𝔭𝔩𝔢𝔯𝔯𝔶 ⸸ — CS2 Stats

DK76561198135983581[U:1:175717853]Steam profile ↗✓ No bans

916Tracked matches54%Win rate2020Tracked since

5,229Hours in CS11Hrs last 2 wks

CSDB Rating6.7 SolidClutch Specialist

Premier CS Rating19,629Top 50% of 185,711 CSDB-tracked playersPurple band · top ~10% of ranked players (population est.)

CSDB Leaderboard#82334 of 232278 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 9 Sep 2026 (11 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 39 days played since 11 May 2026. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 19,629 -1,073 22 May – 9 Sept · 7 days played

21,884Peak Premier in tracked matches

39Days played since 2026-05-11

Premier CS Rating

2,042 below peak (21,671)
+80 over 30 days · steady
-2,042 over 90 days
Next: Pink band at 20,000 — 371 to go
Reached: Pink band · Purple band · Blue band · Light Blue band

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

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=12,417), 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.

Metric	This player	Level 5 median	Level 6 median	vs Level 6
Headshot rate	46.8%	43.8%	44.8%	above
Shot accuracy	17.2%	12.0%	12.4%	above
Kill/death ratio	1.53	1.02	1.04	above
Match win rate	45.1%	44.7%	45.2%	meets

Across every metric we can compare, this profile already matches the typical Level 6 player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

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Performance scores

Aim79

Positioning67

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY44–44–12Last 10044%Win rateTWTWWWLWTW

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · +2.3pp headshot accuracy · −42ms 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

3–0–2 · 60% win rate
Avg rating 0.04
Avg headshot accuracy 15%
Avg reaction 510ms

Last 10

6–1–3 · 60% win rate
Avg rating 0.04
Avg headshot accuracy 19%
Avg reaction 517ms

Last 20

11–5–4 · 55% win rate
Avg rating 0.03
Avg headshot accuracy 18%
Avg reaction 538ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+3.3 against its own average).

Aim7.9

Utility4.9

Positioning6.7

Opening Duels5.3

Clutch10.0

Reliable in 1v1s

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

Plays most like ZywOo 86% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 555ms 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

Aim7.9

Positioning6.7

Utility4.9

Mechanics7.6

Opening Duels4.4

Win Impact6.3

Composite 6.7/10 (Solid), 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 rating0.04−0.00

first ⅓ avg 0.05 → last ⅓ avg 0.04

Reaction time550ms−63ms

first ⅓ avg 613ms → last ⅓ avg 550ms

Headshot accuracy18.9%−0.3%

first ⅓ avg 19.2% → last ⅓ avg 18.9%

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

0.20Best match rating · 7–13 · cache, 28 Jul →

60%Best headshot accuracy · 13–5 · office, 13 May →

391msFastest reaction time · 12–12 · office, 15 Sept →

13–2Biggest win · mirage, 14 Jul →

Across the last 100 tracked matches.

Highlights

6Longest win streak

5–7In matches decided by ≤2 rounds

4Overtime games

Map breakdown

infernoBest map · 62% over 13trainWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	16	5–11	31%	0.05
inferno	A	13	8–5	62%	0.05
nuke	A	12	7–5	58%	0.02
cache	B	12	6–6	50%	0.07
vertigo	C	11	4–7	36%	0.04
mirage	C	10	4–6	40%	0.03
ancient	D	7	2–5	29%	0.02
train	D	6	1–5	17%	0.03
overpass	—	4	3–1	75%	0.08
anubis	—	3	1–2	33%	0.07
office	—	2	1–1	50%	0.05
debris	—	2	1–1	50%	0.06
shelter	—	1	1–0	100%	0.14
fachwerk	—	1	0–1	0%	0.06

Across the last 100 tracked matches.

Lifetime stats

251,394Lifetime kills

1.53K/D · Top 5% of Level 5 players

8,516Matches

45.1%Match win rate · Top 50% of Level 5 players

46.8%Headshot % · Top 50% of Level 5 players

17.2%Shot accuracy · Top 25% of Level 5 players

31,724MVPs

2,714Hours (in match)

5,334Bombs planted

3,616Bombs defused

Most-used weapons

AK-4798,229

M4A4 / M4A1-S51,010

AWP21,936

Desert Eagle12,547

Glock-1811,930

P2000 / USP-S10,743

AUG5,598

Negev3,585

FAMAS3,165

SG 5533,132

Lifetime map wins

15,032dust2

8,541inferno

3,062nuke

2,586train

1,643vertigo

1,247cbble

1,150office

138lake

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

Faceit stats

Combat

203Matches

56%Win rate

1.37Avg K/D

87.0ADR

43%Headshot %

Clutches & streaks

100%1v1 clutch win

0%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Vertigo	1	100%	1.62	21.0
Dust2	1	100%	2.88	23.0
Inferno	1	100%	3.40	17.0
Cache	1	100%	1.75	14.0

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.

