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Klenzic

Klenzic — CS2 Stats

CK76561198446216786[U:1:485951058]Steam profile ↗✓ No bans

502Tracked matches52%Win rate2020Tracked since
CSDB Rating4.6 DevelopingSupport
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

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CSDB.GGKlenzicFACEITLevel 3STANDINGTop 90.6% of rankedcsdb.gg/stats

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Performance scores

Aim64
Positioning38
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY43–49–8Last 10043%Win rateLWLLWLWWLL

Last 10 vs previous 10: 0pp win rate · +0.03 avg rating · −2.7pp headshot accuracy · −34ms reaction

Win rate 0pp 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

  • 2–3 · 40% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 14%
  • Avg reaction 547ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 15%
  • Avg reaction 575ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 17%
  • Avg reaction 592ms

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: Support — Utility contribution stands above the rest of this profile (+2.3 against its own average).

Aim6.4
Utility4.3
Positioning3.8
Opening Duels0.0
Clutch0.0

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

ZywOo

Plays most like ZywOo 89% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; lower opening-duel success.

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. 664ms 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

Aim6.4
Positioning3.8
Utility4.3
Mechanics4.8
Opening Duels0.0
Win Impact5.6

Composite 4.6/10 (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 rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time623ms+1ms
first ⅓ avg 622ms → last ⅓ avg 623ms
Headshot accuracy16.6%+0.5%
first ⅓ avg 16.1% → last ⅓ avg 16.6%

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

0.28Best match rating · 9–1 · eldorado, 25 Oct →
44%Best headshot accuracy · 7–13 · mirage, 10 Mar →
453msFastest reaction time · 7–9 · eldorado, 24 Sept →
13–1Biggest win · inferno, 26 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
8–10In matches decided by ≤2 rounds
2Overtime games

Map breakdown

nukeBest map · 83% over 6ancientWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
vertigoC269–1735%0.01
anubisC156–940%-0.01
cacheD124–833%-0.01
mirageA74–357%0.00
eldoradoS64–267%0.06
infernoB63–350%-0.00
nukeS65–183%0.02
ancientD50–50%0.03
office—31–233%-0.02
sanctum—31–233%-0.02
fachwerk—22–0100%0.02
boulder—21–150%0.01
dust2—22–0100%0.03
debris—10–10%-0.05
shelter—10–10%-0.05
train—10–10%-0.05
overpass—10–10%0.01
alpine—11–0100%-0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

64Matches
59%Win rate
1.16Avg K/D
79.5ADR
38%Headshot %

Clutches & streaks

14%1v1 clutch win
43%1v2 clutch win
6Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno450%1.0814.5
Dust2250%0.8412.0
Mirage2100%1.2116.5
Ancient10%1.0716.0
Train1100%1.2714.0
Nuke1100%2.6716.0

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.

16.6%Headshot accuracy
38.5%Accuracy (enemy spotted)
45.5%Spray accuracy
71.5%Counter-strafing
10.5°Preaim
664msReaction time
29.0%T opening success
29.0%CT opening success
0.43Enemies flashed / flash
1.1%Flash assists
8.74HE damage / grenade
8.14Flashes / 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 0.4271 — 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 29.0259% — below the 40% mark we flag

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.

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage4–13-0.0116%25 Oct →
eldorado9–10.287%25 Oct →
inferno10–13-0.0318%29 Sept →
eldorado7–90.0517%24 Sept →
nuke13–110.0014%23 Sept →
cache4–13-0.0211%23 Sept →
fachwerk13–80.0413%27 Aug →
inferno13–10.0729%26 Aug →
anubis13–16-0.0213%23 Aug →
vertigo7–90.0316%19 Aug →
cache2–13-0.087%16 Aug →
ancient3–130.1016%16 Aug →
eldorado9–70.0226%15 Aug →
cache13–100.0426%15 Aug →
inferno3–13-0.0225%13 Aug →
cache13–40.0316%13 Aug →
eldorado5–9-0.0817%13 Aug →
eldorado9–40.0314%3 Aug →
anubis12–120.0012%2 Aug →
vertigo8–13-0.0020%1 Aug →
vertigo8–13-0.0615%1 Aug →
boulder2–13-0.0522%28 Jul →
cache13–11-0.0530%24 Jul →
anubis6–13-0.0613%24 Jul →
eldorado9–60.0613%23 Jul →
anubis1–13-0.064%23 Jul →
cache6–00.0220%23 Jul →
debris2–9-0.0510%23 Jul →
inferno13–100.0425%23 Jul →
dust216–140.0018%23 Jul →
mirage13–6-0.0323%16 Jul →
shelter8–13-0.0512%16 Jul →
boulder13–40.0712%16 Jul →
fachwerk13–100.0012%16 Jul →
mirage13–50.0311%16 Jul →
nuke13–8-0.0213%16 Jul →
ancient10–13-0.0113%9 Jul →
nuke13–80.0620%9 Jul →
vertigo9–130.0312%8 Jul →
cache9–130.038%8 Jul →
cache4–13-0.0419%8 Jul →
cache7–13-0.0112%8 Jul →
vertigo7–9-0.016%7 Jul →
vertigo9–7-0.0117%7 Jul →
anubis3–70.0510%28 Jun →
ancient12–12-0.0119%23 Jun →
anubis13–4-0.0211%21 Jun →
vertigo9–13-0.0210%21 Jun →
ancient6–13-0.019%21 Jun →
nuke13–60.0417%21 Jun →
office11–13-0.0229%3 Jun →
vertigo6–130.1016%25 May →
vertigo2–7-0.077%24 May →
vertigo13–30.239%23 May →
cache4–130.0125%10 May →
cache9–130.0216%9 May →
cache8–13-0.0418%7 May →
sanctum0–8-0.148%26 Apr →
sanctum9–70.049%26 Apr →
mirage1–13-0.0133%25 Apr →
anubis4–13-0.067%25 Apr →
train12–12-0.057%23 Apr →
inferno3–13-0.0419%20 Apr →
anubis13–10-0.067%19 Apr →
vertigo11–13-0.0113%19 Apr →
sanctum8–80.0330%17 Apr →
overpass8–80.0121%17 Apr →
vertigo7–9-0.0514%17 Apr →
nuke8–80.0224%17 Apr →
inferno13–6-0.0311%12 Apr →
vertigo5–13-0.0135%12 Apr →
office4–13-0.078%3 Apr →
office13–90.0219%2 Apr →
mirage13–40.0412%29 Mar →
anubis10–13-0.0612%29 Mar →
vertigo11–13-0.0816%29 Mar →
vertigo13–100.0314%27 Mar →
vertigo7–90.0016%18 Mar →
vertigo13–11-0.0421%14 Mar →
vertigo13–70.1113%13 Mar →
anubis13–10.108%13 Mar →
mirage7–13-0.0444%10 Mar →
anubis13–5-0.080%10 Mar →
vertigo11–130.0213%10 Mar →
mirage13–70.0418%8 Mar →
anubis8–130.0013%8 Mar →
ancient12–120.0610%5 Mar →
vertigo13–40.0125%5 Mar →
vertigo12–12-0.0130%4 Mar →
nuke13–70.0010%4 Mar →
vertigo13–70.0713%27 Feb →
vertigo5–13-0.0313%20 Feb →
anubis13–110.0610%1 Feb →
dust213–70.0524%30 Jan →
anubis13–80.0412%24 Jan →
vertigo13–10.1618%23 Jan →
alpine13–8-0.0110%23 Jan →
vertigo13–20.0310%22 Jan →
anubis11–13-0.0123%17 Jan →
vertigo5–13-0.0314%17 Jan →

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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