 Oct →
inferno10–130.0425%11 Oct →
vertigo13–110.0816%11 Oct →
vertigo12–120.0134%29 Sept →
ancient12–12-0.0222%29 Sept →
dust23–13-0.0514%29 Sept →
vertigo12–120.0518%11 Sept →
inferno13–6-0.0429%8 Sept →
overpass3–13-0.0317%8 Sept →
ancient2–13-0.0319%8 Sept →
anubis9–130.0213%8 Sept →
inferno6–13-0.0512%1 Sept →
ancient11–13-0.0015%1 Sept →
poseidon8–80.1321%1 Sept →
debris6–90.1114%1 Sept →
dust28–13-0.0419%28 Aug →
inferno5–13-0.0715%28 Aug →
inferno9–13-0.0514%28 Aug →
overpass6–13-0.0211%26 Aug →
ancient12–12-0.0412%21 Aug →
overpass13–90.009%21 Aug →
cache10–13-0.0316%21 Aug →
vertigo13–10-0.0215%20 Aug →
dust20–13-0.0922%20 Aug →
anubis12–12-0.0317%15 Aug →
inferno1–13-0.0817%15 Aug →
vertigo3–13-0.0012%15 Aug →
train13–100.0514%15 Aug →
debris9–00.3216%15 Aug →
inferno15–15-0.0213%13 Aug →
eldorado8–8-0.0513%13 Aug →
anubis13–9-0.038%11 Aug →
vertigo2–9-0.2316%11 Aug →
poseidon8–8-0.0613%11 Aug →
vertigo4–130.0015%2 Aug →
train13–110.0717%28 Jul →
vertigo3–130.036%28 Jul →
anubis13–100.0218%28 Jul →
vertigo12–12-0.0016%24 Jul →
vertigo11–13-0.0119%22 Jul →
fachwerk7–13-0.0418%22 Jul →
boulder2–13-0.0610%22 Jul →
vertigo13–6-0.0118%24 Jun →
inferno13–10-0.0412%24 Jun →
inferno6–130.0129%23 Jun →
train12–12-0.0315%23 Jun →
train12–12-0.059%23 Jun →
inferno8–13-0.0528%11 Jun →
anubis8–13-0.0113%11 Jun →
ancient11–130.0125%11 Jun →
overpass13–100.0020%9 May →
cache13–90.1117%9 May →
cache5–13-0.0117%9 May →
train6–13-0.0314%1 May →
dust28–130.0222%1 May →
inferno7–13-0.077%1 May →
ancient13–3-0.0115%19 Apr →
overpass3–9-0.087%19 Apr →
anubis10–130.0114%19 Apr →
vertigo9–5-0.0618%19 Apr →
anubis7–13-0.0416%19 Apr →
dust25–13-0.0611%10 Apr →
ancient4–13-0.088%10 Apr →
vertigo13–8-0.0216%10 Apr →
inferno9–13-0.0818%8 Apr →
inferno5–13-0.0326%8 Apr →
vertigo8–13-0.0220%8 Apr →
vertigo7–130.0728%8 Apr →
overpass15–150.0216%29 Mar →
ancient9–13-0.025%29 Mar →
stronghold11–9-0.0215%29 Mar →
ancient7–130.0215%27 Mar →
ancient5–130.0119%25 Mar →
ancient3–10.0110%25 Mar →
inferno8–130.0119%25 Mar →
vertigo4–130.0114%25 Mar →
anubis5–13-0.0218%18 Mar →
overpass4–13-0.049%18 Mar →
inferno5–13-0.0515%18 Mar →
inferno11–130.017%15 Mar →
overpass13–9-0.0515%15 Mar →
overpass13–100.0319%15 Mar →
inferno7–13-0.0123%15 Mar →
ancient14–160.0621%13 Mar →
inferno11–130.0314%13 Mar →
inferno10–13-0.0219%7 Mar →

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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