18.6%Headshot accuracy

35.0%Accuracy (enemy spotted)

37.1%Spray accuracy

84.4%Counter-strafing

8.8°Preaim

555msReaction time

42.7%T opening success

52.6%CT opening success

0.54Enemies flashed / flash

4.3%Flash assists

7.27HE damage / grenade

7.83Flashes / match

Recommended for you

Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
office	12–12	0.04	9%	15 Sept →
nuke	8–1	-0.02	15%	15 Sept →
debris	8–8	-0.03	7%	9 Sept →
inferno	9–7	-0.00	25%	9 Sept →
overpass	9–4	0.20	19%	9 Sept →
vertigo	9–7	0.05	28%	9 Sept →
mirage	9–13	0.03	18%	9 Sept →
nuke	13–11	0.00	32%	8 Sept →
vertigo	12–12	-0.00	24%	8 Sept →
inferno	13–5	0.13	14%	6 Sept →
nuke	13–5	0.04	11%	6 Sept →
inferno	13–8	0.01	14%	5 Sept →
cache	11–13	0.09	18%	1 Sept →
nuke	6–13	-0.02	17%	1 Sept →
dust2	12–12	-0.05	27%	19 Aug →
nuke	13–8	0.08	15%	19 Aug →
dust2	11–13	0.02	14%	17 Aug →
mirage	10–13	0.04	15%	17 Aug →
inferno	13–10	0.01	15%	13 Aug →
train	13–6	0.01	19%	12 Aug →
shelter	13–6	0.14	46%	10 Aug →
dust2	13–5	0.18	29%	8 Aug →
nuke	13–11	0.05	16%	8 Aug →
mirage	13–4	0.05	18%	5 Aug →
fachwerk	12–12	0.06	19%	4 Aug →
mirage	13–8	0.09	23%	4 Aug →
inferno	13–8	0.09	23%	4 Aug →
ancient	4–13	-0.03	20%	4 Aug →
cache	7–13	0.20	23%	28 Jul →
inferno	6–13	0.07	16%	28 Jul →
nuke	12–16	-0.01	13%	25 Jul →
nuke	11–13	-0.00	15%	25 Jul →
cache	9–13	-0.03	7%	25 Jul →
inferno	4–13	-0.03	14%	25 Jul →
ancient	12–12	0.05	16%	21 Jul →
dust2	8–13	0.09	12%	21 Jul →
dust2	13–11	0.03	25%	21 Jul →
overpass	9–4	0.04	33%	21 Jul →
inferno	9–3	0.11	11%	21 Jul →
debris	9–4	0.15	22%	21 Jul →
inferno	13–6	0.08	16%	20 Jul →
dust2	9–13	0.07	25%	20 Jul →
vertigo	6–13	0.06	28%	18 Jul →
anubis	9–13	0.09	25%	18 Jul →
cache	8–13	-0.03	13%	14 Jul →
mirage	13–2	0.11	32%	14 Jul →
mirage	15–15	0.02	14%	13 Jul →
ancient	11–13	0.03	28%	13 Jul →
cache	13–5	0.02	13%	13 Jul →
train	4–13	0.01	24%	12 Jul →
ancient	13–9	0.01	29%	12 Jul →
mirage	10–13	0.01	15%	12 Jul →
anubis	13–3	0.11	22%	12 Jul →
dust2	13–8	0.04	22%	12 Jul →
cache	13–10	0.08	27%	11 Jul →
cache	9–13	0.13	31%	11 Jul →
mirage	9–13	-0.04	7%	11 Jul →
vertigo	13–6	-0.03	20%	8 Jul →
vertigo	0–3	-0.12	0%	8 Jul →
train	11–13	0.02	17%	8 Jul →
dust2	0–13	-0.04	13%	4 Jul →
dust2	6–13	0.07	29%	27 Jun →
dust2	13–2	0.07	35%	20 Jun →
inferno	4–13	0.11	21%	20 Jun →
dust2	12–12	0.11	20%	17 Jun →
anubis	0–13	-0.01	22%	17 Jun →
inferno	4–13	0.12	20%	17 Jun →
cache	13–9	0.14	20%	10 Jun →
vertigo	12–12	0.12	21%	3 Jun →
ancient	13–5	0.10	23%	3 Jun →
inferno	10–13	-0.01	12%	30 May →
dust2	9–13	0.02	24%	30 May →
overpass	11–8	-0.04	5%	30 May →
inferno	13–10	0.03	16%	30 May →
train	11–13	0.00	13%	23 May →
vertigo	7–13	0.06	19%	23 May →
dust2	13–6	0.10	21%	23 May →
nuke	10–13	-0.00	16%	23 May →
nuke	16–12	0.05	20%	22 May →
dust2	12–16	-0.01	15%	22 May →
cache	13–9	0.09	29%	21 May →
ancient	8–13	-0.05	21%	20 May →
nuke	12–12	0.06	10%	20 May →
vertigo	13–4	0.13	20%	17 May →
dust2	6–13	0.12	28%	17 May →
mirage	13–9	0.05	12%	17 May →
overpass	7–13	0.12	27%	15 May →
ancient	8–13	0.00	10%	15 May →
train	7–13	0.05	16%	15 May →
vertigo	8–13	0.08	20%	15 May →
nuke	13–5	0.01	18%	15 May →
dust2	12–12	0.04	11%	15 May →
mirage	0–13	-0.07	9%	15 May →
cache	12–12	0.05	18%	15 May →
vertigo	9–13	0.01	20%	13 May →
train	11–13	0.08	17%	13 May →
office	13–5	0.05	60%	13 May →
cache	13–6	0.04	25%	13 May →
vertigo	13–3	0.11	20%	11 May →
cache	13–8	0.05	20%	11 May →