Kaķu Glaudējs

Kaķu Glaudējs — CS2 Stats

LV76561198826411807[U:1:866146079]Steam profile ↗✓ No bans

566Tracked matches43%Win rate2022Tracked since
291Hours in CS
CSDB Rating2.8 LearningSupport
FaceitLevel 2 · 708 ELOTop 97.9% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 17,562 +5,244 25 Dec – 26 Jun · 22 days played
10,11917,562peak 17,56225 Dec26 Jun
17,562Peak Premier in tracked matches
708Highest Faceit ELO seen on CSDB
43Days played since 2025-09-25

Faceit ELO

  • At peak — 708
  • Next: Level 3 at 751 — 43 to go
  • Reached: Level 2

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

Compare periods

Last 30 days vs previous 30

No matches recorded between 7 Sep 2026 and 4 Oct 2026.

Measured 7 Sep 2026 → 4 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 2 among CSDB-tracked players (n=5,923), 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 playerLevel 2 medianLevel 3 medianvs Level 3
Headshot rate51.7%41.3%41.8%above
Shot accuracy1.9%12.7%12.2%10.3% short
Kill/death ratio0.690.950.980.29 short
Match win rate38.4%42.6%43.3%4.9% short

This profile matches the typical Level 3 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 3 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGKaķu GlaudējsFACEITLevel 2 · 708 ELOSTANDINGTop 97.9% of rankedPEAK ELO708csdb.gg/stats

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Performance scores

Aim32
Positioning26
Utility35

0–100 skill scores via Leetify.

Recent form

STEADY30–65–5Last 10030%Win rateLWLWWWLWLL

Last 10 vs previous 10: +20pp win rate · −0.01 avg rating · +1.5pp headshot accuracy · +7ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 700ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 20%
  • Avg reaction 712ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 19%
  • Avg reaction 708ms

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 (+1.3 against its own average).

Aim3.2
Utility3.5
Positioning2.6
Opening Duels0.0
Clutch2.6

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

NiKo

Plays most like NiKo 76% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Areas to improve

Reaction time. 689ms 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

Aim3.2
Positioning2.6
Utility3.5
Mechanics5.5
Opening Duels0.0
Win Impact2.6

Composite 2.8/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05−0.01
first ⅓ avg -0.04 → last ⅓ avg -0.05
Reaction time683ms+21ms
first ⅓ avg 662ms → last ⅓ avg 683ms
Headshot accuracy16.8%+1.1%
first ⅓ avg 15.7% → last ⅓ avg 16.8%

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.

Personal bests

0.07Best match rating · 9–1 · anubis, 24 Jan →
34%Best headshot accuracy · 10–13 · inferno, 22 Oct →
391msFastest reaction time · 4–13 · inferno, 25 Dec →
13–1Biggest win · mirage, 5 Apr →

Across the last 100 tracked matches.

Highlights

4Longest win streak
3–7In matches decided by ≤2 rounds
9Overtime games

Map breakdown

anubisBest map · 67% over 6infernoWeakest map · 21% over 14
MapGradePlayedRecordWin rateAvg rating
mirageD258–1732%-0.04
dust2D206–1430%-0.06
infernoD143–1121%-0.06
ancientD134–931%-0.03
nukeD113–827%-0.05
anubisS64–267%-0.02
overpassD62–433%-0.02
vertigo—20–20%-0.06
cache—10–10%-0.06
palacio—10–10%-0.04
train—10–10%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (21% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

10,297Lifetime kills
0.69K/D
768Matches
38.4%Match win rate
51.7%Headshot % · Top 10% of Level 2 players
1.9%Shot accuracy
1,039MVPs
291Hours (in match)
289Bombs planted
112Bombs defused

Most-used weapons

Lifetime map wins

1,109vertigo
930inferno
667dust2
633nuke
85train
27office

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

Faceit stats

Combat

118Matches
47%Win rate
0.77Avg K/D
67.8ADR
49%Headshot %

Clutches & streaks

33%1v1 clutch win
10%1v2 clutch win
5Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Vertigo3155%0.7612.6
Mirage2642%0.8812.5
Ancient1656%0.7912.3
Inferno1540%0.589.8
Anubis956%0.9312.8
Nuke944%0.7310.2
Dust2838%0.7512.3
Train20%0.387.0

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.

16.7%Headshot accuracy
26.2%Accuracy (enemy spotted)
28.5%Spray accuracy
74.9%Counter-strafing
10.6°Preaim
689msReaction time
20.9%T opening success
26.2%CT opening success
0.44Enemies flashed / flash
3.1%Flash assists
9.01HE damage / grenade
5.59Flashes / 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 0.4428 — 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 20.8623% — below the 40% mark we flag

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.

21% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache3–13-0.0624%28 Aug →
dust213–90.0225%26 Jun →
nuke10–13-0.0515%3 May →
anubis13–9-0.0616%3 May →
anubis13–11-0.037%25 Apr →
mirage13–1-0.0026%5 Apr →
mirage9–13-0.1021%2 Apr →
dust213–4-0.0532%2 Apr →
mirage4–13-0.1024%2 Apr →
nuke2–13-0.097%2 Apr →
vertigo3–13-0.0420%29 Mar →
mirage5–13-0.0618%29 Mar →
anubis4–13-0.0610%28 Mar →
dust29–13-0.0131%22 Feb →
inferno13–8-0.0415%22 Feb →
dust25–13-0.0922%21 Feb →
mirage4–130.0125%14 Feb →
mirage13–5-0.047%14 Feb →
dust213–10-0.0620%14 Feb →
dust213–16-0.0415%13 Feb →
mirage13–100.0012%13 Feb →
ancient9–13-0.0723%13 Feb →
dust215–15-0.0610%5 Feb →
mirage6–13-0.119%5 Feb →
nuke13–9-0.074%3 Feb →
dust215–15-0.047%30 Jan →
mirage13–100.0122%30 Jan →
mirage9–13-0.0213%30 Jan →
overpass13–11-0.0418%30 Jan →
ancient7–13-0.0822%30 Jan →
nuke9–13-0.0117%28 Jan →
anubis13–9-0.039%28 Jan →
dust210–13-0.0913%28 Jan →
ancient11–13-0.0229%24 Jan →
anubis9–10.074%24 Jan →
mirage13–9-0.0510%24 Jan →
inferno13–7-0.0916%24 Jan →
dust213–5-0.0426%23 Jan →
dust26–13-0.0719%22 Jan →
ancient13–30.0324%22 Jan →
anubis5–13-0.0113%20 Jan →
palacio3–13-0.0411%20 Jan →
inferno7–13-0.0513%17 Jan →
ancient9–13-0.0511%17 Jan →
mirage6–13-0.0217%14 Jan →
nuke13–5-0.0013%14 Jan →
inferno13–6-0.0212%11 Jan →
nuke16–13-0.036%11 Jan →
inferno4–13-0.115%10 Jan →
ancient13–8-0.0823%10 Jan →
mirage7–13-0.0121%10 Jan →
nuke3–13-0.0610%10 Jan →
mirage6–13-0.066%10 Jan →
mirage14–16-0.0519%10 Jan →
dust25–13-0.0414%10 Jan →
nuke3–13-0.1415%9 Jan →
mirage4–13-0.0824%9 Jan →
dust28–13-0.1121%8 Jan →
overpass4–13-0.0711%8 Jan →
inferno15–15-0.0513%3 Jan →
train6–13-0.0515%2 Jan →
ancient8–130.0014%31 Dec →
mirage5–13-0.0415%31 Dec →
vertigo3–9-0.0826%30 Dec →
dust26–13-0.0414%30 Dec →
dust24–13-0.065%30 Dec →
inferno10–13-0.079%30 Dec →
nuke15–150.0116%30 Dec →
ancient13–11-0.0626%30 Dec →
mirage8–13-0.0014%28 Dec →
inferno11–13-0.1018%27 Dec →
dust27–13-0.094%27 Dec →
inferno14–16-0.0314%26 Dec →
overpass9–13-0.0320%26 Dec →
dust26–13-0.044%26 Dec →
ancient8–13-0.0110%26 Dec →
nuke1–13-0.0615%26 Dec →
mirage6–13-0.0714%26 Dec →
inferno4–13-0.0312%25 Dec →
mirage11–130.0218%25 Dec →
inferno6–13-0.0211%25 Dec →
mirage13–7-0.0310%25 Dec →
ancient4–13-0.0414%25 Dec →
mirage13–9-0.0426%25 Dec →
overpass10–130.0527%22 Dec →
dust23–13-0.0823%20 Dec →
nuke6–13-0.0523%20 Dec →
mirage13–8-0.037%20 Dec →
inferno11–13-0.0521%20 Dec →
inferno10–13-0.069%20 Dec →
dust213–9-0.109%3 Dec →
ancient15–15-0.0511%17 Nov →
dust213–7-0.0319%17 Nov →
ancient9–130.0122%16 Nov →
mirage5–13-0.1116%16 Nov →
ancient13–7-0.0117%15 Nov →
mirage9–13-0.0515%22 Oct →
inferno10–13-0.0634%22 Oct →
overpass13–80.0110%30 Sept →
overpass11–13-0.038%25 Sept →

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 →

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